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AI's $600B Question

ryandrake
275 replies
21h54m

Others are saying this article is bearish, but then...

A huge amount of economic value is going to be created by AI. Company builders focused on delivering value to end users will be rewarded handsomely.

Such strong speculative predictions about the future, with no evidence. How can anyone be so certain about this? Do they have some kind of crystal ball? Later in the article they even admit that this is another one of tech's all-too-familiar "Speculative frenzies."

The whole AI thing just continues to baffle me. It's like everyone is in the same trance and simply assuming and chanting over and over that This Will Change Everything, just like previous technology hype cycles were surely going to Change Everything. I mean, we're seeing huge companies' entire product strategies changing overnight because We Must All Believe.

How can anyone speak definitively about what AI will do at this stage of the cycle?

TeMPOraL
176 replies
21h37m

How can anyone not see just how impactful it's going to be? Or already is? I can't think of a single recent technology that was so widely adopted by tech and non-tech people alike, immediately integrated into day-to-day experience. The rise of mobile phones and e-commerce in the 90s would be the last time I've seen this happen (I'm not counting smartphones, as those are more of an iteration). Or social media, in purely software space.

I've just had GPT-4o write me a full-featured 2048 clone in ~6 hours of casual chat, in between of work, making dinner, and playing with kids; it cost me some $4 in OpenAI bills, and I didn't write a single line of code. I see non-tech people around me using ChatGPT for anything from comparison shopping to recipe adjustments. One person recently said to me that their dietitian is afraid for their career prospects because ChatGPT is already doing this job better than she is. This is a small fraction of cases in my family&friends circle; anyone who hasn't lived under the rock, or wasn't blinded by the memetic equivalent of looking at a nuclear weapon detonation, likely has a lot of similar things to say. And all of that is not will, it's is, right now.

ryandrake
43 replies
21h27m

How can anyone not see just how impactful it's going to be? Or already is? I can't think of a single recent technology that was so widely adopted by tech and non-tech people alike, immediately integrated into day-to-day experience. The rise of mobile phones and e-commerce in the 90s would be the last time I've seen this happen (I'm not counting smartphones, as those are more of an iteration). Or social media, in purely software space.

You can't know this for certain until you look back on it in retrospect. We did not know mobile phones and e-commerce were going to be huge back in the 90s. We know now, of course, looking back, and the ones who guessed right back then can pat themselves on the back now.

Everyone is guessing. I'll admit it's totally possible LLMs and AI are going to be as earth shattering as its boosters claim it will be, but nobody can know this now with as much certainty as is being written.

TeMPOraL
28 replies
21h22m

You can't know this for certain until you look back on it in retrospect.

Correct, but the thing is, AI blown up much faster than phones - pretty much a decade in a single year, in comparison. Mobile phones weren't that useful early on, outside of niche cases. Generative AI is already spreading to every facet of peoples' lives, and has even greater bottom-up adoption among regular people, than top-down adoption in business.

Quothling
12 replies
20h51m

Correct, but the thing is, AI blown up much faster than phones

What do you base that on though? Two years into the iPhone, Apple reported a $6.75b revenue on iPhone related sales. ChatGPT may reach or surpass that this year considering they're currently at $3.4b. That's not exactly what I would call growing faster than phones, however, and according to this article, very few people outside of nvidia and OpenAI are actually making big money on LLM's.

I do think it's silly to see this wave of AI to be referred to as the next blockchain, but I also think you may be hyping it a little beyond its current value. It being a fun and useful tool for a lot of things isn't necessarily the same thing at it being something that's actually worth the money investors are hoping it will be.

TeMPOraL
9 replies
20h47m

What do you base that on though?

My childhood? I was a teen when mobile phones started to become widely used, and soon after pretty much necessary, in my part of the world. But, to reiterate:

Two years into the iPhone, Apple reported a $6.75b revenue on iPhone related sales.

That's just an iteration, and not what I'm talking about. Smartphones were just different mobile phones. I'm talking about the adoption of a mobile phone as a personal device by general population.

It being a fun and useful tool for a lot of things isn't necessarily the same thing at it being something that's actually worth the money investors are hoping it will be.

That's probably something which needs to be disentangled in these conversations. I personally don't care what investors think and do. AI may be hype for the VCs. It's not hype for regular Janes and Joes, who either already integrated ChatGPT into their daily lives, or see their friends doing so.

threeseed
3 replies
20h26m

This is all just meaningless anecdotes.

And regular Janes and Joes are not using ChatGPT. Revenues would be 10-100x if that were the case.

TeMPOraL
2 replies
20h20m

And regular Janes and Joes are not using ChatGPT. Revenues would be 10-100x if that were the case.

3/4 of the people I know are actively using it are on free tier. And based on all the HN conversations in the last year, plenty of HNers commenting here are also using free tier. I'd never go back to GPT-3.5, but apparently most people find it useful enough to the point they're reluctant to pay that $20/month.

As for the rest, OpenAI is apparently the fastest-growing service of all time ever, so that says something.

ben_w
0 replies
19h59m

I'm one of the free tier people.

A while back I used 3.5 to make a chat web page so I could get the better models as PAYG rather than subscription… and then OpenAI made it mostly pointless because they gave sufficient 4o access to the free tier to meet my needs.

Avshalom
0 replies
19h53m

>apparently most people find it useful enough to the point they're reluctant to pay that $20/month.

Or they find it useless enough that they're unwilling to pay for the upgrade.

kortilla
2 replies
18h43m

Calling the iPhone an iteration is pure nonsense. Mobile phones had tiny utility compared to smartphones.

A phone on the go didn’t fundamentally alter anything except for making coordination while traveling easier. I went through both the cell phone adoption curve and the smartphone curve.

The latter was the massive impact that brought computing to the remaining 85% of the planet and upended targeting desktop operating systems for consumers by default.

Calling smartphones an iteration on cellphones is like calling ChatGPT an iteration on the neural networks we had 10 years ago.

throwup238
1 replies
14h9m

> Mobile phones had tiny utility compared to smartphones

They had tiny utility compared to modern smartphones but the first iPhone was a glorified iPod with a touchscreen and a cellular radio. It didn’t have an app store and the only thing it really did better than other mobile phones was web browsing, thanks to the touchscreen keyboard.

It wasn’t as revolutionary as hindsight now makes it seem. It was just an iteration on PalmPilots and Blackberries.

throwaway2037
0 replies
12h3m

Another thing that is forgotten about the first iPhone: I think Apple negotiated with AT&T (?) to change the voice mail system so you could select from your iPhone (voicemail app?) which message you wanted to listen. Prior, you always needed to call the mobile provider voice mail system, then listen the messages in order (or skip them). That was a huge early selling point for the iPhone. I know -- no one cares about voice mail in 2024, but it used to be very important.

dragontamer
0 replies
20h27m

Its a lot easier to use AI when its basically given away for free than when it cost $399 for a Palm Pilot in the 90s.

For a $399 device, Palm Pilot did well and had an excellent reputation for the time. Phones really took over the PDA market as a personal pocket-computer more-so than being used as ... a phone...

Really, I consider the modern smartphone a successor to the humble PDA. I grew up in that time too, and I remember the early Palm adopters having to explain why PDAs (and later Blackberries) were useful. That was already all figured out by the time iPhone took over.

Quothling
0 replies
12h42m

I personally don't care what investors think and do.

Isn't this a an odd take when you're discussing things on a VC website? In any case, if you like LLM's you probably should care considering it's the $10b Microsoft poured into OpenAI that's made the current landscape possible. Sure, most of those money were fuled directly into Azure because that's where OpenAI does all it's compute, but still.

It's not hype for regular Janes and Joes, who either already integrated ChatGPT into their daily lives, or see their friends doing so.

Are they paying for it? If they aren't then will they pay for it? I think it's also interesting to view the numbers. ChatGPT had 1.6 billion visitors in January 2024, but it had 637 million in May 2024.

Again. I don't think it's all hype, I think it'll change the world, but maybe not as radically as some people expect. The way I currently view it is another tool in the automation tool-set. It's useful, but it's not decision making and because of the way it functions (which is essentially by being very good at being lucky) it can't be used for anything important. You really, really, wouldn't want your medical software to be written by a LLM's programmer. Which doesn't necessarily change the world too much because you really, really, didn't want it to be written by a search engine programmer either. On the flip-side, you can actually use ChatGPT to make a lot of things and be just fine. Because 90% (and this a number I've pulled out my ass, but from my anecdotal experience it's fairly accurate) of software doesn't actually require quality, fault tolerance or efficiency.

sib
0 replies
17h49m

> Correct, but the thing is, AI blown up much faster than phones

What do you base that on though? Two years into the iPhone, Apple reported a $6.75b revenue on iPhone related sales. ChatGPT may reach or surpass that this year considering they're currently at $3.4b.

But the iPhone was launched more than 10 years past mobile phones (in fact, more than 20, but that's stretching it). There were more than 1B mobile phones shipped in 2006, the year before the iPhone launched.

reaperman
0 replies
17h51m

The iPhone was not the first cell phone. Initial adoption of cell phones was much slower than ChatGPT. Think 1980’s/1990’s.

Even when cell phones started getting popular, often only one or two family members would get one. The transition time between “started becoming popular” and “everyone has one” was >5 years and even then it was relatively normal that people would just turn off their cell phone for a few days (to mixed reactions from friends and family).

ryandrake
5 replies
20h37m

Any talk of "regular people" inside the HN bubble is fraught with bias. Commenters here will sometimes tell you that "regular people" work at FAANG, make $400K/yr and have vacation homes in Tahoe. Actual "regular people" use Facebook occasionally, shop at the grocery store, watch Sportsball on TV, and plan their kids' birthday parties or their next vacation. They're not sitting there augmenting their daily lives with ChatGPT.

You're a long time HN contributor and I admit when I see your username, I stop and read the comment because it's always insightful, polite, and often makes me think about things in ways I never have before! But this discussion borders on religious fervor. "Every facet of peoples' lives?" Come on, man!

TeMPOraL
2 replies
20h22m

Actual "regular people" use Facebook occasionally, shop at the grocery store, watch Sportsball on TV, and plan their kids' birthday parties or their next vacation. They're not sitting there augmenting their daily lives with ChatGPT.

I'm aware of the HN bias, but in this case, I'm talking regular, non-tech, sportsball or TikTok watching crowd. Just within my closest circles, one person is using ChatGPT for recipes, and they're proficient at cooking so I was surprised when they told me the results are almost always good enough, even with dietary restrictions in place (such as modifying recipes without exceeding nutrient limits). Another person used it for comparison shopping of kids entertainment supplies. Another actually posted a car sale ad and used gen-AI to swap out background to something representative (no comment on ethics of that). Another is evaluating it for use in their medical practice.

(And I'm excluding a hundred random uses I have for it, like e.g. making colorbooks for my kids when they have very specific requests, like "dancing air conditioners" or whatever.)

ryandrake
1 replies
19h26m

Without data, we're trading anecdotes. Your circle is in the bubble, mine isn't. This user[1] shared a Pew survey, which looks like the best we're going to get. The survey asked what % of people ever used ChatGPT, which I'd interpret as "at least one time ever" and the number is less than 1 in 4. I'd love to see actual data on what percentage of people use it at least once daily, which is the bar I'd accept for "integrated with their daily lives."

1: https://news.ycombinator.com/item?id=40870205

TeMPOraL
0 replies
19h22m

Fair enough. My circle may be in a bubble, and come to think of it, selection bias is a factor - I can think of all the people close to me who use it, but there's more equivalently close friends and relatives who (as far as I know) don't. I do think the survey is giving quite a big results, given we're barely a year into the whole ChatGPT craze - but we can revisit this topic when more data becomes available. I'm sure it'll come up again :).

throwaway2037
0 replies
11h52m

    > work at FAANG, make $400K/yr
Or: work at an unnamed high frequency trading hedge fund, make $800K/yr. (The number of people on HN claiming to be this person surely exceeds the number in the Real World by ... multiples.)

slidehero
0 replies
16h28m

My dad used AI to generate artwork with pictures hung up across the house.

He's intersted in meditation and mindfulness. He's not a native English speaker, so he's using AI to help him write content. He's then using AI text to voice to turn his scripts into YouTube videos. The videos have AI generated artwork too.

My dad is a retired welder in his late 60s. He's as "regular people" as it gets.

I'm a high school teacher and GPT has completely changed teaching. We're using it to help with report writing, lesson planning, resource creation, even for ourselves to get up to speed on new topics quickly.

I'm working on a tool for teachers that's only possible with GPT.

It's by far the single, most transformative technology I've ever encountered.

mrbungie
4 replies
21h16m

Any evidence backing up these claims about adoption?

I thought the same about adoption (across multiple audiences, not just tech workers and/or young people), was faced with surprising poor knowledge about GenAI when making surveys about it in my company. Maybe investors are asking the same questions right now.

fragmede
1 replies
20h48m

the article states

The Information recently reported that OpenAI’s revenue is now $3.4B, up from $1.6B in late 2023.

and links to

https://www.theinformation.com/articles/openais-annualized-r...

That's a lot of $20/month subscriptions. it's not all that but that's a lot of money, regardless.

threeseed
0 replies
20h24m

OpenAI’s revenue is not exclusively subscriptions.

There are a lot of companies building private GPTs and using their API.

Workaccount2
0 replies
20h56m

IIRC openai was the fastest growing service by subscriptions of all time.

tuatoru
2 replies
18h42m

Mobile phones weren't that useful early on, outside of niche cases.

Truck drivers, construction crew, couriers, lawyers, sales people of all kinds, stock brokers, ... Most of the economy that isn't at a desk 996. Pretty big niche, bigger than the non-niche possibly.

You are in a bubble.

relativ575
1 replies
18h28m

Huh? Mobile phone was available commercially in 1980s, and started to proliferate in 1990s. It was definitely not popular in those groups early on. Any of them.

disgruntledphd2
0 replies
8h50m

It was in Europe. I remember that people started to get them in the mid 90's and they were everywhere by the end of that decade.

neta1337
0 replies
12h17m

You are in a bubble, hyping this up way too far

LorenzoBloedow
5 replies
21h23m

I personally attribute this FOMO to so called AI influencers who love "shilling" AGI as something that's as true as 1 + 1 = 2

llm_trw
4 replies
21h13m

I don't get why people insist this is agi any more than a ship is artificial general swimming.

It doesn't matter if it's general, what matters is that its useful. And if you don't find it useful just remember a lot of people in the 00s didn't find google useful either since they already had the yellow pages.

I strongly suggest paying for a subscription to either openai or anthropic and learning quickly.

fragmede
1 replies
20h45m

You don't even have to do that, just go to http://ChatGPT.com and type at it. you don't even need to make an account.

llm_trw
0 replies
20h37m

You get what you pay for, despite what everyone is saying the 4o gpt model is really bad for long form reasoning.

Buy the subscription and use the turbo4 model.

After that api credits so you get access to the playground and change the system prompt. It makes a huge difference if you don't want to chat for 10 minutes before you get the result you want.

okdood64
0 replies
16h57m

learning quickly.

Learning what quickly exactly?

namaria
0 replies
9h40m

Swimming and 'intelligenting' are definitely not in the same category.

VirusNewbie
2 replies
20h14m

I'll admit it's totally possible LLMs and AI are going to be as earth shattering

You don't need earth shattering though. The PC revolution was huge because every company got a bit more productive with things like word processors and printing and email.

The internet (and then later mobile) was big because every company got a revenue boost, from a small one with online presence to a a huge one for e-commerce to transformative with Netflix and streaming services.

Ignoring the more sci-fi claims of AGI or anything, if you just believe that AI is going to make every office worker 10% more productive, surely each company is goign to have to invest in AI, no? Anytime you have an industry that can appeal to every other company, it's going to be big.

wongarsu
1 replies
20h3m

I wouldn't be surprised if in large companies (say >500 office workers) 10% of all office work becomes redundant. Not in the form of each worker getting 10% more productive, but in form of some roles getting eliminated completely and others losing 80% of their workload.

VirusNewbie
0 replies
19h11m

Why? You could make the same argument about PCs or mobile or the Internet?

doe_eyes
1 replies
20h28m

We did not know mobile phones and e-commerce were going to be huge back in the 90s.

Eh? We did. The whole dot-com boom was predicated on that assumption. And it wasn't wrong. But most of the dot-com investments went sideways. In fact, they imploded hard enough to cause a recession.

In the same vein, even if we all agree that AI is fundamentally transformative, it doesn't mean that it's wise to invest money into it right now. It's possible that most or all of these early products and companies will go bust.

ganoushoreilly
0 replies
17h37m

I think this is the right sentiment. I know a handful of AI startups that have raised 10's to 100's of millions. All of them were crushed with gpt-3 and subsequent models. None of them have any real revenue, have crazy burn rates with their compute spend, and generally haven't proven any value with their AI platforms. Most seem to be working on tech to find a problem rather than the inverse. Funds are throwing money on ideas.. that haven't panned out for years now. I worked with one and they were spending 10's of millions per researcher on AI compute... which makes sense if it's directed but most of the researchers were just running off on their own and the company hoped one would figure something out. Very disorganized for the stacks of cash being spent. Similar things have happened in the Cyber Security field just at a lesser scale.

But hey, Nvidia is investing in companies.. to spend money on Nvidia .. infinite money glitch!

anon-3988
1 replies
20h15m

That's his point, we _know_ this. People can already use OpenAI as a replacement for Google search and people are already doing this. You might not think this is a good thing yadda yadda go to the library, but we already know that chat bots are here to stay.

staunton
0 replies
20h1m

There is a huge spectrum between "here to stay" and "changing everything". On another note, I think if the people arguing here would work out quantitative predictions, they would find that a not insignificant part of the "disagreement" about how big we should expect this to really be is in the framing.

LouisSayers
0 replies
20h3m

You can't know this for certain

Except AI is already being used by people (like myself) every day as part of their usual work flow - and it's a huge boost in productivity.

It's not IF it will make an impact - it IS currently making an impact. We're only just moving past early adopters and we're still in the early stages in terms of tooling.

I'm not saying that AI will become sentient and take over humanity, but to think that AI isn't making an impact is to really have your head in the sand at this point.

tempusalaria
32 replies
19h52m

Being able to create 2048 in 6 hours has basically zero economic value.

Can ChatGPT materially and positively impact the code written by big companies? Can it do meaningful work in excel? Can it do meaningful PowerPoint work? Can it give effective advice on management?

Right now we don’t know the answer to those questions. LLM apps can still improve in many ways - better base models, better integration with common enterprise applications, agentic processes, verifiability and so on - so there is definitely hope that there will be significant value created. Companies and people are excited because there’s huge potential. But it is really just potential right now … current systems aren’t creating real enterprise value at this moment in time

TeMPOraL
21 replies
19h46m

Can ChatGPT materially and positively impact the code written by big companies? Can it do meaningful work in excel? Can it do meaningful PowerPoint work? Can it give effective advice on management?

Right now we don’t know the answer to those questions.

I know the answer to the first three. Yes, yes, and yes. I've done them all, including all of them in the past few weeks.

(Which is how I learned that it's much better to ask ChatGPT to use Python evaluation mode and Pandoc and make you a PPTX, than trying to do anything with "Office 365 Copilot" in PowerPoint...)

As for the fourth question - well, ChatGPT can give you better advice than most advice on management/leadership articles, so I presume the answer here is "Yes" too - but I didn't verify it in practice.

current systems aren’t creating real enterprise value at this moment in time

Yes, they are. They would be creating even more value if not for the copyright and exports uncertainty, which significantly slows enterprise adoption.

WgaqPdNr7PGLGVW
17 replies
19h35m

I know the answer to the first three. Yes, yes, and yes.

You say this but from a management perspective at a large enterprise software company I have not seen it.

Some of our developers use copilot and gpt and some don't and it is incredibly difficult to see any performance difference between the groups.

We aren't seeing higher overall levels of productivity.

We aren't seeing the developers who start using copilot/gpt rush ahead of their peers.

We aren't seeing any ability to cut back on developer spend.

We aren't seeing anything positive yet and many developers have been using copilot/gpt for >1 year.

In my opinion we are just regaining some of the economic value we lost when Google Search started degrading 5-10 years ago.

TeMPOraL
7 replies
19h30m

We aren't seeing higher overall levels of productivity.

You can't measure productivity for shit, otherwise companies would look entirely differently. Starting from me not having to do my own finances or event planning or hundred other things that are not my job description, not my specialty, and which were done by dedicated staff just a few decades ago, before tech "improved office productivity".

We aren't seeing the developers who start using copilot/gpt rush ahead of their peers.

That's because individual productivity is usually constrained by team productivity. Devs rushing ahead of their teammates makes the team dysfunctional.

We aren't seeing any ability to cut back on developer spend.

Devs aren't stupid. They're not going to give you an opportunity if they can avoid it.

We aren't seeing anything positive yet and many developers have been using copilot/gpt for >1 year.

My belief is that's because you aren't measuring the right things. But then, no one is. This is a problem well-known to be unsolved.

WgaqPdNr7PGLGVW
6 replies
19h12m

You can't measure productivity for shit

We can't measure small changes and we aren't great at comparing across orgs.

However, at the director level we can certainly see a 50% or 100% productivity improvement in our teams and with individuals in our teams.

We aren't seeing changes of this magnitude because they don't exist.

WgaqPdNr7PGLGVW
2 replies
19h3m

There are other potential explanations.

Perhaps developers are now slacking off.

Perhaps we have added more meetings because developers have more free time.

Or perhaps developers were never the bottleneck.

We can see large productivity improvements when we make simple changes like having product managers join the developers daily standup meetings. We can even measure productivity improvements from Slacks/Zooms auto-summary features. Yet gpt/copilot doesn't even register.

Vegenoid
0 replies
17h47m

We can even measure productivity improvements from Slacks/Zooms auto-summary features.

While not code generation, this auto-summary is powered by the same tech. I think using it to sift through and surface relevant information, as opposed to generation of new things, will have the biggest impact.

By far the greatest value I get out of LLMs is asking them to help me understand code written by others. I feel like this is an under-appreciated use. How long has this feature been in Copilot? Since February or so? Are people using it? I do not use Copilot.

SanderNL
0 replies
10h28m

Or perhaps developers were never the bottleneck.

Now that's dangerous thinking, but I think you are onto something.

bongodongobob
1 replies
18h11m

I use ChatGPT copilot etc to reduce my cognitive load and get a lot of things done quicker so I also have more time to fuck around. You're out of your goddamn mind if you think I'm going to increase my output for the mere chance that maybe I'll get an above inflation raise in a year. "We gave our devs a magic 10% productivity boost machine, but their output hasn't increased? I guess the machine doesn't work..." It's amusing how out of touch you are.

amanaplanacanal
0 replies
4h23m

There is an ethical question in here that I don’t have an answer for. As an employee, I find a way to do my job more efficiently. Do I hand those efficiencies to my employer so I can get a pat on the head, or do I keep them to myself to make my own life less stressful? If I give them to the boss, do they even have the ability to increase my pay? Using the extra time to slack off rather than enriching the employer might be the best choice.

Edit: and now I see chillfox made the same point.

mbernstein
0 replies
18h57m

Out of curiosity what are you using to measure developer productivity platform or metrics wish (if beyond typical sprint metrics)?

afro88
3 replies
19h17m

Writing code is just one part of the process. Other bottlenecks might prevent you from seeing overall productivity improvements.

For example:

- time between PRs being created and being picked up for review and merged

- time spent on releasing at end of sprint cycles

- time spent waiting for QA to review and approve

- extreme scrum practices like "you can only work on things in the sprint, even if all work is done"

How are you measuring developer productivity? Were those that adopted copilot and chatgpt now enabled to finally keep up with their faster peers (as opposed to outstrip them)? Is developer satisfaction improved, and therefore retention?

WgaqPdNr7PGLGVW
2 replies
18h51m

Yes, other bottlenecks might be preventing us from seeing overall productivity improvements. We might require large organisational changes across the industry in order to take advantage of the improvements.

I guess we will see if smaller startups without many of our bottlenecks are suddenly able to be much more competitive.

How are you measuring developer productivity?

We use a host of quantitative and qualitative measures. None of them show any positive improvements. These include the basics like roadmap reviews, demo sessions, feature cycle time, etc as well as fairly comprehensive business metrics.

In some teams every developer is using copilot and yet we can't see any correlation with it and improved business metrics.

At the same time we can measure the impact from changing the label on a button on our UI on these business metrics.

Were those that adopted copilot and chatgpt now enabled to finally keep up with their faster peers

No.

Is developer satisfaction improved, and therefore retention?

No.

afro88
1 replies
14h9m

We use a host of quantitative and qualitative measures. None of them show any positive improvements. These include the basics like roadmap reviews, demo sessions, feature cycle time, etc as well as fairly comprehensive business metrics.

Those are very high level. If there's no movement on those, I'd guess there are other things bottlenecking the teams. They can code as fast as possible and things still move at the same pace overall. Nice thing to know.

If you want to really test the hypothesis that Copilot and ChatGPT have no impact on coding speed, look at more granular metrics to do with just coding. The average time from the moment a developer picks up a work item to the time it gets merged (assuming code reviews happen in a timely fashion). Hopefully you have historical pre-AI data on that metric to compare to.

Edit: and average number of defects discovered from that work after merge

WgaqPdNr7PGLGVW
0 replies
12h5m

look at more granular metrics to do with just coding. The average time from the moment a developer picks up a work item to the time it gets merged (assuming code reviews happen in a timely fashion)

We do collect this data.

I personally don't put a lot of stock in these kinds of metrics because they depend far too much on the way specific teams operate.

For example perhaps Copilot helps developers understand the codebase better so they don't need to break up the tasks into such small units. Time to PR merge goes up but total coding time could easily go down.

Or perhaps Copilot works well with very small problem sizes (IMO it does) so developers start breaking the work into tiny chunks Copilot works well with. Time to PR merge goes way down but total code time for a feature stays the same.

For what it is worth I do not believe there have been any significant changes with these code level metrics either at the org level.

Sysreq2
1 replies
18h53m

Is it the superstars or the line holders that have been the first adopters? I could speculate, but I am actually curious what you are seeing in practice.

WgaqPdNr7PGLGVW
0 replies
18h43m

The first adopters seem to be the same group / personality type that is always first to adopt new technologies.

Very few of these are the superstars. But plenty are good solid senior developers.

chillfox
0 replies
17h21m

Passing on personal productivity gains to management is always a HUGE L for the individual worker.

As a dev, you can use the saved time to slow down and not be stressed, spend more time chatting with colleagues, learn new skills, maybe improve the quality of the code, etc. Or you can pass it on to management which will result in your workload being increased back to where you are stressed again and your slower colleagues will be let go, so now you get to feel bad about that and they won't be around to chat with.

I have never in my life seen workers actually get rewarded with pay raises for improved productivity, that is just a myth the foolish chase, like the pot of gold at the end of the rainbow.

I have also tried being the top performer on a team before (using automation tools to achieve it), and all I got was praise from management. That's nice, but I can't pay for my holidays with praise, so not worth it.

SanderNL
0 replies
10h31m

We aren't seeing higher overall levels of productivity.

We aren't seeing the developers who start using copilot/gpt rush ahead of their peers.

You think we are antsy worker bees, hastily rushing forwards to please the decision maker with his fancy car?

You are leadership. It's not hard. Cui bono, follow the money, etc. The incentives are clear.

If me and my peers were to receive a magic "do all my work for me" device I can assure you exactly zero percent of that knowledge will reach your position. Why would it? The company will give me a pat on the back. I cannot pay with pats on the back. Your Tesla cannot be financed with pats on the back. Surely you understand the nature of this issue.

CuriouslyC
0 replies
19h21m

If you write a spaghetti system where collecting the context for the AI is a big time sink, and there are so many service/language barriers that AI get confused, of course AI is going to suck. Of course, if you give your programmers a game pad and tell them to use it to program with a virtual keyboard, they're gonna suck ass too, so you should consider where the fault really lies.

kortilla
1 replies
18h49m

Which is how I learned that it's much better to ask ChatGPT to use Python evaluation mode and Pandoc and make you a PPTX, than trying to do anything with "Office 365 Copilot" in PowerPoint...

Can you elaborate on what this saved over just making the ppt the old fashioned way?

TeMPOraL
0 replies
10h54m

"I have this set of notes attached below; would you kindly group them by X and tabulate, and then use Python with Pandoc to make me a PowerPoint with that table in it, plus an extra slide with commentary from the notes?"

Attach notes, paste, press Enter, wait half a minute, get back a PPTX you can build on, or just restyle[0].

Sure, it's faster to build the presentation yourself than to make ChatGPT make the whole thing for you. But the more time-consuming and boring parts, like making tables and diagrams and summaries from external data or notes, is something ChatGPT can do in a fraction of time, and can output directly into PPTX via Pandoc.

(There's a lot of fun things you can do with official ChatGPT and Python integration. The other day I made it design, write and train a multi-layer perceptron for playing tic-tac-toe, because why waste my own GPU-seconds :).)

--

[0] - In contrast, if you make the same request in PowerPoint's O365 Copilot, it'll barf. Last time I tried, it argued it has no capability to edit the document; the time before that, it made a new slide with text saying literally "data from the previous message".

tempusalaria
0 replies
18h47m

I think you’re thinking about things very locally. Of course ChatGPT can help with some coding - I use it for regex quite often cause I never really learned that well.

The problem is that at the average medium sized company code looks like this - you have 1mln lines of code written over a decade by a few hundred people. A big portion of the code is redundant, some of it is incomplete, much of it is undocumented. Different companies have different coding styles, different testing approaches, different development dynamics. ChatGPT does not appreciate this context.

Excel has some similar problems. First of all Excel is 2 dimensional and LLMs really don’t think in 2 dimensions well. So you need to flatten the excel file for the LLM. A common approach to do this with LLMs is using pandas and then using the column and row names to index into the excel.

Unfortunately, excels at companies cannot be easily read using pandas. They are illogically structured, have tons of hardcoding, intersheet referencing is weird circular ways and so on. I spent some time in finance and sell side equity research models are written by highly trained financial analysts and are substantially better organized than the average excel model at a company. Even this subset of real world models is far from suitable for a direct pandas interpretation. Parsing sell side models requires a delicate and complex interpretation before being fed into an LLM.

reaperman
2 replies
17h58m

Can it give effective advice on management?

My friends at McKinsey say that while it can’t fine-tune reports and presentations with quite enough nuance, it does a good job sifting through lots of shit to pick out important parts they should pay more attention to, highlighting data/talking points that contradict a working hypothesis, assisting in writing emails, and other time-consuming or very nit-picky tasks.

That said, no one I know has fed it real customer data, that would be a career-ending event. But self-hosted models like Gemma2 open up the possibility for using LLMs against real customer info.

munificent
1 replies
17h49m

Hard to tell if that says more about the value of LLMs or the lack of value of McKinsey...

throwaway2037
0 replies
12h21m

    > the lack of value of McKinsey
Leaving McKinsey's specific brand value aside, people always miss the value of "hiring (business) consultants". You basically get insider knowledge about how competitors businesses and systems work. So if you ask for advice about how to build a healthcare app for smartphones, you hire McKinsey (or whomever) to tell you "about the market". But really, they are just telling you about what they saw at other competitors. For some business decisions, it is very valuable.

ern
2 replies
16h56m

Can it do meaningful PowerPoint work

Yes, it absolutely can. I threw together a PowerPoint presentation with a script for a low-value, high visibility meeting a couple of weeks ago with ChatGPT 4.0 and a PowerPoint plugin. Everyone loved it.

throwaway2037
1 replies
12h20m

    > low-value, high visibility meeting
This is such a gem. Can you tell us more about the meeting? A senior manager kicking the tyres, or what? Any funny bike-shedding stories to tell?

ern
0 replies
11h50m

Corporate values. Drew the short straw, but had to present something.

nl
1 replies
16h11m

Can it do meaningful work in excel?

Yes it can.

But more importantly have you tried ChatGPT Data Analyst?: https://openai.com/index/improvements-to-data-analysis-in-ch...

It drops the barrier for "pretty good data analysis" to effectively zero.

Can it do meaningful PowerPoint work?

Canva and Figma are both building this and they are pretty decent right now. Better than most PowerPoints I've seen.

The aforementioned Data Analyst does good presentations in a different way, too.

Can it give effective advice on management?

Yes. Unfortunately can't talk about this except it is mindblowingly good.

TeMPOraL
0 replies
10h51m

The aforementioned Data Analyst does good presentations in a different way, too.

And on top of that, it can do PowerPoint presentations too - magic keywords are "use Python and Pandoc".

mdorazio
0 replies
19h18m

Can ChatGPT materially and positively impact the code written by big companies?

It already has at a Fortune 100 company I contract with currently.

Can it do meaningful work in excel?

We can quibble about what "meaningful" means, but it satisfactorily answered questions for two friends about how to build formulas for their datasets and is currently being used to summarize data insights from a database at a different large client (Excel =/= database, but the point stands).

Can it do meaningful PowerPoint work?

I've used Midjourney multiple times a month to generate base imagery for various things in PowerPoint (usually requires modification in Photoshop, but saves me several hours each time compared to digital painting or photobashing from scratch).

Can it give effective advice on management?

Again, what does "effective" mean in the context of management? I've seen VP-level individuals with hundreds of people in their orgs using AI tools for different things.

It really feels like a significant chunk of the HN crowd is living in a bubble with respect to AI in the real world right now. It's absolutely invading everything. As for how much revenue that will translate into long-term vs. the investment dollars being poured into it, that's a more interesting question to discuss.

fragmede
0 replies
13h40m

Being able to create 2048 in 6 hours has basically zero economic value.

That's actually a really good point. In the realm of programming, things that were previously not done because they were too expensive can now be done. Prior to ChatGPT, GP could have a) done it themselves, but the cost was too high/it wasn't worth their time, b) found enough time to write a spec, found someone on upwork/etc, paid them to make it, except that costs money they didn't want to spend, or c) just not do it. Now, GP can code this thing up while watching netflix with the kids or whatever. What programs do not exist that previously did not have the economic value to exist, but now can, thanks to programming time getting cheaper?

Now apply that to fields outside of programming. LLMs' ability to program is front and center here, since many of us can program, but they do other things as well.

cfeduke
27 replies
20h15m

Okay I guess I've just had a different experience entirely. Maybe I'm jaded by hallucinations.

The code ChatGPT generates is often bad in ways that are hard to detect. If you are not an experienced software engineer, the defects could be impossible to detect, until you/ChatGPT has gone and exposed all your customers to bad actors, or crash at runtime, or do something terribly incorrect.

As far as other thought work goes, I am not consulting ChatGPT over, say, a dietician or a doctor. The hallucination risk is too high. Producing an answer is the not the same as producing a correct answer.

itsoktocry
8 replies
19h30m

If your procees is asking it to "write me all this code", then you slap it in production, you're going to have a bad time. But there's intermediate ground.

I am not consulting ChatGPT over, say, a dietician or doctor

Do you know any doctors, by chance? You have way more faith in experts than I do.

kortilla
7 replies
18h52m

ChatGPT is just statistically associating what it’s observed online. I wouldn’t take dietary advice from the mean output of Reddit with more trust than an expert.

interstice
3 replies
18h43m

Doctors can be associating what they’ve learned, often with heavy biases from hypochondriacs and not enough time per patient to really consider the options.

I’ve had multiple friends get seriously ill before a doctor took their symptoms seriously, and this is a country with decent healthcare by all accounts.

Human biases are bad too.

abraae
1 replies
14h7m

Doctors can be associating what they’ve learned, often with heavy biases from hypochondriacs

So true. And it's hard to question a doctor's advice, because of their aura of authority, whereas it's easy to do further validation of an LLMs diagnosis.

I had to change doctor recently when moving towns. It was only when chancing on a good doctor that I realised how bad my old doctor was - a nice guy but cruising to retirement. And my experience with cardiologists has been the same.

Happy to get medical advice from an LLM though I'd certainly want prescriptions and action plans vetted by a human.

throwaway2037
0 replies
13h12m

    > It was only when chancing on a good doctor that I realised how bad my old doctor was
How did you determine the new doctor is "good"?

theshackleford
0 replies
12h10m

By the time a doctor paid me enough attention to realise something was wrong I had suffered a spinal cord injury whose damage can never be reversed. I’m not falling all over myself to trust chatgpt, but I got practically zero for doctors either. Nobody moved until I threatened to start sueing.

aworks
0 replies
1h41m

I sometimes use ChatGPT to prepare for a doctor's visit so I can have a more intelligent conversation even if I may have more trust overall in my doctor than in AI.

XajniN
0 replies
15h49m

I’ve seen so many doctors advertising or recommending homeopathic “medicines” or GE-132 [1], that I would be fairly more confident in an LLM + my own verification from reliable sources. I’m no doctor, but I know more than enough to recognize bullshit, so I wouldn’t just recommend this approach to everyone.

[1] https://pubmed.ncbi.nlm.nih.gov/1726409/

TeMPOraL
0 replies
12h20m

You realize that "online" doesn't just mean Reddit, but also Wikipedia and arXiv and PubMed and other sources perused by actual experts? ChatGPT read more academic publications in any field than any human.

jakderrida
3 replies
11h37m

The code ChatGPT generates is often bad in ways that are hard to detect. If you are not an experienced software engineer, the defects could be impossible to detect

I keep hearing this, but it's incorrect. While I only know R, which is obviously a simple language, I would never type out all my code and go without testing to ensure it does what I intended before using it regularly.

So I can't imagine someone that knows a more complex language just typing out all of it before integrating it into business systems at their work or anything else before testing it.

Why would AI be any different?

Why the hell are AI skeptics acting like getting help from an LLM would involve not testing anything? Of course I test it! Why on earth wouldn't I? Just as I tested code made by freelancers I hired on commission before using the code I bought from them. Do AI skeptics really not test their own code? Are you all insane?

disgruntledphd2
2 replies
9h35m

While I only know R, which is obviously a simple language

Take it from someone who started with R, R is 100% not a simple language. If you can write good R, you're probably a surprisingly good potential SE as R is kinda insane and inconsistent due to 50+ years of history (from S, to R etc).

jakderrida
1 replies
8h28m

Hmmm.. I'm trying to imagine interviewing for SE and telling them I got wealthy from a crypto market-making algorithm I coded in R during Covid and the interviewer responding with anything but laughter or with silence as they ponder legal ways to question my mental health.

It's an excellent language, I think, for many reasons. One is that you can work with data within hours because even before learning what packages or classes are, you got native objects for data storage, wrangling, and analysis. Even import my Excel data and rapidly learn the native function cheat sheet so fast that I was excited to learn what packages are because I couldn't wait to see what I could do.

That was my experience in like 2010, maybe, and after having C++ and Python go in and out my head during college multiple times. I view R as simple only because I actually felt more helpless to keep learning it than helpless to ever learn coding at all. Worth noting that I was a Stat/Probability tutor with a Finance degree and much Excel experience.

disgruntledphd2
0 replies
8h12m

That was my experience in like 2010, maybe, and after having C++ and Python go in and out my head during college multiple times. I view R as simple only because I actually felt more helpless to keep learning it than helpless to ever learn coding at all. Worth noting that I was a Stat/Probability tutor with a Finance degree and much Excel experience.

Ah yeah, makes sense. That's the happy path for learning R (know enough stats etc to decode the help pages).

That being said, R is an interesting language with lots of similarities to both C based languages and also Lisp (R was originally a scheme intepreter), so it's surprisingly good at lots of things (except string manipulation, it's terrible at that).

remarkEon
2 replies
10h58m

The code ChatGPT generates is often bad in ways that are hard to detect. If you are not an experienced software engineer, the defects could be impossible to detect, until you/ChatGPT has gone and exposed all your customers to bad actors, or crash at runtime, or do something terribly incorrect.

I wonder about this a lot, because there's a future here where a decent amount of software engineering is offloaded to these AIs and we reach a point, in the near future, where no one really knows or understands what's going on. That seems bad. Put another way, suppose that your primary care doctor is really just using MedAI to diagnose and recommend treatment for whatever it is you went in to see him about. Over time, these sorts of shortcuts metastasize and the doctor ends up not really knowing anything about you, or the other patients, or what he's really doing as a doctor ... it's just MedAI (with whatever wrongness rate is tolerable for the insurance adjusters). Again, seems bad. There's a palpable loss of human knowledge here that's enabled by a "tool" that's allegedly going to make us all better off.

disgruntledphd2
1 replies
9h37m

The closest analogy here is that we don't have as full-featured autopilots in airplanes as we could, because they reduce safety.

remarkEon
0 replies
47m

Right, good point. Maybe I'm making an argument that some features, or scope of features, should be highly regulated along the same lines.

nvarsj
2 replies
19h42m

I agree. I've just seen it hallucinate too many things that on the surface seem very plausible but are complete fabrications. Basically my trust is near 0 for anything chatgpt, etc. spits out.

My latest challenge is dealing with people that trust chatgp to be infallible, and just quote the garbage to make themselves look like they know what they are talking about.

gwervc
1 replies
19h19m

things that on the surface seem very plausible but are complete fabrications

LLMs are language model, it's crazy people expect them to be correct in anything beyond surface level language.

nvarsj
0 replies
9h20m

Yeah, I was probably being a bit too harsh in my original comment. I do find them useful, you just have to be wary of the output.

ern
1 replies
16h59m

I recently needed to help a downstream team with a problem with an Android app. I never did mobile app dev before, but I was able to spin up a POC (having not coded in Java for 22 years) and solve the problem with the help of ChatGPT 4.0.

Sure I probably would have been able to do it without ChatGPT, but it was so much easier to have something to bounce ideas off-of. A safety net, if you will.

The hallucination risk was irrelevant: it did hallucinate a little early on. I told it it was a hallucinating, and we moved onto a different way of solving the problem. It was easy enough to verify it was working as expected.

gexla
0 replies
14h19m

Seems to me this is the equivalent of fast retrieval and piecing together from a huge amount of examples in the data. This might take far more time if you were to do this yourself. That's a plus for the tools. In other words, a massively expensive (for the service provider) auto-complete.

But try to do something much more simple but has much fewer examples (a typical case is something which has bad documentation) in the data, and it falls apart. I even tried to use Perplexity to create a dead simple CLI command, and it hallucinated an answer (looking at the docs, it misused the parameter, and may have picked up on someone who gave an incorrect answer in the data.)

CuriouslyC
1 replies
19h17m

Easy answer. Ask ChatGPT to write testable code, and tests for the code, then just verify the tests. If the tests don't work, have ChatGPT use the test output to rewrite the code until it does.

If you can't have ChatGPT write testable code because of your architecture, you have other problems. People with bad process and bad architecture saying AI is bad because it doesn't work well with their dumpster fire systems, 100% facepalm.

aleph_minus_one
0 replies
1h56m

If you can't have ChatGPT write testable code because of your architecture, you have other problems.

There exist lots of reasons why code is hard to test automatically that have nothing to do with the architecture of the code, but with the domain for which the code is written and runs.

sumedh
0 replies
19h57m

The code ChatGPT generates is often bad in ways that are hard to detect.

Does it work though, yes it does. There are many human coders who write bad code and life goes.

ignoramous
0 replies
19h49m

Okay I guess I've just had a different experience entirely.

I've seen both the good and the bad. I really like the good parts. Most recently, Claude Sonnet 3.5 fixed a math error in my code (I prompted it to check for it from a well-written bug report, and it did it fix it ever so perfectly).

These days, it is pretty much second nature for me to pull up a new file & prompt Copilot to complete writing the entire code from my comment trails. I don't think I've seen as much change in my coding behaviour since Borland Turbo C -> NetBeans.

dmix
0 replies
12h34m

It's already gotten significantly better and faster in a few yrs. Maybe LLMs will hit a wall in the next 5yrs but even if it does it's still extremely useful and there are always other ways to optimize the current technology where this is already a major development for society.

TeMPOraL
0 replies
20h2m

My experience actually agrees with you. It's just that the set of use cases that either:

- Are hard (or boring) to do, but easy to evaluate - for me, e.g. writing code, OCR, ideation; or

- Don't require a perfectly correct answer, but more of a starting point or map of the problem space; or

- Are very subjective, or creative, with there being no single correct answer,

is surprisingly large. It covers pretty much everything, but not everything for everyone at the same time.

elicksaur
8 replies
19h46m

I can't think of a single recent technology that was so widely adopted by tech and non-tech people alike, immediately integrated into day-to-day experience.

This is not meant to be an offense, but you are in a bubble. The vast, vast majority of people do not use LLMs in their day-to-day life. That’s ok, we’re all in our own bubbles.

You should also post the 2048 clone as proof. Lots people saying they built X in Y minutes with AI. But, when it’s inspected, it’s revealed it very obviously doesn’t work right and needs more development.

TeMPOraL
4 replies
19h36m

You should also post the 2048 clone as proof.

I posted it twice already in this thread, but I guess third time's the charm: http://jacek.zlydach.pl/v/2048/ (code: https://git.sr.ht/~temporal/aider-2048).

It's definitely not 100% correct (I just spotted a syntactic issue in HTML, for example), and I bet a lot of people will find some visual issue on their browser/device configuration. I don't care. It works on my desktop, it works on my phone, it's even better than the now-enshittified web and Android versions I used to play. I'm content :).

cout
3 replies
19h13m

It is too large for my phone display (iphone SE). Do you think chatgpt can fix it?

TeMPOraL
2 replies
10h17m

Yes. It does so trivially, but in the process it breaks the CSS for larger screens. I couldn't get it to get both to work at the same time in 5 minutes of trying. My modern CSS skills aren't good enough to quickly notice what the problem is, so it's beyond my horizon of caring (but I do encourage hints I could pass on to the AI).

elicksaur
1 replies
4h47m

Yes. It does so trivially

but in the process it breaks the CSS for larger screens.

So, no, it doesn’t fix it trivially. Also isn’t correctly sized on iPhone 11 Safari.

TeMPOraL
0 replies
54m

It does fix it trivially, just in a way that causes regression on larger screens :).

As mentioned above, I don't care. It's sized correctly for the devices I use to play it, and I'm not going to put any more work into this. I mean, even junior web devs get paid stupidly high salaries for doing Responsive Web Design; I ain't gonna work on this for free.

(But I will accept AI-generated patches, or human-generated advice I could paste into the prompt to get a correct solution :P.)

williamcotton
2 replies
19h24m

I hand-wrote perhaps 10-20 lines of this project:

https://github.com/williamcotton/guish

The rest is Claude 3.5 (with a dash of GPT-4o) with a LOT of supervision!

I'd say I'm about 8 hours deep and that this would have taken me at least 30+ hours to get it to the current state of polish.

I used it to make some graphs at work today!

bomewish
1 replies
17h11m

Quite interesting — but how is it fundamentally more productive than being in VS code in R or python? You don’t get any of the benefits of an IDE here. I often find myself doing very similar workflows but default to either VS Code or the shell. Trying to imagine this truly making workflows faster/easier/more efficient, but can’t figure it.

williamcotton
0 replies
17h3m

Maybe it isn’t? I am just experimenting with new UX! Maybe it could be integrated into an editor of… the fuuuturrre!

But seriously, do you have any thoughts or suggestions?

somesortofthing
7 replies
19h16m

I can't think of a single recent technology that was so widely adopted by tech and non-tech people alike, immediately integrated into day-to-day experience.

I've heard this asserted sometimes, and I just don't think it's true. ChatGPT's use cases as consumer software were discovered basically immediately after GPT 3 came out, and nothing new has really emerged since then. It's great for automating high school/undergrad B-quality writing and the occasional administrative email. Beyond that, it sometimes does better than 2024 Google(though probably still worse than 2019 Google) on knowledge questions.

ChatGPT is software. The barrier to entry is almost zero, and the tech industry has had decades of practice in enticing people into walled gardens and making sure they can never leave. If it's not completely taken over the world in the time it's had, I wouldn't bet on it doing so without a massive jump in capability or accuracy.

myworkinisgood
6 replies
19h5m

Scientific computing is going to be overhauled with this. We have essentially standardized a way to approximately solve optimization problems. And people are now going to design methods to fit this kind of solution, just like people did with linear solvers.

Not to mention all the proof-writing that will become simpler with this optimization/searcher now.

somesortofthing
4 replies
18h53m

Sure, AI represents a substantial improvement over other heuristic methods in some areas. But that's a long way down from the "AI is going to be a permanent fixture in most people's day to day lives" claim that the tech industry is betting the farm on right now.

reaperman
3 replies
17h55m

I think you’re missing that “every” K-12 student is using ChatGPT for all their work right now. Yes, the state of education is in peril (with ChatGPT actually being pretty far down the pareto chart), but the generation coming up after us is absolutely growing up using LLMs the way we used calculators, and using it for everything.

We may not see universal adoption in people who are currently >30 but I think we will in the generations that are <25 now.

somesortofthing
1 replies
14h54m

But are they using it for anything else? Even GPT-2 was "good enough" for high school writing assignments. The fact that this power user class of young people hasn't found any other use cases for LLMs despite vast improvements in LLM capability doesn't reflect well on the merits of LLMs as consumer software.

TeMPOraL
0 replies
10h48m

The fact that this power user class of young people hasn't found any other use cases for LLMs

Why are you assuming they haven't? High school writing assignments and homework are the majority of the problems teenagers face daily, but they're also having fun with it, and why wouldn't they try it on new problems as they come along?

threeseed
0 replies
15h18m

Of course students are using ChatGPT. It helps them to write assignments.

But it isn't translating into better across the board test results and at least in Australia we would be able to tell because we have yearly standardised testing.

And so schools are looking at it as more of a form of cheating and simply moving back to in-person, hand-written tests.

pas
0 replies
18h54m

with what? how? there's already a lot of bad python/R code out there, how more of it will "overhaul" scientific computing?

We have essentially standardized a way to approximately solve optimization problems.

.. what does this mean? we had simplex solvers before. do you mean things like protein folding prediction?

saulpw
5 replies
21h8m

I canceled my GPT-4 subscription recently because it just wasn't that impactful for me. I found myself using it less and less, especially for things that matter (because I can't trust the results). The things it's good at: boilerplate text, lightweight trivia, some remixing/brainstorming. Oh and "write me a clone". Yes, it can write clones of things, because it's already seen them. I've spent WAY more time trying to get anything useful out of it for a non-clone project, than it took me when I just buckled down and did it.

Yes, "many things are clones", but that just speaks to how uncreative we are all being. A 2048 clone, seriously? It was a mildly interesting game for about 3 minutes in 2014, and it only took the original author a weekend to build in the first place. Like how was that impactful that you were able to make another one yourself for $4?

TeMPOraL
4 replies
20h52m

Like how was that impactful that you were able to make another one yourself for $4?

It's been my "concentration ritual", an equivalent of doodling, for a few years in 2010s, so I have a soft spot for it. Tried getting back to it the other day, all my usual web and Android versions went through full enshittification. So that $4 and couple hours bought me a 2048 version that's lightweight, works on my phone, and doesn't surveil or monetize me. Scratched my own itch.

Of course, that's on top of gaining a lot of experience using aider-chat, by setting myself a goal of making a small, feature-complete app in a language I'm only moderately good at (and environment - the modern web - which I both hate and suck at), with extra constraint of not being allowed to write even a single line of code myself. I.e. a thing too boring for me to do, but easy enough to evaluate.

And no, the clone aspect wasn't really that important in this project. I could've asked it for something unique, and I expect it to work more-less the same way. In fact, this is what I'm trying right now, as I just added persistent state to the 2048 game (to work around Firefox Mobile aggressively unloading tabs you're not looking at, incidentally making PWAs mostly unusable) and I have my perfect distraction completely done.

EDIT:

BTW. did I ever tell you about the best voice assistant ever made, which is Home Assistant's voice assistant integrated with GPT-4o? I have a near-Star Trek experience at my home right now, being able to operate climate control and creature comforts by talking completely casually to my watch.

raspasov
3 replies
20h2m

(Also a Chat GPT4o,x etc user)

Try asking it something actually technologically hard or novel and see what answers you get.

In my experience, it repeatedly bails out with "this is hard and requires a lot of careful planning" regardless of how much I try to "convince" the model to live the life of a distributed systems engineering expert. Sure, it spits out some sample/toy code... that often doesn't/compile or has obvious flaws in it.

reaperman
2 replies
17h38m

Very few people are working on technologically hard or novel things. Those people have always had very special effects on society, and will continue to be special going forward - LLM's aren't going to prevent those people from delivering real value. HN has an absurdly rich concentration of these special people, which is why I like it. And many of them are surrounded by other similarly special people in real life. I only regularly talk with maybe 1-2 people in real life who are even close to that type of special. Even when I was a chemical/electrical/petroleum engineer working closely with other engineers - usually only 1-2 people at each workplace were doing really smart work.

That said, the majority of my friends are doing relatively manual work (technician, restaurants, event gigs, sex work) and are neither threatened by LLMs nor find much use for them.

raspasov
1 replies
10h4m

You are likely not wrong.

Even though I do think that almost any profession can potentially find use for LLMs in some shape or form. My opinion is LLMs can increase productivity and be a net positive the way the Internet/search engines are if used correctly.

To expand on my original comment: All that being said, I think the hype/media cycle overestimates the magnitude of the potential positive LLM effect. You’ll see numbers like 5x, 10x, 100x increase in productivity thrown around. If I have to bet, I would say the likely increase is going to be in the 1x-1.5x range but not much greater.

Most things in the world are not infinitely exponential, even if they initially seem to be.

(Not sure why the downvotes.)

reaperman
0 replies
8h46m

(Not sure why the downvotes.)

Appreciated! But if we fret about a few downvotes, we're using the forum wrong. Some unpopular views need to be discussed - either because they hold some valuable truth that people are ignorant of, or because discussing them can shine a light on why the unpopular views are misguided. I suspect the downvotes are related to "Very few people are working on technologically hard or novel things" -- many HN users have been surrounded since elementary school by tons of people who do currently work on hard or novel problems, so they understandably think that >5-10% of people do that, when in fact it's closer to maybe 1-in-200. I've been part of social groups who went to high schools with absurd numbers of Rhodes' Scholars and peer groups where everyone in the group can trivially get through medical schools with top marks, receive faculty positions as professors at top-3 universities, found incredible startups through insane technical competence, and still all think they're stupid because they compare themselves to the true 1-in-a-million geniuses they grew up with who are doing research so advanced that it's far beyond their most remote chances of ever having even surface-level comprehension of that research. Their extended social group likely comprises >1% of all Americans working on "hard or novel problems", but since 75% of them are doing it, they have no idea that the real base rate is closer to 1-in-200, generously. They grossly underestimate their relative intelligence vs. the median and grossly overestimate the ability of average people (and explain away differences in outcome to personality issues like "laziness").

There are a surprising number of people from these peer groups on HN. These are the people who will never be threatened by LLM's -- they are capable of adapting to use any new tools and transcending any future paradigm, save war/disease/famine.

To expand on my original comment: All that being said, I think the hype/media cycle overestimates the magnitude of the potential positive LLM effect. You’ll see numbers like 5x, 10x, 100x increase in productivity thrown around. If I have to bet, I would say the likely increase is going to be in the 1x-1.5x range but not much greater. Most things in the world are not infinitely exponential, even if they initially seem to be.

Yours is a very reasonable take that I wouldn't argue against. I also think it's reasonable that some people think it will be 5x-100x -- for the work some individuals are familiar with it very well might be already, or they might be more bullish on future advances in reinforcement learning / goal-seeking / "search" (iterative re-search to yield deep solutions).

Even though I do think that almost any profession can potentially find use for LLMs in some shape or form.

I reactively feel this is stretching it for people who travel around just to load/unload boxes of equipment at events/concerts/etc. But the way you worded this is definitely not wrong - even manual laborers may find LLM's useful for determining whether they, their peers, and their bosses are following proper safety/health/HR regulations. More obviously, Sex workers will absolutely be using LLM's to screen potential customers for best mutual-fit and maintain engagement (as with lawyers who own small practices, a large number of non-billable hours goes towards client acquisition, as well as retention). LLM's are not "there" yet for transparent personalized client engagement which maintains the personality of the provider, but likely will be soon with some clever UX and RAG.

maxlamb
5 replies
21h26m

What’s a 2048 clone?

woodruffw
3 replies
20h19m

This version seems to be using slightly different rules: my recollection is that the original 2048 prevented a move if it wouldn't cause any blocks to shift or collapse, while this one spawns a block unconditionally.

TeMPOraL
2 replies
20h12m

It doesn't anymore.

You're right. I pasted your comment to aider and it fixed it on the spot :).

EDIT: see https://git.sr.ht/~temporal/aider-2048/commit/9e24c20fc7145c....

A bit lazy approach, but also quite obvious. Pretty much what you'd get from a junior dev.

(Also if you're wondering about "// end of function ..." comments, I asked the AI to add those at some point, to serve as anchors, as the diffs generated by GPT-4o started becoming ambiguous and would add code in wrong places.)

woodruffw
1 replies
19h45m

I think it's also not progressing the block size with score: IIRC the original came also begins spawning 8s and 16s once you get above your first 512 block. But I could be misremembering.

(This kind of feedback driven generation is one of the things I do find very impressive about LLMs. But it's currently more or less the only thing.)

TeMPOraL
0 replies
19h38m

I don't remember it doing progressive block sizing - I only vaguely remember being mildly annoyed by getting to 2048 taking >2x the effort it took to get to 1024, which itself took >2x the effort of getting to 512, etc. - a frustration which my version accurately replicates :).

meiraleal
3 replies
20h55m

I've just had GPT-4o write me a full-featured 2048 clone in ~6 hours of casual chat

Honestly I'm totally in the AI camp but 6 hours to make a 2048 clone?! And that's a good result? Come on.

reaperman
0 replies
17h35m

The vast majority of devs would take much longer than 6 hours if this task were assigned to them. Yes, the vast majority of devs might suck, but its actually a shockingly low percentage who are genuinely skilled. You are probably surrounded by rare skilled devs.

fragmede
0 replies
20h39m

you come on. it's not six hours of focused work, it sounds like six hours while watching Netflix and puttering around.

TeMPOraL
0 replies
20h42m

Of casual chatting in between making dinner, doing chores, playing with kids, and work. The actual time spent strictly on this was more like 2 hours. And that's with me writing zero lines of code, and using the technology stack (modern web) I hate and suck at (but I'm proficient enough to read the basics).

Also, to be honest, it would've been much faster if GPT-4o didn't occasionally get confused by the braces, forcing me to figure out ways to coerce it into adding code in the right place. This is to say, there's still plenty of low-hanging fruits for improvement here.

grumbel
3 replies
19h55m

Just because it's impactful doesn't mean it's going to make much money. Take audiobooks for example, the market is valued at around $5 billion. In the very near future audiobooks will be created with AI. Does that mean anybody is making billions with those AI audiobooks? I don't think so. The value of audiobook will go towards $0 and audiobooks as a product category will completely disappear. Audiobooks will simply be the text2speech feature of your eBook reader.

Similar stuff will happen with a lot of other content, things that used to be costly will become very cheap. And then what? The amount of books people can consume doesn't scale into infinity. Their entertainment needs will be served by auto-generated AI content. Even the books themselves will be written by AI sooner or later.

Advertising industry might also start hurting badly, as while they will certainly try getting ads into AI content, users will have AI at home to filter it out. A lot of classic tricks and dark pattern to manipulate the user behavior will no longer work, since the user has a little AI helper to protect them from those tricks.

I don't doubt that the impact of AI will be gigantic, but a lot of AI produced content won't be worth anything, since it's so easy to create for everybody. And there isn't much of a moat either, since new models with better capabilities pop up all the time from different companies. Classic lock-in is also not really usable anymore, as AI can effortlessly translate between different APIs and user-interfaces.

vasco
1 replies
19h50m

Why would I watch someone else's AI content when I can watch my own with about the same work? It probably takes longer to pick something on Netflix than to shout at my TV to show me some auto-generated on the fly show about whatever I'm feeling like watching right now. Can even be building upon itself "show me yesterday's show but in space and give it some new twists that I don't expect".

mejutoco
0 replies
19h17m

You can share opinions about a common show the next day with another person and bond over it. For example, about a football match.

throwaway2037
0 replies
11h45m

While I agree that most audiobooks will be priced near zero, there will still be a healthy market for highly paid actors to read, like Morgan Freeman. That said, it will be a tiny segment in the market, and many famous people will need to fight/sue AI providers to remove impersonations. I expect those markets will be flooded by fan-created favourites that read like Morgan Freeman.

epolanski
3 replies
19h45m

Meanwhile I have the opposite experience.

I have used chatgpt less and less, and bar copilot which is a useful autocomplete I just don't have much use for AI.

I know I'm not alone, and even though I've seen many people super excited by Dall-E first and chatgpt later they use very rarely both of them.

cageface
2 replies
15h42m

This is where I am with it now. I got bored with the image generators and tired of their plastic looking output.

I still use GPT or Claude occasionally but I find switching over to prompting breaks my mental flow so it’s only a net win for certain kinds of tasks and even there it’s not a huge step up from searching Stack Overflow.

namaria
1 replies
9h36m

For me it's been great for things like generating a latex version of my cv, or CSS for a web app. It's worth an OpenAI subscription for me, but I do wonder if it's worth all the energy and resources gone into making those GPU clusters and powering them.

TeMPOraL
0 replies
46m

The huge up-front energy costs of GPU clusters, both of making and operating them, is amortized over all subsequent uses of the models, i.e. inference. Inference itself is cheap per query. Your use cases aren't consuming that much energy. I feel the amount is in the same ballpark as what you'd use doing those things yourself.

As for whether it's worth it, I argue this is the single most useful application of GPUs right now, both economically and in terms of non-monetary value delivered to users.

(And training them is, IMO, by far the most valuable and interesting part of almost all creative works available online, but that's another discussion.)

woodruffw
2 replies
20h9m

I don't think the uptake of LLMs by non-technical people has been that dramatic. Nobody in my familial or social circles (which spans doctors, lawyers, artists, waitresses, etc.) has really mentioned them outside of asking my what I think about them.

As for what I think about them: I've been impressed with some aspects of code generation, but nothing else has really "wowed" me. Prose written with the various GPT models has an insincere quality that's impossible to overlook; AI-generated art tends to look glossy and overproduced in the same way that makes CGI-heavy movies hard to watch. I have not found that my Google Search experience was made better by their AI experiments; it made it harder, not easier, for me to find things.

falcor84
1 replies
19h50m

... makes CGI-heavy movies hard to watch

While I absolutely agree that many movies over-use CGI, even with the relative decline in superhero movies, CGI-heavy movies still top the box office. Going over the list of highest-grossing movies each year [0], you have to go back about three decades to find a movie that isn't CGI-heavy, so apparently they're not that difficult for the general public to watch.

[0] https://en.wikipedia.org/wiki/List_of_highest-grossing_films

woodruffw
0 replies
19h41m

True. It's also a rude reality that much of the US uses word art and comic sans to advertise things, so I might just be a snob. Then again, impressing the snobs is a relevant part of the mass adoption curve :-)

pavel_lishin
2 replies
20h1m

I've just had GPT-4o write me a full-featured 2048 clone in ~6 hours of casual chat

May we see it?

TeMPOraL
1 replies
19h59m

http://jacek.zlydach.pl/v/2048/

https://git.sr.ht/~temporal/aider-2048

There's a full transcript of the interactions with Aider in that repo (which I started doing manually before realizing Aider saves one of its own...).

Before anyone judges quality of the code - in my defense, I literally wrote 0 lines of it :).

pavel_lishin
0 replies
19h54m

That works surprisingly well! I mean that I am genuinely surprised.

nl
2 replies
16h20m

I agree with this take.

The perspective I take is the 15 year view: The iPhone 1 sucked objectively but by the iPhone 3 the trajectory was clear and 15 years later the world is a very different place.

You hear people very focused on specific shortfalls: "I asked it to write code and look it made a mistake". But there are very clear routes to fixing these and there are lots of people finding it useful despite these bugs.

I think AI is bigger than mobile. I'm nearly 50, and I remember the PC boom, the Internet boom, Social Networking boom, Mobile boom, SaaS boom - probably more that I forget.

I think the PC and Internet booms are the only ones that are as impactful as AI will be in 15 years.

Maybe mobile is as big, maybe not - depends if someone can build AI devices that replace the UX of phones sometime in the next 15 years.

freediver
1 replies
2h59m

Interesting takeaway if this holds true - following the analogy, people will be excited about GPT-16 as much as they are excited about iPhone 16 today, compared to the excitement about first few generations of iPhone. That may mean that LLMs may become so ubiquitous that we won't even notice. Which means there will be no AGI.

TeMPOraL
0 replies
44m

If GPT-16 is pretty much GPT-4 but a bit faster and a bit smarter, then sure. If subsequent generations of GPT continue the trend of qualitatively improving on the predecessors, then we'll likely hit AGI somewhere around GPT-10 at the latest.

madeofpalk
2 replies
20h17m

I think it’s reasonably obvious that the tech could have a lot of potential, but that’s yet to be realised. Chatbot interfaces are so primitive and clearly not the final form for LLMs, but people have to invent that.

But, tech being impactful doesn’t mean it will create and deliver value for others.

falcor84
1 replies
19h47m

Can you come up with an example of tech that was impactful without delivering value to others?

The closest I can think of would be the atom bomb, but even that arguably brought significant value in terms of relative geopolitical stability.

madeofpalk
0 replies
7h45m

Sorry, I phrased it poorly.

Very often technology advancements redistribute value, taking it away from many people and allowing companies to capture more profit and/or lower costs. Such as self-serve checkouts at supermarkets leading to less cashier jobs.

A huge amount of economic value is going to be created by AI. Company builders focused on delivering value to end users will be rewarded handsomely.

Companies will acrue value, but 'common folk' will lose it.

bamboozled
2 replies
19h52m

I've just had GPT-4o write me a full-featured 2048 clone in ~6 hours of casual chat, in between of work, making dinner, and playing with kids;

As cool as this might be, what is the actual economic value of this? 2048 is free, you didn't even have to spend a dollar to get it.

TeMPOraL
1 replies
19h40m

I don't give a damn about economic value of the game - I just wanted to have a 2048 that's lean and not powering the adtech economy. At the same time, I care about both economic and non-monetary value of me leveraging AI tools in creating software, so this game was a perfect little project to evaluate aider-chat as a tool.

bamboozled
0 replies
19h7m

The questions stands though: Is building all this infra so you (random internet guy) can generate a 2048 clone worth the increased emissions and the $600B of investment?

shermanyo
1 replies
17h18m

I've just had GPT-4o write me a full-featured 2048 clone in ~6 hours of casual chat, in between of work, making dinner, and playing with kids; it cost me some $4 in OpenAI bills, and I didn't write a single line of code.

This kind of example always confuses me. I don't see the value vs reading an article like this: https://www.freecodecamp.org/news/how-to-make-2048-game-in-r...

If I said I built a 2048 clone by following this tutorial, noone would be impressed. I just don't see how reading a similar tutorial via a chat interface is some groundbreaking advancement.

ern
0 replies
15h59m

The difference is that with a chat interface you can ask it questions, you can brainstorm with it, you can drill down into specific concepts and you can do it any language/framework, without waiting for a tutorial to be written for it. And it would help you do the "homework" at the end.

For the tutorial you linked to, there's a lot of prior knowledge assumed, which the author alludes to in the summary, which a chat interface would help with:

This time I decided to focus on the essence of the topic rather than building basic React and CSS, so I skipped those basic parts. I believe it makes this article easier to digest.

ClimaxGravely
1 replies
17h41m

can you show the 2048 clone?

EDIT : My bad, I see you posted the link elsewhere (link for posterity http://jacek.zlydach.pl/v/2048/ )

TBH 6 hours seems a lot longer than I would have expected.

TeMPOraL
0 replies
10h39m

6 hours of on-and-off casual chatting while working, making dinner, playing with kids, etc. Total time spent in front of keyboard was at most half of that. And would be half of that still, if I had more experience guiding GPT-4o/Aider diffs out of stupid ruts - experience which I gained through this short project.

Also: 6 hours is a lot if you sit down to it and know exactly what to write. Not when you half-remember how the game works, don't have uninterrupted focus time for it, and deal with executive function issues to boot.

woopsn
0 replies
14h40m

Keep in mind, the "hole" takes ChatGPT and Copilot/Gemini/etc into account at a rate of $5-10B per product. The remainder of $500B is about the size of the global cell phone market. Where will it come from?

roenxi
0 replies
19h24m

And we seem to be in an exponential upswing of hardware capacity, so we expect extreme improvements from an already impressive base. >90% of the compute that can be used to train models doesn't exist yet.

prng2021
0 replies
18h39m

The article explains a $600B gap in AI revenue expectations vs actuals. Rather than addressing that, you're posting about some dietician you know who worries their job will get replaced, as if it has any relevance whatsoever to the big picture.

We should have seen massive revenue growth and raises in future quarter revenue forecasts in the most recent round of SaaS company earnings reports. I think tons of companies have hyped up AI as if it's just on the cusp of AGI. The lack of massive top line growth has proven we're not even close, but the enormous investor speculation these companies triggered is the main reason for this $600B gap.

I'm not at all saying AI won't be transformational because it definitely does bring revolutionary capabilities that weren't possible before.

mvdtnz
0 replies
18h58m

I see non-tech people around me using ChatGPT for anything from comparison shopping to recipe adjustments.

This is baffling to me, because these are two use cases I have tried and in which ChatGPT completely fails to produce any useful information.

lend000
0 replies
20h22m

GPT-4 is an upgrade over a search engine (on the 2010 internet, which was much easier to search than the internet today) and there is certainly opportunity in using it to chain together complex programming tasks fully programmatically, but we are stuck right on the cliff of a truly reliable and generalizable AI, and it isn't clear that we can just train an AI with the next generation of GPU's and more data and bridge that gap. Most of the truly high value add activities (fully autonomous programs and AGI that creates novel inventions) rely on a model more intelligent and more consistent than the current state of the art. So I think most of the valuation is in speculative potential.

kortilla
0 replies
18h53m

No offense, but you’re group is just very early on the adoption curve and is not representative of at all.

I have a bunch of peers that haven’t used chatgpt at all and they are software developers. A bunch more tried it once, realized how terrible it was for anything you aren’t already knowledgeable in and then haven’t gone back to it.

Recipe adjustments has to be a joke unless they are really basic things like “cut it in half”. ChatGPT is terrible at changing recipes without fundamentally changing them and will offer multiple “substitutions” for an ingredient that have extremely different outcomes that it doesn’t warn or know about.

jmartin2683
0 replies
19h14m

This is the type of thing that I’ve only ever read about on the internet and have never heard of a normal person actually doing.

dimgl
0 replies
18h15m

I actually don't think it's going to be that impactful. It often gets everything wrong. Today I asked ChatGPT questions about a game I used to play. It got it all wrong. I've recently asked questions about coding. A majority of it is also wrong. I've tried using it in a professional setting and it's also hit or miss.

I'm not saying AI is useless but it's certainly not the panacea that some say it is.

chillfox
0 replies
18h4m

I think that comes down to the kind of people you hang out with.

While I use AI quite often, none of my friends or family does. A few of them will use an image gen once or twice a year. And at work, only a few of my colleagues use AI.

So my impression is that current gen AI is too hard to use correctly, has too many rough edges and is not useful enough for most people.

Progress also seems to have stalled around the GPT-4 quality. Everything after GPT-4 (GPT-4 Turbo, GPT-4o, Claude 3 Opus, Claude 3.5 Sonnet) seems to be pretty much producing the same quality output, I have been using Open WebUI to bounce around between the different models and I can't really tell a difference in the quality of them, they are all roughly the same for my use case (programming/sysadmin stuff).

So the question of if a plateau has been hit or if scale can still improve quality is real to me.

aleph_minus_one
0 replies
2h3m

I can't think of a single recent technology that was so widely adopted by tech and non-tech people alike, immediately integrated into day-to-day experience.

Which technology are you talking about? ;-)

What I can clearly say is that I know no one from my social circles and extended social circles who used these AI chatbots for anything else than "simply trying out what is possible" (and ridiculing the results). A quote from a work colleague of me when I analyzed the output of some latest generation AI chatbot: "You shouldn't ask so complicated questions to the AI chat bots [with a huge smile on his face]. :-)"

PaulHoule
0 replies
21h4m

One difference between AI and mobile is this.

The mobile revolution needs three kinds of investment:

(A) The carrier has to build out a network

(B) You need to buy a handset

(C) Businesses need to invest in a mobile app.

The returns that anybody gets from investing in A, B or C depend on the investments that other people have made. For instance, why should I buy a handset if the network and the apps aren't there? Why should a business develop an app if the network and users aren't there? These concerns suppress the growth of mobile phones in the early phase.

ChatCPT depends on the existing network and existing clients for delivery so ChatGPT can make 100% of the investment required to bring their product to market which means they can avoid the two decades of waiting for the network and handsets to be there in order to motivate (C).

---

Note another thing that younger people might never have noticed was that the US was far behind the rest of the world in mobile adoption from maybe 1990 to 2005. When I changed apartments in the US in the 1990s I could get landline service turned on almost immediately by picking up the phone. When I was in Germany later I had no idea I could go into a store in most countries other than the US and walk out with a "handy" and be talking right away so I ended up waiting a month for DT to hook up my phone line.

stale2002
24 replies
21h46m

Such strong speculative predictions about the future, with no evidence. How can anyone be so certain about this?

The evidence is all around you. For anyone who has made any serious attempt to add AI to your current life and work process, you will fairly quickly notice that your productivity has doubled.

Now, do I as a random software engineer who is now producing higher quality code, twice as fast, know how to personally capture that value with a company? No. But the value is out there, for someone to capture.

It's like everyone is in the same trance and simply assuming and repeating over and over that This Will Change Everything

It already is changing everything, in multiple fields. Go look up what happened to the online art commission market. It got obliterated over a year ago and is replaced by people getting images from midjourney/ect.

Furthermore, if you are a software engineer and you haven't included tools like github copilot, or cursor AI into your workflow yet, I simply don't consider you to be a serious engineer anymore. You've fallen behind.

And these facts are almost immediately obvious to anyone who has been paying attention in the startup space, at least.

choeger
13 replies
21h40m

Furthermore, if you are a software engineer and you haven't included tools like github copilot, or cursor AI into your workflow yet, I simply don't consider you to be a serious engineer anymore. You've fallen behind.

That sounds like you're fresh out of college. Copilot is great at scaffolding but doesn't do shit for bug fixing, design, or maintenance. How much scaffolding do you think a senior engineer does per week?

delichon
7 replies
21h25m

40+ years of coding here. I've been using LLMs all day and getting a large boost from it. That last thing I did was figure out how to change our web server to have more worker processes. It took a half dozen questions to cure a lot of ignorance and drill down the right answer. It would have taken a lot longer with just a search engine. If you're not seeing the large economic advantage of these systems you're not using them like I am.

ern
3 replies
16h24m

I think that one of the reasons there's a surprising amount of pushback because a lot of developers don't like the sort of collaborative, unstructured workflow that chat-oriented tools push onto you.

I once worked with someone who was brilliant, but fell apart when we tried to do pair-programming (acturial major who had moved into coding). The verbal communication overhead was too much for him.

ryandrake
1 replies
15h21m

This is a really interesting observation that makes a lot of sense to me. I can relate to this and it really helps to explain my own skepticism about LLMs "helping" with programming tasks.

I've always thought of software development as an inherently solo endeavor that happens entirely inside of one's own mind. When I'm faced with a software problem, I map out the data structures, data flows, algorithms and so on in my mind, and connect them together up there. Maybe taking some notes on a sheet of paper for very complex interactions. But I would not really think of sitting down with someone to "chat" about it. The act of articulating a question "What should this data structure look like and be composed of?" would take longer than it would take to simply build it and reason about it in my own brain. This idea that software is something we do in a group socially, with one or more people talking back and forth, is just not the way I operate.

Sure, when your software calls some other person's API, or when your system talks to someone else's system, or in general you are working on a team to build a large system, then you need to write documents and collaborate with them, and have this back-and-forth, but that's always kind of felt like a special case of programming to me.

The idea of asking ChatGPT to "write a method that performs a CRC32 on a block of data" seems silly to me, because it's just not how I would do it. I know how to write a CRC function, so I would just write it. The idea of asking ChatGPT to help write a program that shuffles a deck of cards and deals out hands of Poker is equally silly because before I even finished writing this sentence, I'm visualizing the proper data structures that will be used to represent the cards, the deck, and players' hands. I don't need someone (human or AI) to bounce ideas off of.

There's probably room for AI assistance for very, very junior programmers, who have not yet built up the capability of internally visualizing large systems. But for senior developers with more experience and capability, I'd expect the utility go down because we have already built out that skill.

ern
0 replies
15h15m

I consider myself to be fairly senior, and use it all the time for learning new things. I work with some brilliant senior developers who lean on it heavily, but I do think it doesn't mesh with the cognitive styles of many.

TeMPOraL
0 replies
9h46m

There might be something to this; however, N=1, I'm very much the kind of developer who hates pair-programming and falls apart when forced to do it. But it's not the conversation that's the problem - it's other people. Or specifically, my fight-and-flight response that triggers when I am watched and have to keep up with someone (and extreme boredom if the other person can't keep up with me). LLMs aren't people, and they aren't judging me, so they do not trigger this response.

Chat interface is annoying, though. Because it's natural language, I have to type a lot more, which is frustrating - but on the other hand, because it's natural language, I can just type my stream of thought and the LLM understands it. The two aspects cancel out each other, so in terms of efficiently, it's a wash.

skydhash
2 replies
20h1m

If you're not seeing the large economic advantage of these systems you're not using them like I am

I just read the manual.

fragmede
1 replies
19h56m

do you flip to the back of the book to the index to find the pages that references a topic, or do you use ctrl-f?

skydhash
0 replies
19h25m

I also use the table of contents.

stale2002
1 replies
21h28m

Nope. 10 years experience working at startups and FAANG.

And yes cursor AI/copilot helps with bugs as well.

It works because when you have a bug/error message, instead of spending a bunch of time on Google/searching on stack overflow for the exact right answer, you can now do this:

"Hey AI. Here is my error message and stack trace. What part of the code could be causing it, and how should I fix it".

Even for debugging this is a massive speed up.

You can also ask the AI to just evaluate your code. Or explain it when you are trying to understand a new code base. Or lint it or format it. Or you can ask how it can be simplified or refactored or improved.

And every hour that you save not having to track down crazy bugs that might just be immediately solvable, is an hour that you can spend doing something else.

And that is without even getting into agents. I haven't figured out yet how to effectively use those yet, and even that is making me nervous/worried that I am missing some huge possible gains.

But sure, I'll agree that of all you are doing is making scaffolding, that is a fairly simply usecase.

choeger
0 replies
10h54m

It works because when you have a bug/error message, instead of spending a bunch of time on Google/searching on stack overflow for the exact right answer, you can now do this:

That's not how I work since I stopped being a junior dev. I might google an error message/library combination if I don't understand it but in most cases, I just read the stacktrace and the docs, or maybe the code.

I don't doubt that LLMS can be quite useful when working with large, especially foreign, codebases. But I have yet to see the level of "if you don't use it you're not an engineer" some people like to throw around. To the contrary, I'd argue if you rely on an LLM to tell you what you should be doing, you aren't an engineer, you are a drone.

volkk
0 replies
21h37m

depends on what you're working on. i'm a senior engineer currently doing a lot of scaffolding for startups and my copilot saves me a ton of time. life's good.

mdale
0 replies
21h31m

It's getting better and new UIs for it are being tested like Claude and artifacts.

Sr. Eng adopted copilot and sung it's praises a lot faster then the jr engineers. Especially when working on codebases with less familiar languages.

ilaksh
0 replies
21h30m

I started teaching myself programming 40 years ago and I believe that Copilot and other AI programming tools are now an essential part of programming. I have my own agent framework which I am using to help complete some tasks automatically.

Maybe take a look at tools like aider-chat with Claude 3.5 Sonnet. Or just have a discussion with gpt-4o about any programming area that you aren't particularly familiar with already.

Unless you literally decided you learned everything you need and don't try to solve new types of problems or use new (to you) platforms ever..

GenerocUsername
4 replies
21h42m

Ive added "how have you incorperated generative AI into your workflow" as an interview question, and I dont know if it is stigma or actual low adoption, but I have not had a single enthusiastic response across 10+ interviews for senior engineer positions.

Meanwhile, I have chatGPT open in background and go from unaware to informed for every new keyword I hear around me all day everyday. Not to mention annotating code, generating utlity functions, and tracing errors

bagels
1 replies
18h7m

What, in your mind, is the right answer to that question?

GenerocUsername
0 replies
15h41m

Good question.

The best answer is for someone who has found ways to boost their own productivity, but also understands the caveats such as hallucinations and not pasting proprietary information into text boxes on the internet.

ilaksh
0 replies
21h22m

Would you consider hiring on a contract basis? I use AI tools like Copilot in vim, and have my own agent framework to ask questions or even edit files for me directly, which I have been trying to use more. And I could use a new contract. You can see my email in my HN profile.

devjab
0 replies
20h23m

I think if sort of depends on the work you do. If you’re working on a single language and have been for a while then I imagine that much of the value LLMs might give you already live in your existing automation workflows.

I personally like co-pilot but I work across several languages and code bases where I seriously can’t remember how to do basic stuff. In those cases the automatic code generation from co-pilot speeds my efficiency, but it still can’t do anything actually useful aside from making me more productive.

I fully expect the tools to become “necessary” in making sure things like JSdoc and other domination is auto-updated when programmers alter something. Hell, if they become good enough at maintaining tests that would be amazing. So far there hasn’t been much improvement over the year we’ve used the tools though. Productivity isn’t even up across teams because too many developers put too much trust into what the LLMs tell them, which means we have far more cleanup to do than we did in the previous couple of years. I think we will handle this thing once we get our change management good enough at teaching people that LLMs aren’t necessarily more trustworthy than SO answers.

beambot
2 replies
21h35m

Very true! From where I sit, most of the hype cycles were overestimated in the short term & underestimated in the long term: world wide web, mobile, big data, autonomous cars, AI, quantum, biotech, fintech, clean tech, space and even crypto.

c-cube
1 replies
18h11m

It's a bit weird to claim that "quantum", autonomous cars, and crypto are "underestimated". If anything they've been overhyped and totally failed to deliver actual value.

beambot
0 replies
13h51m

Underestimated in the long term. It's become clear that the time constant for deep-tech innovation & adoption doesn't match the classic VC-backed SaaS adoption curve.

We're nearing general quantum supremacy for practical jobs within the next 5 years. Autonomous cars are now rolling out in select geographies without safety drivers. And crypto is literally being pushed as an alternative for SWIFT among the BRICS, IMF, and BIS as a multi-national CBDC via the mBridge program.

rty32
0 replies
21h30m

Twice as fast is way over exaggerating the reality. In certain cases, sure, but more generally you are looking at 10%-50% productivity increase, more likely on the lower end. I say this as someone who has access to ChatGPT and AI code completion tools and use them every day, and the numbers are backed up by Google's study. https://research.google/blog/ai-in-software-engineering-at-g...

americanvirtual
0 replies
21h13m

Yeah some expert I work in the field type YouTubers I remember well over 7 months ago now kept saying that we're going to have AGI within 7 months. He was like the big prediction hinging practically his whole channel on... Sorry I don't have the name but there's a little anecdote.

glitchc
20 replies
21h53m

Whenever I hear the AI hype cycle, I'm always reminded of expert systems and how they were going to revolutionize the world.

llm_trw
11 replies
21h43m

You should also be reminded about the internet. After the dotcom bubble it was extremely common to hear it outright dismissed as never being useful for anything.

Sometimes the future just gets here before we're ready for it.

glitchc
9 replies
21h37m

Repeat after me: An LLM is not AI. The internet enabled a whole new world of possible applications. It's unlikely this or even the next upgrade to ML will get there. If we get to AGI, sure, that's grpund-breaking, but we're still a few steps removed from that.

TeMPOraL
4 replies
21h35m

Repeat after me: "AI hype" is not like Bitcoin hype, it's like Dot-com boom.

Generative models are already changing how people live and work. Ignore the grifters, and ignore the entrepreneurs. Look at civilians, regular folks, and watch how it impacts them.

glitchc
1 replies
20h54m

Oh the belief is so strong! Wouldn't it be great if this were true.

TeMPOraL
0 replies
20h43m

It's not hard to have strong beliefs about something that's real.

pphysch
0 replies
19h6m

To be fair to Bitcoin, the world's largest economic bloc is actively building an alternative to USD/Western banks for international settlements, with blockchain technology.

It doesn't have anything to do with the libertarian vision of BTC but it's the same technical concept.

SoftTalker
0 replies
15h30m

I see you saying this all over this topic and yet I don't know anyone who uses AI for anything real. I've never used it once for anything, and I work in tech. The only people I know who use AI are kids who use it to do their homework for them. I'm sure they love it, but it's hardly a good thing.

It's like hiring someone to go to the gym for you, as far as I can see.

llm_trw
2 replies
21h29m

Repeat after me: An LLM is not AI.

They are more intelligent than the average person I deal with on a daily basis.

The one thing us meat bags have going for us is that we have bodies and can do things.

sfink
0 replies
17h41m

They are more intelligent than the average person I deal with on a daily basis.

No they aren't. They are differently intelligent. Which includes being more "intelligent" in some ways, and vastly less in others.

It is an all too common mistake to infer an LLM's capability based on what it would mean if a human could produce the same output. But it's not the same thing at all. A human that could produce the quality of many LLM outputs I've seen would be a person with superintelligence (and supercreativity, for that matter). But a human who is constrained to only the output that an LLM is capable of would be an untrustworthy idiot.

What's interesting to me is looking at the human+LLM combos that have recently entered the world. (As in, everyone who is regularly using good quality LLMs.) What are they capable of? Hopefully they'll be at least as intelligent as a regular human, though some of the articles on people blindly accepting LLM hallucinations do make me wonder.

pixl97
0 replies
21h13m

And with the advances in robotics recently, who knows how long we're going to hold on to this monopoly.

apitman
0 replies
21h22m

An LLM is not AI

Good luck with that genie

threeseed
0 replies
18h43m

After the dotcom bubble it was extremely common to hear it outright dismissed as never being useful for anything

eBay, Amazon, Google, Yahoo etc were all around at the time and making serious money.

Not sure who those people were but it was very obvious to most that the internet was here to stay.

awahab92
6 replies
21h44m

there were probably people who doubted electricity, vaccines and indoor plumbing.

ryandrake
2 replies
21h38m

There were also people who doubted the Segway, Magic Leap, Theranos, 3D TVs, Windows Phone, and Google Glass.

I think doubt is OK, at least it is before any particular technology or product has actually proven itself.

fragmede
1 replies
20h6m

the gap between participants in this conversation is that some have had it proven itself for themselves and others around them, and others have not seen that same proof.

rsynnott
0 replies
19h30m

Thing is, that comment would have worked in a thread three years ago about ‘metaverses’. Sometimes, the early adopters are the only adopters. Not saying that’s definitely the case here, but it is looking like it’s going in that direction - huge hype, absurd levels of VC spending, a bunch of ultra-enthusiastic early adopters, but real mainstream application still absent.

glitchc
1 replies
21h38m

This is false equivalence and you know better. Electricity is foundational technology. What we call AI are LLMs, which are great and useful, but not in the same league as something foundational like electricity.

pixl97
0 replies
21h5m

Now, the question of "Are LLMs intelligent" is debatable, but intelligence is foundational itself.

rurp
0 replies
20h15m

The ration of hyped technologies that turned out to be overhyped, versus ones that turned out to be as impactful as electricity is... I don't even know how many orders of magnitude different, but it's a lot.

cjbgkagh
0 replies
21h29m

This really is different, and I say that as someone who spent a lot of time on expert systems, not as someone who is overly bought into AI hype.

The problem with expert systems is that even if the tooling was perfect the people using them needed a rather nuanced and sophisticated understanding of ontologies. That just wasn’t going to happen. There is not enough of that kind of expertise to go around. Efforts to train people largely failed. I think the intentional undermining of developer salaries pushed a lot of smart people out of the software industry making the problem even worse.

That’s what makes AI special, the ability to deliver value even when used by unsophisticated operators. Many workflows can largely stay the same and AI can be sprinkled in where it makes the most sense. I use it for documentation writing and UI asset production and it’s better in that role than the people I used to pay.

simonw
9 replies
21h37m

If, like me, you're using LLMs on a daily basis and getting real personal value out of them, it's hard not to conclude that they're going to have a big impact.

I don't need a crystal ball for this. The impact is already evident for us early-adopters, it's just not evenly distributed yet.

That's not to say they're not OVER hyped - changing the entire company roadmap doesn't feel like a sensible path to me for most companies.

ryandrake
8 replies
21h31m

Early Adopters are always True Believers. That's why they are early adopters. Every single one of them is going to say "The impact is clear! Look around you! I use XYZ every day!" You really don't know what the adoption curve will look like until you get into the Late Majority.

llm_trw
5 replies
21h9m

Early Adopters are always True Believers.

Early adopters were using gpt-2 and telling us it was amazing.

I used it and it was completely shit and put me off openai for a good four years.

gpt-3 was nearly not shit, and 3.5 the same just a bit faster.

It wasn't until gpt-4 came out that I noticed that this AI thing should now be called AI because it was doing things that I didn't think I'd see in decades.

simonw
4 replies
20h32m

I tried GPT-2 and thought it was interesting but not very useful yet.

I started using GPT-3 via the playground UI for things like writing regular expressions. That's when this stuff began to get useful.

I've been using GPT-4 on an almost daily basis since it came out.

llm_trw
3 replies
20h27m

The hype around gpt2 was ridiculous. It made me firmly put openai into 'grifters, idiots and probably both' territory.

Turns out they were just grifters as the hilarious mess around Sam Altmans coup/counter coup/coup showed us.

Fripplebubby
2 replies
19h41m

I don't know what your operating definition of "grifter" is but for me, a grifter is not a company that delivers a product which gains a large adoption and mindshare (ChatGPT) and essentially sets the world on fire. (not an opinion on Altman specifically but OpenAI at large)

llm_trw
1 replies
18h23m

My definition is someone outright lying that gpt-2 was agi that should be regulated just so they could raise more money for the next round of training.

p1esk
0 replies
17h56m

Who said gpt2 was agi?

wruza
0 replies
20h4m

I’m not that much of a believer, but what is clear is that “AI” still has a plug incompatible with your regular wall socket, if you get the analogy. It’s too early to draw a circle around adopters count.

We’ll talk counts when my grandma will be able to hey siri / okay google something like local hospital appointment or search for radish prices around her. It already is possible, just not integrated enough.

Coincidentally, I’m working on a tool at my job (unrelated to AI) that enables computer device automation on much higher level than playwright/etc. These two things combined will do miracles, for models good enough to use it.

TeMPOraL
0 replies
21h26m

We're already entering Late Majority stage. Early Majority is like a good chunk of the western population, which already should tell you something - the "technology adoption model" might not make much sense when the total addressable market is literally everyone on the planet, and the tech spreads itself organically with zero marketing effort.

And/or, it's neither hard nor shameful to be True Believers, if what you believe in is plain fact.

apitman
7 replies
21h32m

IDK. Blockchains have been super hyped. The tech is undeniably cool. But I have yet to see an example of them solving a real problem for anyone who's not a criminal.

In contrast, I've put in very little effort to use AI, but I'm noticing things.

I see high quality AI-generated images in blog posts. They look awesome.

I look over my coworker's shoulder and see vscode predict exactly the CSS properties and values he's looking for.

Another coworker uses AI to generate a working example of FPGA code that compiles and runs on a Xilinx datacenter device.

An AI assistant pops up in Facebook messenger. My girlfriend and I are immediately able to start sending each other high quality, ultra-specific inside joke AI generated memes. This has added real value to my life.

I'm starting to feel FOMO, a bit worried that if I don't go hard on learning this new tool I'm going to be left in the dust. To me at least, AI feels different.

sumedh
2 replies
19h55m

Blockchains have been super hyped.

Were regular people using it like ChatGpt?

hnthrow289570
1 replies
16h22m

Yeah up until Mt. Gox exploded and maybe a bit afterwards

After that it started really getting its scammy, investor-only reputation

theshackleford
0 replies
11h33m

Every normie I know who has touched crypto ONLY got into it after it gained its scammy investor status. Prior to that it was basically only people like me…dudes running Linux etc, you know the type.

LorenzoBloedow
2 replies
21h19m

I'll admit blockchains (while they may have potential for the future) don't currently have much use in the real world, but saying the only people it helps are criminals is just that old flawed argument that undermines privacy which in turn only benefits oppressors

apitman
1 replies
21h14m

I didn't say the only people it helps is criminals. I said that's the only example I've seen in the real world. If you have more I'd be happy to hear about them.

kortilla
0 replies
18h36m

Sending money to family in another country with crap financial infrastructure

Ekaros
0 replies
20h53m

I have followed one site that has own AI generator for certain type of content... And after a while it just start to feel samey and soulless... I kinda noticed similar stylistic patterns with text generated I have seen posted... Different styles can be asked, but I wonder how soon the AI output stops feeling worth seeing or reading.

paulmd
4 replies
20h55m

just like previous technology hype cycles were surely going to Change Everything. I mean, we're seeing huge companies' entire product strategies changing overnight because We Must All Believe.

this didn’t really happen the way you want it to. Fortune 50 companies never spent billions of dollars on crypto or NFTs like they are doing for AI. No NASDAQ listed companies got trillion-dollar valuations out of crypto.

There is buy-in happening this time, unlike previous times, because this time actually is different.

The whole AI thing just continues to baffle me. It's like everyone is in the same trance and simply assuming and chanting over and over that This Will Change Everything

I mean, some people see a broad consensus forming and reactively assume everyone else must be stupid (not like ME!). That’s a reflection of your own personal contrarianism.

Instead, try to realize that a broad consensus forming means you actually hold heterodox opinions, and if you think you have a good basis for them that’s fine, but if the foundation for your point that everyone in the world is too stupid to see what’s REALLY going on then maybe your opinions aren’t as reasoned as you think they are. You need to at least understand the values differences that are leading you down the road to different conclusions before you just dismiss the whole thing as “everyone else is just too wrapped into the cult to see straight”.

Bitcoin was actually rebuttable on some easily-explicable grounds as to why nobody really needed it. Why do you think semantic embeddings, semantic indexes/generation, multimodal interfaces, and computationally-tractable optimization/approximation generators are not commercially useful ideas?

ryandrake
1 replies
20h28m

Instead, try to realize that a broad consensus forming means you actually hold heterodox opinions, and if you think you have a good basis for them that’s fine, but if the foundation for your point that everyone in the world is too stupid to see what’s REALLY going on then maybe your opinions aren’t as reasoned as you think they are.

I haven't even formed much of an opinion either way, yet. Sure, I have doubt, but that's more of a default than something I reasoned myself into. I'm saying it's just way too early to make statements either way about the future of LLMs and AI that are anything beyond wild guesses. "This time it's different, it's fundamentally transformative and will obviously change the world" is a religious statement when made this early.

fragmede
0 replies
19h39m

Early would have been with GPT-2 writing bad poems. ChatGPT was released 1 year and 7 months ago, so it's still in diapers, but at that age it's already providing value to its users.

rsynnott
0 replies
19h27m

this didn’t really happen the way you want it to. Fortune 50 companies never spent billions of dollars on crypto or NFTs like they are doing for AI.

Got to imagine that IBM’s spending on their weird blockchain hobby was at least in the hundreds of millions.

And Facebook spent tens of billions of dollars on metaverse stuff, of course.

philipwhiuk
0 replies
19h57m

this didn’t really happen the way you want it to. Fortune 50 companies never spent billions of dollars on crypto or NFTs like they are doing for AI. No NASDAQ listed companies got trillion-dollar valuations out of crypto.

nvidia did very well out of crypto.

from-nibly
3 replies
19h26m

Its because it has to. We're so far behind the 8 ball at this point if it doesn't work we are all screwed.

All of society is so freaking leveraged at this point, something has to give.

pas
2 replies
18h48m

society is so freaking leveraged

can you elaborate on this? in what sense?

ukuina
0 replies
16h41m

I think they're implying AI has too much investment behind it to implode (i.e., it's "too big to fail").

SoftTalker
0 replies
15h28m

$35T in national debt for one. At some point that house of cards is going to collapse.

tootie
2 replies
21h34m

I can't see any news out of Sequoia without remember how massively bullish they were on FTX.

fragmede
1 replies
20h1m

they're human and were taken in by con artists. it's a reminder that none of us are infallible.

kibwen
0 replies
14h59m

It's one thing to be taken in by con artists, it's another to publicly boast about your limitless credulity and your complete and utter lack of judgment. Sequoia aren't innocent senile grandmas who got conned by high-pressure scam calls, they're gullible trend-chasing morons who were victims of their own starry-eyed greed.

tim333
2 replies
19h14m

Imagine looking back on the earth's history from a billion years in the future. There will be a divide around now between a few billion years before when biological life was the most advanced thing going on and after that when AI life was. It's in a different category to the other tech hypes. And I don't really see any possible way that it won't happen(?)

p1esk
1 replies
17h51m

I don’t think anyone doubts that.

The question is when exactly do we get to human level intelligence on all tasks (agi)? Is it going to be GPT5? GPT6? Or has the performance improvements saturated already? It makes a huge difference in terms of your investment and even career decisions whether you expect it to happen next year or 10 years from now.

tim333
0 replies
9h10m

Fair enough although some people do doubt it. I guess zooming in AI will gradually exceed human abilities in different areas like it's already much better at chess and still rubbish at going down to the shop to get a pint of milk. I'm not sure how the plays into ten year investment and career plans. There's probably a lot of opportunity at the moment for startups to take ChatGPTs abilities and apply them to human tasks involving written language.

postalrat
2 replies
20h32m

This whole AI thing reminds me of the early 90 and people talking about how computers would change the world. Of course they were right but probably not in the ways they expected.

ukuina
0 replies
16h41m

If you go back and look at the overhyped ads back then, you'd see them describing the future that we are currently living, except tainted by some institutions that were too-ingrained; things like "Using the World Wide Web, you will be able to view your checking account balance and make a payment to your utility provider with just a few clicks!" right after someone brings the milk in. i.e., They could predict online banking but not the rise of DoorDash.

Given the accelerated invention/deployment cycles we're in, it's not hard to extrapolate GPT4o to $0 token cost and 0ms latency. Even assuming stagnation in context lengths and cognition, the extreme scope of impact on every computerized industry becomes self-evident.

ip26
0 replies
18h32m

I think many of the changes actually were predicted. What seems to have been the most unexpected was how it would monetize and where market power would gather.

Online banking is great, and people knew it was coming since the dawn of the internet, but they mostly didn’t predict Stripe.

jiggawatts
2 replies
19h24m

Don’t assume “widespread deployment of the same”. Think about next-gen models running faster and at a low cost.

They already understand spoken English and can respond in kind.

This is Siri or Alexa on steroids. Just that alone is a “killer app” for everyone with a mobile phone or a home assistant device!

What’s the addressable market for that right now? Five billion customers? Six or seven maybe?

Computer RPG games are about to become completely different. You’ll be able to actually converse with characters.

Etc…

I’m a short-term pessimist but a long-term optimist.

This all reminds me of 3D graphics a in the early 1990s. The nerds were impressed but nobody else thought it was interesting. Now we have Pixar and a computer games industry bigger than Hollywood.

mechagodzilla
1 replies
17h57m

Siri and Alexa are good examples - they turned out to be incredibly expensive to develop and had extremely limited productivity benefits for users, while being almost impossible to monetize.

jiggawatts
0 replies
17h48m

That's... my point. You're agreeing with me.

Siri and Alexa are bad. Very, very bad.

They pretend to understand spoken English, but they don't, because they're just a huge set of hard-coded rules written out one-at-a-time by enormous numbers of very expensive developers.

This is the 1990s approach to AI: Fuzzy logic, heuristics, solvers, dynamic programming, etc...

That approach has been thoroughly blown out of the water by Transformers, which does all of that and much more with a thousand lines of code that can be banged out in a couple of hours by one guy while talking in a YouTube video: https://www.youtube.com/watch?v=kCc8FmEb1nY

Transformers will revolutionise this entire space, and more that don't even exist yet as a market.

Take for example humanoid robots: Boston Dynamics has had the hardware working well enough for a decade, but not the software. You can't walk up to one of their robots, point at something, and tell the robot to complete a task. It can't understand what it is seeing, and can't understand English instructions. Programming that in with traditional AI methods would take man-millenia of effort, and might never work well enough.

If we could speed up GPT-4o (the one with vision) to just 10x or 50x its current speed, with some light fine-tuning it could control a humanoid robot right now with a level of understanding comparable to C3P0 from Star Wars!

perlgeek
1 replies
21h34m

Remember that this is written by Venture Capital investors, and they make high risk, high reward bets.

I don't know the exact numbers, but I guess only maybe 5% of all investments in a given batch make any impact on the total return.

So for a VC, if there's a 10% chance that this whole AI thing will be a financial success, it's chance of success is already twice as high as average, so a pretty good bet.

xmprt
0 replies
21h30m

My rule of thumb is that if someone was super bullish on crypto 3 years ago and is now super bullish on AI then their opinion is probably not worth that much. But if they've been consistently optimistic about AI progress over the last 5-10 years then they probably know what they're talking about.

geph2021
1 replies
20h45m

When you think about the promise (or hype) of crypto/bitcoin/blockchain 10 years ago, in some sense it augured equally, if not more, transformative change/disruption than AI.

Crypto portended drastic and fundamental changes: programmable money, disintermediation, and the decentralization of the very foundations of our society (i.e. money, banking, commerce). Suffice to say that nothing close to this has happened, and probably will never happen.

So I can see how many people are equally skeptical that AI, as the next hyped transformative technology, will achieve anything near the many lofty predictions.

2OEH8eoCRo0
0 replies
19h51m

Why is there such an effort to hitch current AI to cryptocurrency? They have nothing in common, not the tech, and not the way people interact with it.

epolanski
1 replies
19h48m

I can't summarize it better than saying that AI hype is deserved, but the excessive euphoria and FOMO are not.

wayeq
0 replies
17h24m

You know I hear ChatGPT is pretty good at summarizing.

rsynnott
0 replies
19h41m

They’re a _VC_. If they don’t believe in it, what are they even doing? You can’t really expect them to be particularly objective about it.

root_axis
0 replies
19h49m

Transformers clearly represent a significant advancement in software design, this is undeniable. For example, LLMs are so good at language translation that every approach to machine translation ever conceived of is now obsolete by a very large margin. There are a few other examples and certainly some new ones will emerge, so the tech is good and it's here to stay.

The question of "how do we make money from it" is a much harder to answer. Using every available computer to run quadratic time brute force on everything you can scrape from the internet is an unbounded resource sink that offers little practical return for almost everybody, but leveraging modest and practical use of generative machine learning where it works well will absolutely create some real value.

michael_nielsen
0 replies
20h6m

There's (at least) two meanings for AI: (1) Software systems based on extensions of the LLM paradigm; and (2) Software systems capable of all human cognitive tasks, and then some.

It's not yet clear what (1) has to do with (2). Maybe it turns out that LLMs or similar can do (2). And maybe not.

I can understand being skeptical about the economic value of (1). But the economic value of (2) seems obviously enormous, almost certainly far more than all value created by humanity to date.

danans
0 replies
19h45m

> A huge amount of economic value is going to be created by AI. Company builders focused on delivering value to end users will be rewarded handsomely.

Such strong speculative predictions about the future, with no evidence.

The speculation makes sense from a VC's perspective, but perhaps not from the perspective of society at large (i.e. human workers).

From the revenue-generating use cases of LLMs (== AI in the article) that I've seen so far, most seem to be about replacing human mental labor with LLMs.

The replacement of workers with AI-based machines will likely happen in mature industries whose market growth is basically capped. Productivity will stay mostly the same, but the returns will increase dramatically as the human workforce is hollowed out.

To the extent that AI instead empowers some workers to multiply their productivity with the same amount of effort, then it can create more economic value overall, and this may happen in industries with a long growth runway ahead.

On balance, it's not clear to me whether the growth (in productivity and employment) that comes from the latter will be enough to offset the employment losses from the former.

But in either scenario, the VCs investing in AI win, either from efficiency gains, or from accelerating growth in new industries.

avereveard
0 replies
18h26m

Think about all the high volume processes in the enterprise world with a expensive human fallback. Llm are great after the process and before the human to reduce tasks routed to the fallback.

Think about all human involved in producing unstructured document that people have to read like public councils, court of laws, teachers or other evaluators. Llm can be given a relevancy metric and flag content so that those in need of or waiting for a certain information aren't drowned in noise

Llm are unlocking digital transformation in sectors that have been historically resistant to it, and because they are goal driven they do it with minimal programming, just a few good prompts and a data pipeline.

And it's just the tip. They don't get tired, they don't forget nor omit, they are absolutely bonkers to find relevant products and services given a database a need and a set of preferences and they will transform how the next generation will make purchasing decisions, travel decision and all these opinion based choices.

And while llm are likely not the path to agi and they will cap out in capabilities at some point, they are coming down in price super fast, which will propel adoption even for those cases where other options would be more sensible, just because of the sheer convenience of just asking them to do stuff.

Terr_
0 replies
21h29m

How can anyone be so certain about this?

Oh, it's really simple, you see if they don't get rewarded handsomely, that proves they didn't focus on delivering true [Scotsman] value. /s

2OEH8eoCRo0
0 replies
19h53m

I think they've tapped into something fundamental about knowledge, the mind, and information and this is only the beginning. How many different ways are there to train, wire these up, and integrate with other systems? Then the silicon built for it...I just don't know where the horizon is.

LarsDu88
100 replies
21h38m

According to Jensen it takes about 8000 H100s running for 90 days to train a 1.8 Trillion param MoE GPT-4 scale model.

Meta has about 350,000 of these GPUs and a whole bunch of A100s. This means the ability to train 50 GPT-4 scale models every 90 days or 200 such models per year.

This level of overkill suggests to me that the core models will be commoditized to oblivion, making the actual profit margins from AI-centric companies close to 0, especially if Microsoft and Meta keep giving away these models for free.

This is actually terrible for investors, but amazing for builders (ironically).

The real value methinks is actually over the control of proprietary data used for training which is the single most important factor for model output quality. And this is actually as much an issue for copyright lawyers rather than software engineers once the big regulatory hammers start dropping to protect American workers.

Voloskaya
24 replies
14h51m

This means the ability to train 50 GPT-4 scale models every 90 days or 200 such models per year.

Not anywhere close to that.

Those 350k GPUs you talk about aren't linked together. They also definitely aren't all H100s.

To train a GPT-4 scale model you need a single cluster, where all the GPUs are tightly linked together. At the scale of 20k+ GPUs, the price you pay in networking to link those GPUs is basically almost the same as the price of those GPUs themselves. It's really hard and expensive to do.

FB has maybe 2 such clusters, not more than that. And I'm somewhat confident one of those cluster is an A100 cluster.

So they can train maybe 6 GPT-4 every 90 days.

LarsDu88
22 replies
13h32m

I had to take a second look at this: https://www.datacenterdynamics.com/en/news/meta-to-operate-6...

340,000 H100s 600,000 H100 equivalents (perhaps AMD Instinct cards?) On top of the hundreds of thousands of legacy A100s.

And I'm certain the order for B100s will be big. Very big.

Even the philanthropic org Chan-Zuckerberg institute current rocks 1000 H100s, probably none used for inference.

They are going ALL OUT

onion2k
19 replies
12h33m

They are going ALL OUT

Just like they did for their metaverse play, and that didn't work out very well.

LarsDu88
18 replies
12h12m

I honestly don't think we've seen the end of AR/VR yet. The tech continues to improve year over year. There are rumors the prototype Zuck plans to show at Meta Connect this year are mindblowing

onion2k
17 replies
11h42m

Better VR tech won't make people buy VR. You could literally offer them a Star Trek holodeck and they still wouldn't buy in. People don't buy it because they don't see the point.

This was even true in Star Trek. People could do literally anything on a holodeck and the writers still had them going to Risa for a holiday.

There is no chance of VR going mainstream until someone solves the fundamental human problem of people preferring to do things in real life.

TeMPOraL
5 replies
9h58m

This was even true in Star Trek. People could do literally anything on a holodeck and the writers still had them going to Risa for a holiday.

If anything, that was a failure of imagination on writers' part, somewhat rectified over time and subsequent shows. Even in the core shows (TNG, DS9, VOY), we've seen the holodeck used for recreation, dating, study, simulation, brainstorming, physical training, hand-to-hand combat training, marksmanship training, gaming out scenarios for dangerous missions, extreme sports, engineering, accident investigation, crime scene reconstruction, and a bunch of other things. Still, the show was about boldly going where no one has gone before - not about boldly staying glued to a virtual reality display - so this affected what was or wasn't shown.

Plus, it's not either/or. People went to Risa to have real sex (er, jamaharon) with real people, and lots of (both it and them). This wasn't shown on-screen, just heavily implied, as this is where Roddenberry's vision of liberated humanity clashed with what could be shown on daytime TV. Holo-sex was a thing too, but it was shown to be treated more like pornography today - people do it, don't talk much about it, but if you try to do it too often and/or with facsimile of people you know, everyone gets seriously creeped out.

ChainOfFools
2 replies
7h52m

so much human potential, natural resources, and anxiety wasted on obsessive pursuit of diddling a few special nerve endings, heaped in a mountain of self-serving social pecking order mythology and ritualistic mystery.

mc32
1 replies
7h4m

Once we can produce offspring in sci-fi vats, then we can remove the then unnecessary organs from our DNA and not have those worries. We can be just like human ants where the queen is now vats and we just work and maybe think a little.

plasticchris
0 replies
4h33m

What a brave new world it would be.

jordanb
0 replies
4h55m

In TNG we see Barkley get addicted to the holodeck and use it to play out fantasies with female members of the crew. Through the episode we end up learning that Barkley escaped to the holodeck because he was having problems and not being fulfilled in his real life.

There was a similar episode of DS9 where Nog gets addicted to the holodeck due to war trauma.

The central take of the show is that real life is better for these people in this future communist space utopia and the only reason why you'd go to the holodeck is light entertainment, physical training, or if there's something wrong with your life that needs fixed.

figassis
3 replies
10h48m

VR requires too much setup. I have a PS4, bought a used PSVR set and realized I needed a camera that I did not have. Realized instead of buying a camera, I could upgrade to a ps5 and buy the new headset that did not require a camera, bc I prefer not to have my living room look like a lab. Then there is the social aspect of it.

You can't interact with people around you the same way you do if you play with, say, a console controller. VR is an all encompassing activity that you have to dedicated time for, instead of having it casually just exist around you. Then we have the cost. Only some people can have it, so it will be a lonely activity most of the time when it could be so much more.

I can afford it, but every time I am in front of a new set, I consider my life with it and say "maybe next time". Finally, I have not really explored them, but I have a feeling the experience is limited by the content that exists.

I dream of a VR experience where suddenly all content I currently enjoy on flat screens will automagically be VRified. But I am pretty sure that will not be the case. Only a very limited collection will be VR native.

But I want it all to be, or almost all, before I go all in.

pmarreck
0 replies
2h8m

Vision Pro is already that today, FYI. It’s honestly amazing.

But it’s too expensive and still too heavy on your face.

mapt
0 replies
2h43m

The appropriate response to VR is that we all get a VR/storage/etc room in addition to the existing paradigms of bedroom, living room, kitchen, etc. At the high end we've grown houses to the point that in order to remain boxes they demanded interior rooms without windows, and so far we have varied between refusing to build these rooms because "natural light" and outright banning these rooms for safety reasons, creating sprawling complicated floorplans instead with lots of surface area per volume.

It would be a bit better suited to a civilization that wasn't undergoing a catastrophic urban housing shortage crisis with demographic & economic effects for upcoming generations that are comparable to a world war or the Black Death. We are building huge exurban houses which nonetheless do not have VR-appropriate rooms, and tiny 1-bedroom apartments, and not much else. https://www.youtube.com/watch?v=4ZxzBcxB7Zc

The question is whether this is a chicken/egg problem that prevents us from launching next-generation VR plays.

LarsDu88
0 replies
5h2m

You should try the quest3. Virtually no setup

duggan
1 replies
8h22m

There is no chance of VR going mainstream until someone solves the fundamental human problem of people preferring to do things in real life.

Ready Player One had a pretty good answer to this: dystopia. Once real life is miserable enough, VR's time will have arrived.

bergie
0 replies
8h7m

That, or another year of lockdown could also do it.

tonynator
0 replies
11h4m

Think you're off base here and the issue is comfortability. People spend all day on their computers and phones, VR just needs to make some breakthroughs in comfort (maybe built-in fans? Literally include ginger tablets with the headset?) to get people over the initial nausea hump. This plus higher resolution for AR purposes will do a ton.

Now, there may also be a physical laziness factor to overcome, but there are enough people that enjoy moving their bodies to really explode the industry even if all the lazy folks stay 2D.

rlt
0 replies
10h47m

AR might be a different story, if the tech gets small/good enough.

jononor
0 replies
7h56m

There is no chance of VR going mainstream until someone solves the fundamental human problem of people preferring to do things in real life.

Three counterpoints: Online gaming, social media, smartphones. All of these favor "virtual" over "real life", and have become massively popular over the last decades. Especially among the young, so the trend is likely to continue.

eru
0 replies
11h12m

There is no chance of VR going mainstream until someone solves the fundamental human problem of people preferring to do things in real life.

I don't think that's much of a problem? People already watch TV and play computers games and read novels, instead of real life.

I agree that VR has _some_ problem, but I don't think it's that people prefer real life.

boloust
0 replies
11h18m

Totally agreed. It's like the hype around "social media" or "streaming services" or "video games". There's no chance of any of them going mainstream because of the fundamental human problem of people preferring to do things in real life.

dmix
1 replies
13h12m

Even the philanthropic org Chan-Zuckerberg institute current rocks 1000 H100s, probably none used for inference.

What do they use them for?

ChainOfFools
0 replies
7h51m

tax writeoffs

LarsDu88
0 replies
13h41m

Ok, I might have misread some rumored ballpark figures. And most of the GPUs will be used for inference rather than training. Still 6 GPT-4's every 90 days is pretty amazing.

apitman
14 replies
21h12m

I thought AI is supposed to put all the lawyers out of work.

tracerbulletx
6 replies
17h58m

Nothing will put lawyers or doctors out of work. They are powerful cartels that can easily protect themselves. Realtors are already irrelevant technologically but they have a huge entrenched social and legal system to make it impractical to compete.

bamboozled
4 replies
13h29m

My friend is a real estate agent, they play a major part in the psychology of buyers and sellers. Selling your dead parents home that you grew up in (for example) isn't something everyone just signs up to some website and does using a credit card without a second thought.

A good real estate agent can guide people through this process while advising them on selling at the right price while avoiding the most stress often during an extremely difficult time in their life, such as going through divorce of breakup. They of course also help keep buyers interested while the seller is making up their mind about the correct offer to take.

I find your comment ignorant in so many ways. Maybe have some respect?

dmix
3 replies
13h0m

Are you not just explaining "a huge entrenched social system" as OP said?

It takes a long time for cultures to shift and for people to start to trust information systems to entirely replace high touch stuff like that. And at some level there will always be some white glove service on top for special cases.

bamboozled
2 replies
12h42m

How is hiring a professional to help you sell a property a "huge entrenched social system" sorry ? No one is forced to hire a real estate agent. I bought my house through private sale.

DataDive
1 replies
12h26m

No one is forced to hire a real estate agent.

but for long time in the US you were "forced" to hire a real estate agent, if you wanted to get the market price.

Refer to the NAR settlement that pretty much admits to this.

https://www.realestatecommissionlitigation.com/

This is not to say that real estate agents cannot add value to a process; it is just that they were a cartel with anticompetitive practices.

The mandated and fixed 6% on each sale was and is ridiculous, when the median sell price is 400K in the US ... that is 24K commission

wolfendin
0 replies
12h11m

That really does say something about how unrealistic house prices are nowadays, doesn’t it?

DataDive
0 replies
12h28m

Weren't lots of realtors recently put out of work in the US, at least?

When NAR settled the price collusion charge? Thus cartel or not, times do change.

falcor84
4 replies
19h43m

Just out of curiosity, what's the human lawyer baseline on that?

dbish
2 replies
17h51m

it's the self-driving car problem. Humans aren't perfect either but people like to ignore that.

Terr_
0 replies
17h29m

True, they're similar... But what's also similar is that people make the mistake of focusing on differences in failure rates while glossing over failure modes.

Human imperfections are a family of failure-modes which have a gajillion years of experience in detecting, analyzing, preventing, and repairing. Quirks in ML models... not so much.

A quick thought-experiment to illustrate the difference: Imagine there's a self-driving car that is exactly half as likely to cause death or injury than a human driver. That's a good failure rate. The twist is that its major failure mode is totally alien, where units attempt to inexplicably chase-murder random pedestrians. It would be difficult to get people to accept that tradeoff.

Barrin92
0 replies
16h14m

No, people have the correct intuition that human errors at human speeds are very different in nature from human rate errors at machine speeds.

It's one thing if a human makes a wrong financial decision or a wrong driving decision, it's another thing if a model distributed to ten million computers in the world makes that decision five million times in one second before you can notice it's happening.

It's why if your coworker makes a weird noise you ask what's wrong, if the industrial furnace you stand next to makes a weird noise you take a few steps back.

csa
0 replies
17h51m

Just out of curiosity, what's the human lawyer baseline on that?

Largely depends on how much money the client has.

zacmps
0 replies
15h14m

I'm sure it's no where near good enough yet, but a legal model getting the answer right 83% of the time is still quite impressive imo.

shoggouth
13 replies
17h26m

In my opinion Elsevier and others charging for access to academic publications has held back the advancement of humanity to a lower exponential acceleration into the future at a considerable factor. Think of how cancer could have been cured a decade ago if information was allowed to flow freely from the 50's forward - if anyone could have read scientific publications for free. I have no respect for people that want to protect the moat around information that could be used to advance humanity.

OJFord
4 replies
17h11m

As much as I'd love open access to academic publications and don't think the current model is great:

Think of how cancer could have been cured a decade ago if information was allowed to flow freely from the 50's forward

might be a bit fanciful? Unless you're referring to something particular I'm unaware of.

The people best equipped and trained to deliver a cure for cancer (and then some, since it tends not to be particularly field-restricred) do have access.

I think the loss is more likely in engineering (to the publication's science), cheaper methods, more reliably manufacturable versions of lab prototypes, etc.

I doubt there are many people capable of cancer research breakthroughs who don't have access to cancer research, personally.

(And to be clear: I'm not capable of it.)

enjoylife
1 replies
17h1m

I’ll add that even if the papers we all wanted were more freely accesible, the replication and completeness of their described methods would be another source of slowdown.

robwwilliams
0 replies
16h15m

Main problem is still just getting good quantitative data and metadata. Most biomedical researchers are motivated to “tell stories”. Few of us care about generating huge mineable data sets.

instagib
0 replies
14h24m

All of the engineering companies I’ve worked for have not paid for IEEE or any journals. I have to go to the library and maintain membership for IEEE myself then request reimbursement.

The schools I’ve worked with have access to everything I’ve needed. They didn’t advertise it but it’s also free for students.

azinman2
0 replies
12h14m

Not to mention there is not singular “cancer” - there are many types and they’re all sufficiently different to make the problem much more challenging.

robwwilliams
1 replies
16h18m

Have to disagree. Almost all researchers have essentially unfettered access to all of biomedical literature. Access to papers is therefore a tertiary annoyance wrt progress in science and the cures for cancers.

What IS a huge problem is the almost complete lack of systematically acquired quantitative data on human health (and diseases) for a very large number (1 million subjects) of diverse humans WITH multiple deep-tissue biopsies (yes, essentially impossible) that srr suitable for multiomics at many ages/stages and across many environments. (Note, we can do this using mice.)

Some specific examples/questions to drive this point home: What is the largest study of mRNA expression in humans? ANSWER: The small but very expensive NUH GTEx study (n max of about 1000 Americans). This study acquired postmortem biopsies for just over 50 tissues. And what is the largest study of protein expression in humans across tissues? Oh sorry, this has never been done although we know proteins are the work-horses of life. What about lipids, metabolites, metagenomics, epigenomics? Sorry again, there is no systematically acquired data at all.

What we have instead is a very large cottage-industry of lab-level studies that are structurally incoherent.

Some brag about the massive biomedical data we have, but it is truly a ghost and most real data evaporates with a few years.

Here is my rant on fundamental data design flaws and fundamental data integration flaws in biomedical research:

Herding Cats: The Sociology of Data Integration https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2751652/

mchinen
0 replies
8h4m

I also think the bottleneck isn't access to the papers today and data access and silos are more important.

But I also think the GP's claim and yours are not incompatible. I wonder how much survivorship bias this has since it only considers those that are able to do research, and not those that would have but ended up doing continuing with another STEM job. We could be asking the counterfactual that I think the GP is implying: would more people have been interested in becoming cancer researchers if publications were open?

We can sort of see the effect because we have scihub now, which basically unlocks journal access for those that are comfortable with it, and I consider it plausibly having a significant effect for the population that have a research background without an academic affiliation. I've met a few biotech startup founders that switched from tech to bio and did self study+scihub outside of the university. The impetus for change I've heard a few times is a loved one got X disease, and I studied it, quit my less impactful tech job to work on bio stuff.

lkrubner
1 replies
2h31m

But anyone who needs to see these publications can reach them through libraries. One of the reasons why Elsevier can charge so much is that their customers have been institutions.

aleph_minus_one
0 replies
2h14m

This depends a lot on the country and the library.

xhkkffbf
0 replies
2h42m

1) First, most researchers at universities or other institutions have always had unfettered access thanks to a site license. It would be pretty hard to find a real example of a university researcher who couldn't see something.

2) There may be a few researchers who don't have unfettered access. Perhaps they paid $40 for a copy of a paper. Given the high cost of other parts of research labs, I find it hard to believe that any real possibility of curing cancer was halted because someone had to pay $40.

3) It's possible to imagine the opposite being the case. Perhaps someone had a key insight in a clever paper and decided to distribute it for free out of some info-anarchistic impulses. There it would sit in some FTP directory uncrated, unindexed and uncared for. Perhaps the right eyes would find it. Perhaps they wouldn't. Perhaps the cancer researcher would be able to handle all of the LaTeX and FTP chores without slowing down research. Perhaps they would be distracted by sys admin headaches and never make a crucial follow up discovery.

The copyrighted journal system provides curation and organization. Is it wonderful? Nah. Is it better than some ad hoc collection of FTP directories? Yes!

Your opinion may be that this scenario would never happen. In my opinion, this is more likely than your vision.

robertlagrant
0 replies
2h31m

You have to not latch on to causes such as "advance humanity" and then justify making people do work for free. We decided a while ago[0] that making people work for free was a bad thing. There is high demand for curing cancer. Every company that tries it will hire scientists and lab techs and large laboratories, and have subscriptions to journals. Do you think all of those people should work for free, in the cause of advancing humanity?

[0] https://en.wikipedia.org/wiki/Slavery_Abolition_Act_1833

jimjimjim
0 replies
16h6m

99%+ of the people doing scientific work in curing cancer have access to all the relevant medical and scientific journals.

eru
0 replies
11h10m

Eh, most published research papers are wrong anyway.

alberth
12 replies
18h4m

making the actual profit margins from AI-centric companies close to 0

The same thinking stopped many legacy tech companies from becoming a “cloud” company ~20 years ago.

Fast forward to today and the margin for cloud compute is still obscene. And they all wish in hindsight they got into the cloud business way sooner than they ultimately did.

lmm
6 replies
17h20m

Are the second-tier cloud companies really seeing big margins? Why is it not competed away to zero like airlines?

mbb70
3 replies
17h15m

There is essentially zero cost for a user to switch airlines. The cost to switch clouds is astronomical for any decent sized org.

throwaway2037
1 replies
13h39m

I like the sentiment of your post. I mostly agree. If you use OpenShift, doesn't that help to reduce the cost of switching cloud providers?

coredog64
0 replies
1m

Not really. What happens when you run a cloud on top of your cloud is that you don’t get to use any of their differentiating features and that winds up costing you money. Plus you have to pay for your own control plane when that’s already baked into the cloud provider’s charge model.

jart
0 replies
12h13m

Those poor little AI clouds will never keep people reeled in unless they invent something like CUDA.

flyingpenguin
1 replies
16h28m

There will probably be 2 huge winners, and everyone else will fail. Similar to the solar boom.

throwaway2037
0 replies
13h38m

Who are the winners in solar?

jordanb
4 replies
3h29m

That's not the way I remember the cloud transition at all. My company adopted an internal cloud. VMWare had some great quarters. Openstack got really big for a while and everyone was trying to hire for it. All the hosting companies started cloud offerings.

What ended up happening was Amazon was better at scale and lockin than everyone else. They gave Netflix a sweet deal and used it as a massive advertisement. It ended up being a rock rolling down a hill and all the competitors except ones with very deep pockets and the ability to cross-subsidize from other businesses (MSFT and Google) got crushed.

demondemidi
2 replies
2h22m

It still blows my mind that Microsoft is the most valuable company in the planet because of the cloud and Balmers long term vision. I thought they would have gone the way of IBM.

hollerith
0 replies
2h20m

Agree. Ballmer seems to have done his job well.

fragmede
0 replies
2h20m

Which, IBM booked about $62 billion in revenue for 2023.

I thought Nvidia recently took that crown recently though.

coredog64
0 replies
3m

It’s not just the software, it’s the hardware too. Too many companies got good at speeding up VM deployments but ignored theory of constraints and still had a 4-6 month hardware procurement process that gave everyone and their dog veto power.

And then you come to companies that managed to streamline both and ran out of floor space in their data center because they had to hold onto assets for 3-5 years. At one previous employer, the smallest orderable unit of compute was a 44U rack. They eventually filled the primary data center and then it took them 2 years to Tetris their way out of it.

Kon-Peki
9 replies
21h31m

It's like someone thinking that they are SOOOO smart, they are going to get rich selling shovels in the gold rush. So they overpay for the land, they overpay for the factory, they overpay for their sales staff.

And then someone else starts giving away shovels for free.

Terr_
5 replies
21h27m

And then someone else starts giving away shovels for free.

And their business model is shovel-fleet logistics and maintenance... :p

woah
1 replies
19h39m

The platform for shovel fleet logistics startups

ugh123
0 replies
18h14m

SaaS (shoveling as a service)

TeMPOraL
1 replies
21h19m

And/or exploiting the legal infrastructure around intellectual property rights to make sure only hobbyists and geologists can use the shovels without paying through the nose or getting sued into oblivion.

freehorse
0 replies
17h55m

If your company grows to 700 million monthly active users, then most probably you can make your own AI department and train your own models. I guess people's aspirations are very high in this space, but let's be realistic.

jona-f
0 replies
11h6m

Their business model is of course tracking all the shovels and then selling the locations of all the gold.

gwd
1 replies
10h47m

And then someone else starts giving away shovels for free.

Ah, I see -- it's more like a "level 2 gold rush".

So a level 1 gold rush is: There's some gold in the ground, nobody knows where it is, so loads of people buy random bits of land for the chance to get rich. Most people lose, a handful of people win big. But the retailers buying shovels at wholesale and selling them at a premium make a safe, tidy profit.

But now that so many people know the maxim, "In a gold rush, sell shovels", there's now a level 2 gold rush: A rush to serve the miners rushing to find the gold. So loads of retailers buy loads and loads of shovels and set up shop in various places, hoping the miners will come. Probably some miners will come, and perhaps those retailers will make a profit; but not nearly as much as they expect, because there's guaranteed to be competition. But the company making the shovels and selling them at a premium makes a tidy profit.

So NVIDIA in this story is the manufacturer selling shovels to retailers; and all the companies building out massive GPU clouds are the retailers rushing to serve miners. NVIDIA is guaranteed to make a healthy profit off the GPU cloud rush as long as they play their cards right (and they've always done a pretty decent job of that in the past); but the vast majority of those rushing to build GPU clouds are going to lose their shirts.

demondemidi
0 replies
2h25m

And basically one AI company making all the money. Weird symbiosis.

from-nibly
0 replies
19h23m

It's almost like you can't actually control the demand side.

Willish42
7 replies
17h43m

once the big regulatory hammers start dropping to protect American workers

Have we been living in the same universe the last 10 years? I don't see this ever happening. Related recent news (literally posted yesterday) https://www.axios.com/2024/07/02/chevron-scotus-biden-cyber-...

LarsDu88
5 replies
13h37m

I think people wildly underestimate how protectionist people - particularly educated software engineers and PhDs will get once an AI model directly impacts their source of wealth.

Red state blue collar workers got their candidate to pass tariffs. What happens when both blue state white collar workers and red state blue collar workers need to contest with AI. Perhaps not within the next 10 years, but certainly within 20 years!

And if you think 20 years is a long time... 2004 was when Halo 2 came out

sangnoir
1 replies
11h30m

I think people wildly underestimate how protectionist people - particularly educated software engineers and PhDs will get once an AI model directly impacts their source of wealth.

I don't know what power you imagine SWEs and PhDs posses, but the last time their employers flexed their power by firing them in droves (despite record profits); the employees sure seemed powerless, and society shrugged it off and/or expressed barely-concealed schadenfreude.

demondemidi
0 replies
2h27m

They were sued for collusion and the lawyers got a massive payout and the employees got a fraction of lost wages. I was one of them. (Employees not lawyers.)

jjallen
1 replies
10h55m

Hopefully that time AI will be working for us in our homes, stores and farms so we don't need to work as much and this is ok.

rlt
0 replies
10h45m

People will still need purpose, which for better or worse is often provided by their job.

dmix
0 replies
13h5m

It's not going to stop it though even if they try though. You can't stop technical progress like this any more than you can stop piracy.

But agreed, between the unions with political pull and "AI safety" grifters I suspect there could be some level of regulatory risk, particularly for the megacorps in California. I doubt it will be some national thing in the US absent a major political upheaval. Definitely possible in the EU which will probably just be a price passed on to customers or reduced access, but that's nothing new for them.

hnthrow289570
0 replies
16h29m

The only upside is state-level minimum wage increases. The federal minimum wage is still a complete joke at $7.25 an hour.

But there's bigger fish to fry for American politics and worker obsolescence is not really top of mind for anyone.

laweijfmvo
3 replies
21h37m

A lot of those GPUs are for their 3B users to run inferencing, no?

LarsDu88
1 replies
19h46m

True that, but I think in a very short amount of time, using dedicated general purpose GPUs just for inferencing is going to be mega overkill.

If there's dedicated inferencing silicon (like say the thing created by Groq), all those GPUs will be power sucking liabilities, and then the REAL singularity superintelligence level training can begin.

campers
0 replies
17h37m

Etched is another dedicated inference hardware company that recently announced their product. It only works for transformer based models, but is ~20x faster than a H100

benreesman
0 replies
18h23m

It’s been a very long time since I had any inside baseball, but I very much doubt that Hopper gear is in the hot inference path.

The precisions and mantissa/exponent ratios you want for inference are just different to a mixed-precision, fault tolerant, model and data parallel pipeline.

Hopper is for training mega-huge attention decoders: TF32, bfloat16, hot paths to the SRAM end of the cache hierarchy with cache coherency semantics that you can reason about. Parity gear for fault tolerance, it’s just a different game.

kristjansson
1 replies
15h47m

per Zuckerberg[0], ~half of their H100s were for Reels content recommendation:

I think it was because we were working on Reels. We always want to have enough capacity to build something that we can't quite see on the horizon yet. ... So let's order enough GPUs to do what we need to do on Reels and ranking content and feed. But let's also double that.

So there's an immense capacity inside Meta, but the _whole_ fleet isn't available for LLM training.

[0]: https://www.dwarkeshpatel.com/p/mark-zuckerberg?open=false#§...

matthewdgreen
0 replies
6h23m

Surely they’re using some of that hardware to overcome Apple’s attempts to deprive them of targeted advertising data.

weitendorf
0 replies
11h44m

There are more kinds of AI-centric companies than just foundation models. Making that equivalency is akin to equating internet companies during the dotcom bubble with just websites like pets.com. Now one semi-skilled person in a couple days can make websites that entire teams back then would have taken months to build, but that doesn't mean google.com and thefacebook.com are easily commodotized or bad businesses just because they're websites.

vasco
0 replies
19h37m

The infinitely expanding AI-generated metaverse isn't going to render itself, at least in the case of meta I think that might be one of the only pieces missing.

naveen99
0 replies
17h18m

Propriety data is not necessary for training intelligence. Wikipedia, pubmed, arxiv, Reddit and github are probably sufficient. And babies don’t even use that.

I agree though that the returns on hardware rapidly diminish.

itkovian_
0 replies
13h38m

Everything is if scaling keeps making the models better. If it does you don't train 50 gpt4s, you have the best model.

forgot-im-old
0 replies
15h37m

What percentage of GPUs are being used for training versus inference?

eru
0 replies
11h14m

The real value methinks is actually over the control of proprietary data used for training which is the single most important factor for model output quality.

Maybe. But we've barely scratched the surface of being more economical with data.

I remember back in the old days, there was lots of work on eg dropout and data augmentation etc. We haven't seen too much of that with the like of ChatGPT yet.

I'm also curious to see what the future of multimodal models holds: you can create almost arbitrarily amounts of extra data by pointing a webcam at the world, especially when combined with a robot, or letting your models also play StarCraft or Diplomacy against each other.

boloust
0 replies
11h15m

Why are we assuming we're topping out at a GPT-4 scale model?

babyshake
0 replies
11h7m

once the big regulatory hammers start dropping to protect American workers.

The US Supreme Court seems determined to make sure that big regulatory hammers are not going to be dropping, from what I can tell.

VirusNewbie
0 replies
14h43m

Llama isn't even in the same stratosphere as the big models when it comes to coding, logic, and other interesting tasks that I think are commercially viable.

threeseed
20 replies
22h6m

Founders and company builders will continue to build in AI—and they will be more likely to succeed, because they will benefit both from lower costs and from learnings accrued during this period of experimentation

Highly debatable.

When we look back during the internet and mobile waves it is overwhelmingly the companies that came in after the hype cycle had died that have been enduring.

malfist
15 replies
22h0m

Let's see: Microsoft Windows: wasn't close to the first OS

Microsoft Office: wasn't close to the first office editing suite

Google: Wasn't close to the first search engine

Facebook: Wasn't close to the first social media website

Apple: ~~First "smart phone"~~ but not the first personal computer. Comments reminded me that it wasn't the first smartphone

Netflix: Wasn't close to the first video rental service.

Amazon: Wasn't close to the first web store

None of the big five were first in their dominate categories. They were first to offer some gimmick (i.e., google was fast, netflix was by mail, no late fees), but not first categorically.

Though they certainly did benefit from learnings of those that came before them.

AlexandrB
11 replies
21h58m

Apple: First "smart phone" but not the first personal computer

Was it the first smartphone? I would call phones like the Palm Treo and later BlackBerries smartphones. There were even apps, but everything was lot more locked down and a lot more expensive.

dvt
4 replies
21h52m

There were even apps, but everything was lot more locked down and a lot more expensive.

And just plain... bad. The entire experience didn't have that "feel" that Apple turned into reality. It's comparable to today's AI landscape—the technology is pretty neat, but using it is a complete slog.

nextos
2 replies
21h32m

Nokias were very open. You had a terminal with apt-get.

The entire device was a regular Linux machine.

endless1234
1 replies
20h8m

In general, they were not. You're probably thinking of the very niche and unsuccessful Maemo/MeeGo project - eg Nokia N900 - that were indeed Linux-based. But everything else smartphone-ish from Nokia before Lumia (Windows Phone) were Symbian, which predates Linux and has nothing to do with it.

nextos
0 replies
19h13m

I am of course referring to Maemo, as per my previous post.

AlexandrB
0 replies
21h46m

I actually have pretty fond memories of PalmOS PDAs. The hardware was very nice, but they were held back by the resistive touchscreen and dependence on a stylus for input. I never used a Treo but it felt like this was Palm trying to copy BlackBerry by adding a physical keyboard.

Edit: There were also the limitations of that era that held devices back in general. WAP internet[1] was awful, but most mobile services were too slow for much else.

[1] https://en.wikipedia.org/wiki/Wireless_Application_Protocol

nextos
1 replies
21h34m

There were Nokias running Maemo ahead of the iPhone. Note these were not Symbian.

The 770 was released in Q4 '05.

They definitely fell within the smartphone category, but oddly the first few iterations lacked GSM radio.

Ekaros
0 replies
20h42m

I would classify them as tablets. At least what I thought my N810 as.

irq
1 replies
21h42m

I would call phones like the Palm Treo and later BlackBerries smartphones.

It's not just you; at the time these products were available, _everyone_ called them smartphones. Emphatically, Apple did not bring the first smartphone to market, not even close. They were, however, the first to popularize it beyond the field of nerds into the general public.

tim333
0 replies
18h41m

I had an Nokia N95 which was basically a smartphone and came out a year before the iPhone. And Wikipedia says

it became a huge sales success for Nokia ... It managed to outsell rivals such as LG Viewty and iPhone.

However the iPhone got better.

seanmcdirmid
0 replies
21h53m

First modern smartphone (capacitive touch screen/multi-touch/form factor), but not first smartphone.

malfist
0 replies
21h31m

I'm a complete idiot. I almost bought an HTC fuse too

robbiemitchell
0 replies
21h43m

some gimmick

"key differentiator" and not necessarily easy to pull off or pay for

olalonde
0 replies
18h32m

I have a pet peeve with this common piece of wisdom. You can always find a "predecessor" for about anything. The corollary being that there is never a "first". And therefore, stating that "none of the big companies were the first in their categories" is just stating a tautology.

edanm
0 replies
10h30m

i.e., google was fast,

Just to quibble with this - that was not even close to the reason Google got popular. It was because Google was much, much better at finding what you actually wanted. It was just a far better product.

You can debate why this is exactly, Joel Spolsky pointed out many years ago that it was because Google got that what matters to users most isn't "finding all pages related to X" but rather "ranking" those pages, a take I agree with.

malshe
1 replies
21h36m

There is an old study that supports your point. The abstract reads:

"Several studies have shown that pioneers have long-lived market share advantages and are likely to be market leaders in their product categories. However, that research has potential limitations: the reliance on a few established databases, the exclusion of nonsurvivors, and the use of single-informant self-reports for data collection. The authors of this study use an alternate method, historical analysis, to avoid these limitations. Approximately 500 brands in 50 product categories are analyzed. The results show that almost half of market pioneers fail and their mean market share is much lower than that found in other studies. Also, early market leaders have much greater long-term success and enter an average of 13 years after pioneers."

PDF available here:

https://people.duke.edu/~moorman/Marketing-Strategy-Seminar-...

dmix
0 replies
12h39m

Yes the "first mover advantage" is mostly just a common myth in business that refuses to die, but if we look at the original statement:

Founders and company builders will continue to build in AI—and they will be more likely to succeed, because they will benefit both from lower costs and from learnings accrued during this period of experimentation

This still lines up with the 2nd wave benefiting more. The first movers helped established the large scale AI hardware industry, got a bunch of smart kids trained on how to make AI, a bunch of people will fail and learn, etc and this experimentation stage sets the groundwork for OpenAI 2.0.

We could very well just in the Altavista vs Yahoo days of AI and an upstart takes over in 5yrs.

jjtheblunt
1 replies
21h59m

“Pioneers get the arrows, and settlers get the land”?

chrisweekly
0 replies
15h18m

"The early bird gets the worm -- but the second mouse gets the cheese."

pedalpete
13 replies
20h24m

I think this is the correct take. My understanding of the article is that huge investments in hardware, mostly to NVIDIA, and spending by major tech companies is currently defining the market, even if we include OpenAI, Anthropic, etc. It is FAANG money they are running on.

I put this as equivalent to investing in Sun Microsystems and Netscape in the late 90s. We knew the internet was going to change the world, and we were right, but we were completely wrong as to how, and where the money would flow.

npalli
10 replies
18h39m

The better analogy is the massive investment in fiber optic cable in the late 90s. All the companies in that line (Global Crossing, Worldcom etc.) went bust after investing 10s of billions but the capacity was useful (with a >90% drop in price) for future internet services. Around 2000 when the bubble was bursting only 5% of capacity was being used but proved to be useful to get all internet-first companies like the Googles, Amazon, NetFlix's going.

pedalpete
3 replies
17h17m

I initially was agreeing with you, but I don't see NVIDIA, AWS, Microsoft, etc going to zero (and Worldcom was unraveled by accounting fraud).

Sun Microsystems sold to Oracle for $7B, and Netscape was acquired by AOL for $10B.

wmf
1 replies
15h53m

Yeah, Cisco didn't go to zero in 2000 and Nvidia won't go to zero. It will merely go down 90%.

aurareturn
0 replies
10h1m

When Cisco went bust, their stock price was still 150% higher than before the boom.

So will Nvidia be worth $5 trillion AFTER the AI bust?

ddrmaxgt37
3 replies
13h33m

I wonder how the analogy holds up given computational advances. Will a bunch of H100s be as useful a decade later like fiber ended up being?

torginus
0 replies
10h33m

I might be wrong, but my understanding is that we're on a decelerating slope of perf/transistor and have been for quite a while - I just looked up the OpenCL benchmark results of the 1080 Ti vs 4090, and the perf/W went up by 2.8x despite going from 16nm to 5nm, with perfect power scaling, we would've seen a more than 10x increase.

novaRom
0 replies
11h26m

Probably not. There will be better GPUs. It's like we did use all those Kepler K10 and K80 fifteen or so years ago, they were Ok for models with few millions of parameters, then Pascal and Volta arrived ten years ago with massive speed up and larger memory, allowing to train same size models 2-4 times faster, so you simply had to replace all Keplers. Then Turing happened making all P100 and V100 obsolete. Then A100, and now H100. Next L100 or whatever with just more on-board memory will make H100 obsolete quickly.

dmix
0 replies
12h45m

Same applies to the railroads analogy used in the original article.

cruffle_duffle
1 replies
18h27m

Good old JDS Uniphase was one of the first individual stocks I bought. I mean it had to go up right? Fiber and dark fiber and the continual threat of the internet collapsing due to load… better buy that stock!

elphinstone
0 replies
16h40m

Worldcom here. Ah, the Enrons of the internet.

treis
0 replies
16h46m

Think the FAANGs are doing part moat defending and part value add. Like AI powered spreadsheet might dethrone Excel so Excel has to be AI powered. MS will probably get some additional revenue from it but I don't think it will be a revolutionary amount.

hnburnsy
0 replies
18h9m

I put this as equivalent to investing in Sun Microsystems and Netscape in the late 90s.

Cisco too.

dzink
12 replies
20h57m

AI is dangerous to VCs.

The returns are going to chip-makers and employers, including single founder startups, who don't have to hire a lot of people, and additionally get productivity they never thought possible. A surgeon I know uses AI every day - to translate, to explain, to figure out problems, to write. They wouldn't have paid someone to do that, but now they get that output in seconds. This is a time to solve all kinds of problems we didn't think possible - because AI has made the enterprising among us instantly smarter.

All the fodder about AGI being a next step is smoke and mirrors - for everyone using OpenAI knows they don't need any more niche tools as their one $20 subscription is doing more for them every day. AGI is here. Experts can correct AI generated mistakes, but those are getting less and less too. The real benchmark is: Name how many people you know who can out-do ChatGPT on a question. You won't bother to check LinkedIn for that.

The gains are aggregating towards Chips, Clouds and Entrepreneurs. The VCs, since A16Z's original AI blog post (all expense, little return, echoed this Sequoia post but did it but years ago), know they are not needed as much anymore. Fewer VCs will beat the market when founders can grow startups without raising too much money (they don't need to hire as many people). Hiring needs lead to PR waves which require VC funding. Valuation is not a big deal for founders making money either, so they may not even disclose how successful their companies are. Bragging about your gains only invites competition. So other than ponzi-type ventures where you need to attract the dinner to serve dinner, you won't hear much about the good ones.

A different era indeed. The tech giants are in for a lot of change as well. Those who have distribution may try to push their models to the masses to be the point of reference, but that can get expensive, especially for those who don't charge. AI will help improve AI performance as well and that means cheaper better performance with time.

What's most needed in this era are people who know what the world needs that hasn't been invented yet. They need to be inventing and monetizing it. Little stopping you now.

tim333
2 replies
18h31m

What people mean by AGI varies but consider:

The Coffee Test (Wozniak)

A machine is required to enter an average American home and figure out how to make coffee: find the coffee machine, find the coffee, add water, find a mug, and brew the coffee by pushing the proper buttons.

That is a step yet to come.

joebob42
1 replies
16h23m

Well, that seems like a dumb test for the intelligence part. You need a robot for that. But that means intelligence cannot exist without a physical presence" which I think is at least controversial.

tim333
0 replies
9h41m

I think the idea is that for many definitions of AGI it should be able to do anything a human does and negotiating the physical world is part of that. It might seem dumb as an intelligence test but would be very economically significant. The difference between a chatbot and being able to tell a bot to build an extension on your house.

threeseed
2 replies
20h5m

This is the sort of grifter/influencer style comment that we saw in crypto and now pervasive in AI.

Not just that AI is a great tool that will over time have a significant impact on society. It’s the breathless hype e.g. we have AGI today, society will be instantly smarter because of it and every tool and employee will be impacted. The FOMO i.e. you must jump on board now or be left behind. And the complete lack of any data or evidence.

dzink
0 replies
19h22m

Except I see no grift or FOMO. You don’t need to put your money into it. All you need now is instinct and creativity. The FOMO to raise money or be nobody goes away instead. The FOMO in giants to appear like they are riding the AI horse is real. Evidence is in the productivity of each individual and how many would consult with experts or expert friends vs just using AI.

brcmthrowaway
0 replies
18h50m

Looked at their profile, total grifter vibe.

slicerdicer1
2 replies
16h39m

"The gains are aggregating towards Chips, Clouds and Entrepreneurs. "

Are the gains aggregating to entrepreneurs? It seems like every just a matter of time before the function of the big models overtakes any entrepreneurial idea other than hardware and the models themselves.

dzink
1 replies
11h58m

AI overtakes software, finance, and distraction industries (content generation of any kind - text, image, video, multi-modal). Distraction industries (social and regular media) are a time waster and brain frier for most humans who often consume to escape their world or decorate /fill their time.

In software the UX is the big burden AI will overcome. Not having to deal with all the typing and clicking frees up more tasks and energy for deciding what needs to be done. Brain energy.

Distraction industries, like sugar, become obviously tart when oversaturated and AI is quickly pushing that boundary. Once people realize they’ve been served a pacifier to the brain in every free minute, they will start thinking more and consuming less.

So now AI frees more human brain energy towards what is actually needed - what problems need solved for humans, not for overloaded interfaces or zombified content consumers.

Examples: Trustworthy, efficient and safe transport for kids to and from enrichment activities. Education of others on tasks that could earn them a living. A better healthcare experience, because 60% of the admin paperwork is AI automated and health workers can talk to patients instead of typing. Organizing people to do more things together to clear the social-media-generated loneliness epidemic. Making new, interactive experiences people would pay to do, especially with friends. People ask for more things to look forward to. Not more things to type. AI is a new hands-free take on UX and UI.

slicerdicer1
0 replies
8h35m

great post, lots to think about

yieldcrv
0 replies
19h22m

Yeah one things that bothered me about artist complaints is the idea that anybody was ever going to pay them.

The people expressing themselves with image AI would never have gone to fiverr or upwork to begin with.

And only some of the existing clientele would change their behaviors too.

Additionally, I know artists that always wanted to express themselves differently than what they became known for, and actually create and sell AI generated work to their clientbase now.

nojvek
0 replies
20h25m

Well written argument.

The holy grail of AI is still in future. Where it can interact with software tools like we do. Competent AI Agents will be a huge productivity unlock.

anon-3988
0 replies
20h5m

This. Whenever AI come up, people are quick to think of automations completely making every jobs obsolete. But that is probably not going to happen. What is probably going to happen is that we are going to have 1 artist handling 10x more commissions because they can just use AI to do 90% of the work and just cleanup afterwards.

I am also using this to solve problems that are usually delegated to junior developers. I get faster results (that I would have to fix up anyways) for far less effort.

Animats
12 replies
21h41m

"Unlike the CPU cloud, which became an oligopoly, new entrants building dedicated AI clouds continue to flood the market. Without a monopoly or oligopoly, high fixed cost + low marginal cost businesses almost always see prices competed down to marginal cost (e.g., airlines)."

So why aren't there more entrants in the CPU cloud area? The technology is a commodity. Google and Amazon don't make CPUs.

wmf
4 replies
21h34m

The secret sauce in the cloud is not hardware but control plane, networking, and storage software.

mcast
1 replies
18h30m

And IP space.

wmf
0 replies
15h56m

The clouds are buying IPs and there's nothing stopping you from doing the same.

falcor84
1 replies
19h40m

And battle-tested SREs

ukuina
0 replies
16h18m

Battle-scarred*

mike_d
4 replies
21h29m

So why aren't there more entrants in the CPU cloud area?

Because the market is saturated with players.

AWS, Azure, GCP, Alibaba, IBM Cloud, Digital Ocean, Tencent, Oracle Cloud, Huawei Cloud, that Dell/VMware thing, Linode/Akamai, HP, Scaleway, Vultr, GoDaddy, OVH, Hetzner, etc.

Animats
3 replies
21h8m

So are margins low?

galeaspablo
2 replies
19h25m

Margins are high. 30-80%

Source: I run a cloud company and have plenty of friends in the space.

kortilla
1 replies
17h57m

Software engineers are shockingly dumb when it comes to infra costs and will quickly push the technology arm of a company to jam everything in the cloud because it’s more convenient for them.

It’s not shocking at all that margins are that high when a team pushes to pay AWS $40k a month for a static workload that could run on two racks of servers.

galeaspablo
0 replies
6h28m

“Dumb” could be reworded ;)

I would say “irrational when it comes to costs”. Not all developers ask questions such as:

Does paying 10K for convenience save me and my team more than 10k worth of time? Does this vendor make it easy to migrate out?

Of course I’m biased, because I like it better when the answers favor us, cloud vendors. But there are no catch all answers; as always, it depends.

jamessinghal
0 replies
21h27m

Would the Graviton CPUs from Amazon and upcoming Axion from Google not count?

TeMPOraL
0 replies
20h30m

The technology is, but operations isn't. Anyone can start a CPU cloud. Fewer can run it reliably (there are plenty of those at regional level, though). Very few can do it on a global scale, and break through the mindset of Amazon, Google and Microsoft being the only options.

beejiu
8 replies
21h56m

It interests me that the $200-600 billion number seems to be all-derived from GPUs. Are LLMs/AIs totally dependent on GPUs? I read last week (https://news.ycombinator.com/item?id=40787349) that there is research ongoing to run LLMs on FPGAs at greater energy efficiency.

I'm reminded of Bitcoin/crpyto, which in its early history was all operated on GPUs. And, then, almost overnight, the whole thing was run on ASICs.

Is there an intrinsic reason something similar couldn't happen with LLMs? If so, the idea of a bubble seems even more concerning.

cma
2 replies
21h47m

Nvidia and AMD bought out the big FPGA makers.

jamessinghal
1 replies
21h24m

AMD bought Xilinx, but Intel recently spun off Altera.

cma
0 replies
19h7m

Opps, yeah was thinking of Intel's Altera buy, not Nvidia, which I guess is now undone.

cmcclellan
0 replies
15h21m

This is just a PowerPoint slide at this point.

wmf
0 replies
21h45m

These numbers are just the hole from GPUs that have already been bought/ordered. Today's GPUs will inevitably be replaced by something, whether it be better GPUs, NPUs/TPUs, ASICs, or FPGAs. As chips get cheaper in the future the hole will grow at a slower rate but it only grows.

pixl97
0 replies
20h56m

Is there an intrinsic reason something similar couldn't happen with LLMs?

Only if we can increase the efficiency of LLMs by 2-3 orders of magnitude, there are only some in lab examples of this and nothing really being publicly shown.

Even then the models are still going to require rather large amounts of memory, and any performance increases that could boost model efficiency would very likely increase performance on GPU hardware to the point we could get continuous learning models from multimodal input like video data and other sensors.

light_hue_1
0 replies
19h50m

There is a reason why we don't use ASICs and instead use GPUs.

While people may say something is a Transformer that's more of a general description. It's not a specific algorithm; there are countless transformers and people are making progress on finding new ones.

Bitcoin runs a specific algorithm that never changes. That's for an ASIC. AI/ML runs a large class of models. GPUs are already finely tuned for his case.

julianozen
5 replies
16h36m

ELI5, why are GPUs not a commodity piece of hardware that any sophisticated chip manufacturer can't also produce?

This is one of the first time in the tech industry where the value was fully reaped by the hardware itself and not by the differentiated software that ran on top of it

paulmendoza
1 replies
16h0m

Amazon has a some AI chips they created themselves. Same with Tesla. They are both behind Nvidia and probably won’t catch up BUT raw performance isn’t always the most important part. Often it’s the cost per compute unit and companies are quickly getting close to Nvidia.

julianozen
0 replies
2h13m

Can more less sophisticated chips perform as well as fewer more expensive chips?

alberth
1 replies
16h35m

Intel for a few decades didn’t do to shabby.

julianozen
0 replies
2h15m

Yes, they did have great run, but I think over the long run the OS they were tied to was more important

ineedaj0b
0 replies
16h31m

they are very small, very advanced, and production yields are poor. The equipment is also stupidly expensive and takes reams of smart people just to run.

Silicon is currently the most advanced tech humans have ever made and those GPUs are on the cutting edge of that

dvt
4 replies
21h53m

In reality, the road ahead is going to be a long one. It will have ups and downs. But almost certainly it will be worthwhile.

The biggest takeaway from this piece is the stark realism of this article (maybe a bit too bearish, imo) compared to the usual Sequoia VC-speak. Maybe FTX did teach them something, after all.

smeeth
2 replies
21h28m

I don’t think FTX is the right contrast here. This document is mostly about business realism: revenue, margins, etc.

VCs did get burned by speculative investing in the 2019-21 period but FTX wasn’t like the others. At the time of its collapse, FTX was profitable and had $1+ bn in revenue, its doom had nothing to do with product market fit, revenue, margins, etc.

Quibi might be a more relevant example of a learning opportunity.

dvt
1 replies
21h22m

I don’t think FTX is the right contrast here.

Comparing this article to the (now deleted) SBF profile is night and day.

smeeth
0 replies
19h9m

I know, my point is that I fail to see how the FTX collapse would lead them to a tone change.

Maybe FTX did teach them something

The new tone is all about business fundamentals and the FTX collapse had literally nothing to do with business fundamentals. If this is the lesson they learned they learned the wrong lesson.

mike_d
0 replies
21h33m

VCs in general hate core AI because it is dominated by large players that don't need VC money to be successful. If someone was taking Sequoia money to buy GPUs they'd be singing a completely different tune.

mupuff1234
3 replies
22h4m

I expect this will lead to a final surge in demand for NVDA chips

But other than FOMO why would someone buy better chips when they don't actually know what to do with their old ones?

alecco
2 replies
21h49m

H100s are in very high demand and usually running work 24/7. So much that the energy cost is a big factor. The B100 halves the energy costs, among many other things.

technotony
1 replies
21h45m

If they are in such high demand, then are they just being priced below cost? why else is the capex so much higher than the revenues? These things must depreciate over only 3-5 years (or less?)

alecco
0 replies
8h57m

No. Some people say H100s are priced at 1000% of cost and Nvidia could charge even more but then they would really push their large clients (Microsoft, Meta, Amazon) to build competing hardware. And even at the current price they are trying already.

sheeshkebab
2 replies
17h53m

The only thing AI needs to do to demonstrate its value is replacing jobs at scale. Until it happens, it’s all capex and opex bs and hobby projects.

dbish
1 replies
17h49m

Yes, and I think we're on the way to that happening in chunks of the economy, but it's not going to be overnight, there are still a number of improvements to make along the way. I am willing to bet my time working on it that we will be replacing many jobs in the next few years.

sheeshkebab
0 replies
17h37m

Maybe Musk will show to all how it’s done starting with robotaxis, however looking at current state I wouldn’t bet on it, at least not anytime in near future. Buying more gpus will definitely not be the thing that solves this.

igammarays
2 replies
16h6m

Maybe because the revenue isn't directly attributable to AI itself, but is realized in the cost savings and productivity improvements in already existing revenue streams? That's where AI has been useful to me. I can't put a number on how much AI has made me exactly, but it has certainly helped all aspects of my bootstrapped startup.

dmix
0 replies
12h43m

but it has certainly helped all aspects of my bootstrapped startup.

Well if there's value to you then how much did you pay for it and would it realistically cover operating cost once VC cash dries up? That's the only question.

alok-g
0 replies
12h50m

Any product should bring benefits to both the producer and the consumer.

For the case where a company is using their own AI for their own cost reduction and productivity improvements, they can keep doing that but not offer to another party.

If they offer to another party, and that party is having benefits (like you have said), the price should be such that a part of the consumer benefit is shared with the producer resulting in benefits for the producer.

The real challenge here is because of price wars, i.e., too much competition already with producers willing to take a hit on profitability in anticipation that they will be able to do so later after creating a moat above and beyond competitors. Or they think that it will strenghen their overall bigger offering by adding an otherwise lossy feature.

In a nutshell, even if there's a lot of value for the consumers, it must result in a win-win for a new product to be sustainable in the market.

openrisk
1 replies
21h51m

Those who remain level-headed through this moment have the chance to build extremely important companies.

But in which sector will these extemely important companies be active? Adtech? Knowledge management / productivity tools? Some completely new category?

What is an undeniable fact is the drastic commodization of the hardware / software stack for certain classes of algorithms. How is this technological development going to be absorbed and internalized by the economy feels still rather uncertain.

sumedh
0 replies
19h46m

But in which sector will these extemely important companies be active?

I dont think anyone knows the answer to that question.

mike_d
1 replies
21h39m

The calculations here seem to depend on a few false assumptions:

1. That all datacenter GPUs being purchased are feeding AI. You might be able to argue that some are or a lot are, but you don't know how many just looking at Nvidia sales numbers. I know of at least two projects deploying rows of cabinets in datacenters full of GPUs for non-AI workloads.

2. The assumption that pay-for-an-API is the only AI business model. What we now call "AI" has been driving Google's search and ad businesses for nearly a decade, sooo AI is already doing $300B/yr in revenue? There is no way for this guy to quantify how AI is solving problems that aren't SaaS.

David Chan, if you are reading this feel free to email me if you want a fact check for what will surely be the third installment in the series.

jerrygenser
0 replies
16h50m

Yes but Google hasn't needed gpus to power search. It's used cpu even for ML inference and training before deep learning.

artisin
1 replies
15h3m

LLMs are undeniably remarkable, but their wheels start to fall off once you go beyond the basics and a few party tricks. The cynical part of me thinks this tracks pretty well with our society's tendency to favor appearance over substance. Yet, if my burger order gets messed up, I don't fault the restaurant; however, if an LLM messes up my order, the same cannot be said. As a seasoned human, I feel confident saying that we humans love blaming other humans, whether it's justified or not.

So while I initially thought customer-facing roles would be front and center in the "AI revolution." Today, I tend to think they'll be bringing up the rear, with entertainment/smut applications at the forefront along with a few unexpected applications where LLMs operate behind the scenes.

bamboozled
0 replies
13h25m

Even smut seems to be having a pretty slow take off, I had a go of an AI porn generator for fun recently, it was nightmare fuel. I know it's "almost right and it will get better" but not being "there" yet just isn't good enough when it comes to accurately depicting penetration.

arisAlexis
1 replies
11h42m

The article doesn't say anything. First is says AI is meh for profit and it ends with AI is the most important tech ever and will generate tons of money. I think if it wasn't written in the sequoia blog it would have gotten very little attention.

demaga
0 replies
11h8m

It's all relative. The author does appreciate AI and its potential value. He simply argues that this value won't be as high as $600B.

timestap
0 replies
12h23m

Are there any case studies of companies/cloud vendors using non-Nvidia GPUs for inference at scale?

Assuming startups like Etched (with its recent massive funding) could shrink CapEx quite a bit (and make it not such a large revenue shortfall)

the__alchemist
0 replies
17h52m

About a week ago, [Angela Collier posted a video on this topic](https://www.youtube.com/watch?v=dKmAg4S2KeE) highlighting the "malicious optimism" of AI hype. She used comments by the Zoom CEO as a basis, but it generalizes.

surfingdino
0 replies
13h26m

Investment incineration

Just two words to describe all the idiocy of the current wave of AI offerings.

A huge amount of economic value is going to be created by AI. Company builders focused on delivering value to end users will be rewarded handsomely. We are living through what has the potential to be a generation-defining technology wave.

No. It's crap no matter how much money you throw at it. It will end in tears, because there is no standard, no operating system, no protocol, only a handful of APIs controlled by a couple of companies. They are not building networks, but hubs with a single point of failure--the API provider. The internet is such a world-changing force because it is built on top of TCP/IP, which allows the rest of the internet to survive even if a part of it goes down. When an AI API provider shuts down, all those bullshitters repackaging LLMs will be left holding the bag, or rather their investors will be. In a way, the coming AI bubble burst is going to be a self-fulfilling prophecy--AI will make its creators redundant.

But we need to make sure not to believe in the delusion that has now spread from Silicon Valley to the rest of the country, and indeed the world. That delusion says that we’re all going to get rich quick, because AGI is coming tomorrow, and we all need to stockpile the only valuable resource, which is GPUs.

No, the delusion is that Gen AI is good for anything. It is not.

Soon, the $600B question is going to be, "where's the money gone?"

sadhorse
0 replies
18h12m

I recall Marvin Minsky saying that 1 GigaFlops would suffice for doing most of what humans do. Current AI is addiction to more data, more compute but no smarts. At least they gave us cheap compute, soon the right people will figure out how to produce real AI, not this travesty.

neaanopri
0 replies
22h2m

This seems about as bearish as a VC is allowed to be. My takeaway is:

Sell! Sell! Sell now before it's too late!

nabla9
0 replies
19h46m

38 OECD countries have combined population 1.38 billion, GDP $49.6 trillion

$600 billion is $434 per person, $36 per month per person, 1.2% percent of GDP.

If 75% of the spending goes to increasing productivity, I could see it. Get rid of $450 billion in labor costs (12 - 15 million work years). Cut worked hours in call centers, customer service, many services, menial programming jobs, ...

But I don't see it happening fast enough to pay for current investments.

matchagaucho
0 replies
20h58m

There's a growing divide between inference GPUs and training GPUs.

Investors first need to ask what that ratio might look like in 10 years. 10-to-1? 100-to-1? Inference-to-Training

Assuming for each NVDA training GPU sold there are 100 open source / commodity GPUs doing inference, who owns and supplies those data centers and hardware?

mark_l_watson
0 replies
15h27m

Context: I have been paid to work as an AI practitioner since 2982, nothing special about me except I have worked with amazing people. I have lived through at least two “AI winters.”

The author of this blog makes a great argument that there is a risk of AI investments not paying off because if a revenue gap: The author argues that the gap between the revenue expectations implied by the AI infrastructure build-out and actual revenue growth in the AI ecosystem has increased from $200B to $600B. This is due to factors such as the subsiding of the GPU supply shortage, growing GPU stockpiles, and the dominance of OpenAI in AI revenue. The author also notes that the $125B hole in AI revenue has now become a $500B hole.

However, my experience with previous AI winters is not relevant here because now is the first time in history that there is a possibility of what we used to call “real AI” and now call AGI. No investor wants to miss out completely on the creation of near limitless wealth.

lqprag
0 replies
21h49m

As always, free analysis by VCs and investment banks is not necessarily for the reader's benefit.

So we have this bearish piece and the previous bearish Goldman Sachs piece. While I agree with their analysis in this case, there is a lingering doubt that some banks might just want to tank Nvidia a little in order to go long. Or something like that.

light_hue_1
0 replies
19h43m

This is not an AI or ML problem. This is an Nvidia, Google, Microsoft, Meta, Tesla, etc. problem.

Most AI startups aren't building massive data centers so they're unaffected. Most money isn't spent on compute in most startups. Only a few companies spend big.

It's obviously a terrible idea to invest massive amounts into compute when Nvidia's profit margins are so astronomical if you need ROI in the long term. The massive corporations won't get their money back for these investments; but they don't have to.

ksec
0 replies
2h8m

This article and most of these thesis assume one thing, you need to make a return of investment from AI while using OpenAI revenue as an anchor to measure it.

What if these AI investment were only to protect or strengthen their current business? AI in Windows, macOS, Adobe, iPhone, Facebook, Instagram may not bring in any additional revenue. But it add additional value to their current product line, making competition harder, further hardening their moat.

Nvidia or Jensen is also smart to play the national security card. Does the European want their model to be all US based. Are the answer culturally correct? Just like how every single country invested in their own Telecom or Internet infrastructure, if this pitch were even half as successful, do these numbers we are looking at even matter when it is spread out across G7 or G20?

While I believe we are still far, or at least 10+ years away from AGI, the current form of AI still has a lot of improvement incoming and are already bringing in real world benefits and value to a lot users. The adoption curve will accelerate once it is integrated into Windows, Office and Mac. So even if we are in a bubble, I still think we are very early in the curve before it burst.

joshuakarl
0 replies
15h2m

Data center GPUs are not only used for LLMs. Meta makes hundreds of billions and invests tens of billions on GPUs, using them directly in its core business, not just for cute chatbots. OpenAI is not the clear winner in revenue generation from "AI" if we define AI as deep learning models trained on GPUs.

jfghi
0 replies
22h6m

Reminds me of the gnomes from South Park.

barnabyjones
0 replies
15h36m

I think there is far too much focus on potential productivity gains, and not nearly enough on entertainment value, which still has a ways to go but much higher potential compared to serious problem solving, which may or may not be be feasible with these models. Nobody has really figured out yet a good way to integrate generative multimedia together in a way that makes a hit, but surely someone will in the next few years. Right now there are utterly half-assed apps like Linky making good money, and that's just midjourney and CAI glued together awkwardly. I don't know what a genuine hit product is going to look like, or if it'll even be an app, but the potential for generative multimedia is so much higher that what we're seeing now.

andsoitis
0 replies
17h9m

"Consider how much value you get from Netflix for $15.49/month or Spotify for $11.99. Long term, AI companies will need to deliver significant value for consumers to continue opening their wallets."

Timber-6539
0 replies
21h16m

The problem with AI is that it's very much a gimmick and consumers don't have much use for gimmicks. Certainly not when it works half the time and hallucinating the other half. All it takes is an NBER announcement to pop this mania.

Kon-Peki
0 replies
21h37m

Many of the winners haven't even been formed yet. And most of the losers have already lost, they just don't know it yet.

Ekaros
0 replies
20h48m

Has anyone asked will AI actually very soon be commodity tech? With too many players competing with each other driving prices to bottom? Is there actually meaningful value to extract, after you have spend money on hardware and power?

Modern web is full of examples of platforms that really don't make money...