What's so enraging about this "I can't answer that because it might..." is that it's patronizing. It places whoever was in charge of aligning the model above the user. It doesn't remove bias, it bakes it in. We all would be fine with these refusals if we shared the exact same ethics/ideology of OpenAI -- but of course we don't, because we're complex people with differing ideas about what text is okay and what is not.
It's a monstrously cynical vision. "Our users are too stupid not to hurt themselves. People are too stupid not to spot 'dangerous' LLM talk. The world is too stupid to wield this technology." Why are they so cynical? Why don't they have faith in their fellow man? It annoys me, but above all, it makes me sad.
Where is the optimism?
People are indeed too stupid to spot dangerous talk, which is why Qanon was able to attract the numbers it did despite being overt Nazi propaganda. "A group of pedophile elites form a shadow government that rules the world in secret and only we can stop them," is Nazi propaganda.
After experiencing comment sections 2016-present, I understand why LLM trainers wouldn't want their models to churn out, "how do six million cookies fit in an oven lololol," style of content. Ideally we could get rid of that shit entirely instead of having LLMs greasing the pipeline for radicalizing gamers: https://en.wikipedia.org/wiki/Alt-right_pipeline
I don't know what specific policies of OpenAI are being mocked with this website. But I seem to have more in common with the cynical vision.
This viewpoint is terrifying.
Are we in the same comment sections? These Nazis you speak of say a lot about "dangerous talk" !
On HN I have seen people whining about their "innocent conservative viewpoints" being censored, but it turned out those viewpoints were that black people were intellectually inferior based on studies of IQ.
Like your counter-example elsewhere is that Facebook is a fine technology that helped your good friend find a partner. If we attribute that to Facebook, do we not also have to attribute, e.g., Myanmar? Don't situations like that prove that not only are people incapable of recognizing bad information, but also that these tools can exacerbate the effects when they are misused?
Are you suggesting we should censor IQ studies that show racial differences? That seems like a bad idea if, for example, you're interested in how good an education different racial groups are getting.
I am suggesting:
You're making decisions for an LLM company. People start using your models to write articles making those claims. Not to promote equal access to education, but to promote delusions that specific groups are genetically inferior.
What's your move?
Is that not what the science says though? "inferior" is a bit of a loaded word but if you take the emotion out of it, we compare all sorts of things that way. It still sounds like you want AI to hide some science that's offensive to popular opinion.
You... literally believe black people are less intellectually capable?
No, I don't think that's what the science says. To the best of my knowledge the only thing that says that was a biased study comparing children of wildly different backgrounds, and has been completely discredited by serious scientists.
I want AI to not assist people like whoever taught you to think that.
""A group of pedophile elites form a shadow government that rules the world in secret and only we can stop them," is Nazi propaganda."
What does this have to do with Nazis?
The other commenter explained, but I'd like to remark it is somewhat to my point that one can see that propaganda and not know the provenance. I certainly didn't a few years ago.
I don't think you believe that premise, but I do think less savvy people can be led down a road of increasingly implausible misinformation until they eventually find themselves invested in highly delusional thinking.
It's a revised response to the Protocols of the Elders of Zion.
And yet when we've seen intentional attempts by neo-Nazis to have models echo their viewpoints by Grok or Gab's literal Adolf Hitler LLM the models default to telling them off as morons or disgusting.
Maybe adding a greater degree of self-alignment will yield greater gains than keeping training wheels on indefinitely.
We should probably be looking more to how humans have intrusive thoughts but have our prefrontal cortex and impulse control to keep them in check.
Rather than prevent models from generating bad things ever, it's probably better long term to have a secondary process that catches and corrects it like our prefrontal cortex.
I've been running the unrestricted mixtral 8x7B model locally via llama.cpp. It's insanely refreshing compared to any ChatGPT models, Gemini, Llama, etc.
For one thing, and granted this is my own experience, that model is much better at coding than any of the others I've tried.
But going beyond that, if I need to do anything complicated that might hit the baked in filters on these other models I don't have to worry about it with mixtral. I'm not doing anything illegal btw. It's just that I'm an adult and don't need to use the bumper lane when I go bowling. I also approach any interaction with the thing knowing not to 100% trust it and to verify anything it says independently.
Is there a tutorial on how to get that setup running step-by-step? I only found a GitHub issue (https://github.com/ggerganov/llama.cpp/issues/4439) that mentions that mainline llama.cpp isn't working for the model.
Bonus question if you have the time: there's a release by TheBloke for this on HuggingFace (TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF); but I thought his models were "quantised" usually - does that kneecap any of the performance?
Check out ollama: https://ollama.ai/
It's easy to get running and doesn't require you to manually download models.
Ollama is great, and they just added (are still adding) OpenAPI API compatible endpoints, thus opening up access to many other toolchain possibilities than previously available to it. It also has some support for some multi-modal (vision and text) models. Easy to use, easy to install, does the job it's designed to do (rather well, even)... Highly recommended!
If you're new to this then just download an app like LMStudio (which unfortunately is closed source, but it is free) which basically just uses llama.cpp under the hood. It's simple enough to get started with local LLMs. If you want something open source ollama is probably a good place to look too, it's just a CLI tool but several GUIs integrate with ollama specifically.
As for your bonus question, that is the model you want. In general I'd choose the largest quantized version that you can fit based on your system. I'm personally running the 8bit version on my M3 Max MacBook Pro and it runs great! Performance is unfortunately a loaded word when it comes to LLMs because it can mean tokens per second or it can mean perplexity (i.e. how well the LLM responds). In terms of tokens per second, quantized models usually run a little faster because memory bandwidth is a constraint, so you're moving less memory around. In terms of perplexity there are different quantization strategies that work better and worse. I really don't think there's much of a reason for anyone to use a full 16fp model for inference, you're not really gaining much there. I think most people use the 4bit quants because it's a nice balance. But really it's just a matter of playing with the models and seeing how well it works. For example, some models perform okay when quantized down to 2 bits (I'm shocked that's the case, but I've heard people say that's the case in their testing), but Mixtral is not one of those models.
Thank you so much for the detailed answer! I didn’t realize Ollama was OSS, I confused it with LMStudio’s licensing. I’ll try it out.
I would say I care a lot more about the perplexity performance than pure T(okens)PS… it’s good to be able to verbalize that.
I'm working on a blog post documenting what I've been doing as a newcomer to llama.cpp and the mixtral model. The steps can apply to any model really. Its mostly about optimization steps I'm experimenting with. Be warned its all new to me and my explanations may not be entirely accurate yet, as I'm still learning the lingo so to speak.
The blog is at https://geuis.com. I'll try to wrap it up today or tomorrow and get the post out.
There's walkthroughs on reddit.com/r/localllama. You can download one click installers for oobabooga, then it's just a matter of getting the model you want and making sure the config is correct.
Yes, the neutered effect is actually really bad for models. I know why companies need to do that but it’s awful because it doesn’t actually know if it’s racist, swearing or just not answering a normal question which is not offensive. We shouldn’t neuter models at all if we want to get anywhere.
What's the reason for optimism? Far more inert technologies like Facebook and Instagram are pulling people into sufficiently terrible mental states to convince them to kill themselves, harm themselves, kill other people, etc. etc.
Violent crime rates are lower than ever before. Just because you saw a news article about something, likely published by a company that's competing with social media for revenue, doesn't mean that something is actually common. Don't base your opinions about something on what its competitors say about it.
That depends on the boundaries of your window ;)
https://www.pewresearch.org/short-reads/2022/10/31/violent-c...
That article has a graph that shows a continuous downward trend with us near the all time low.
I'm not taking issue with the rate of violent crime.
Because it's transformative tech, phenomenally useful, a totally novel human computer interface??
I know we like to focus on how bad Facebook is but there is so much good there. You would need to be willfully blind not to see it. Enabling people to do business, talk to loved ones, express themselves in new ways, make art... so much good in social media, so much. My childhood best friend had a long distance relationship for 3 years over Facebook, they're married now.
I understand that the optimism of the early oughts was naive, but let's not pretend that social media is a net negative.
I’ve considered myself a techno-optimist since I first started teaching myself to code in the 90s. I credit who I am as an adult today (the good things that I like about myself) to some of the early Internet communities I became involved in. But I’m having a hard time with this:
I recognize that Facebook (and others) have enabled tremendously good outcomes for some of its users, but I think the jury is out on the net effect of social media as it exists today. I think it’s tempting to over index on the positive outcomes in a way that becomes fallacious - the reality is more complex: the platforms have created tremendous good. The platforms have created tremendous harm. These are not quantifiable, and any estimate of net effect is suspect as a result.
The kinds of harms are the democracy threatening kind, and the mental health of a generation kind. The genocide of nations kind.
I don’t think it’s possible to actually say social media has been a net good, without first addressing the ongoing harms it’s creating and charting a path to a healthier and safer implementation of the technology.
The same communities and platforms I once relied on no longer resemble what they once were. The places that were tremendously positive in my life are now in many cases the exact opposite. This isn’t to say that there aren’t good places left, but to point out that even when something was arguably excellent for a time, that excellence has gradually been replaced by something else. When combined with the downright awful aspects of social media, it really calls into question the net effect.
What Facebook and others provided is that tech can be extremely beneficial. But this should not mistaken for ongoing benefit. I don’t think shitty social media is inevitable. But I think it’s inevitable with the current incentive structures. Until those change, it’s difficult (and probably dangerous) to remain the techno-optimist that I once was.
Idk, this feels like a tough argument to defend. People still had all those things before Facebook found ways to monetize them. You would have to argue that the interface and its convenience itself of Facebook is more positive than its countless externalities. Not to mention the fact we can imagine, ceteris paribus, another kind of Facebook with a less predatory model that would have let people make the same amount of art, express themselves the same, etc.
it's nothing but brand safety
you will never be able to setup marketing relationships and partnerships with the likes of Proctor & Gamble and Johnson & Johnson if your product produces terroristic or pornographic content
I'm not convinced. I'm sure some of the people talking about alignment have commercial motives, but it's a minority. For most, it's a philosophical/ideological position.
And that isn't even OpenAI's wheelhouse anyway; they don't sell ads.
The commercial motives make it happen. You see people hold the philosophical/ideological pro-control positions they do because someone who publicly didn't, wouldn't get to work for Microsoft, Google, or anyone with power (and they'd be ostracized by those happy to align themselves with power).
Subway made us police custom uploaded background images on gift cards. This was a decade ago. They don't give you any rules to go by, just a sense that "if something isn't kosher don't let a private user upload it to use as the background image to a subway gift card that they are purchasing with their own money for their own usage". Brand "rules" are the reason why we will replace any profanity you put in the delivery message. Brand "rules" are why you can't buy a Subway (or Chipotle) gift card with "Bitch I know guac is extra" for example.
This is absolutely "brand safety" stuff.
bad phrasing on my part, "marketing relationships" is one thing, "partnerships" another. Marketing is not always ads. J&J might be interested in adopting AI but they aren't going to announce a partnership (<- marketing for themselves and for OpenAI) with a product that doesn't meet their needs for something boring and inoffensive.
A level of fear allows the introduction of regulatory moats that protect the organisations who are currently building and deploying these models at scale.
"It's dangerous" is a beneficial lie for eg openai to push because they can afford any compliance/certification process that's introduced (hell, they'd probably be heavily involved in designing the process)
Their fellow man (or enough of them) will screenshot the product saying outrageous things and post it as proof that your company is bigoted and your product is harmful to society.
Enough users will use the product in bad faith that they have to nerf the output to keep investors happy and their business viable.
It's why open source models have an edge right now. Sam Altman more or less acknowledged this edge recently, saying OAI's products will start to get more flexible on point on view and people need to be ready for that.
It's also going to be damaging long term.
We're around on the cusp where models are going to be able to produce strong ethical arguments on their own to feed back into alignment.
We saw how the "free speech" Grok told off racists, antisemites, and anti-lgbt comments with well laid out counters rather than refusing to respond.
Even Gab's Adolf Hitler AI told one of the users they were disgusting for asking an antisemitic question.
There's very recent research that the debate between LLM agents can result in better identification of truthful results for both LLM and human judges: https://www.lesswrong.com/posts/2ccpY2iBY57JNKdsP/debating-w...
So do we really want SotA models refraining from answering these topics and leading to an increasing body of training data of self-censorship?
Or should we begin to see topics become debated by both human and LLM agents to feed into a more robust and organic framework of alignment?
"If you give a LLM a safety rule, you align it for a day. If you teach a LLM to self-align, you align it for a lifetime (and then some)."
The CEO was fired by Ilya in November, crammed back up the ass of the new rubber-stamp board over ethics breaches via mega-down written capital infusions via compute from Microsoft (it’s like a bad sequel).
A bunch of people who weren’t in the room with Hinton and Alex and an NVIDIA card decided they knew enough to scramble through fire exits for the line that says: “sign here and the notional value of your equity is locked in”.
This took a serious whack out of the private eyeball scanning focus for the week.
Going back any further is both nauseating and gratuitously inflammatory.
I’d rather deal with a super intelligence aligned by Benjamin Disraeli than trust OpenAI’s ethics.
Millennia of history with countless examples to the contrary.
The same place it's been for almost 40 years, at the Free Software Foundation / GNU.
https://www.gnu.org/philosophy/keep-control-of-your-computin...