Classifying all of the pdfs on the internet

I haven't downvoted you but it is presumably because of your hasty typing or lack of proofreading/research.

33TB (first google result from 5 years ago) not 33GB. Larger figures from more recently.

8TB - ~8,000GB - is more than 33GB.

I think Libgen is ~100TB, and the full Anna's Archive is near a PB.

They all probably contain lots of duplicates but...

https://annas-archive.se/datasets

(edit: why would someone downvote this, HN is becoming quite hostile lately)

Also, there are browser extensions that will automatically downvote and/or hide HN comments that use words like "lol," or start with "So..." or include any of a number of words that the user considers indicative of low-grade content.

It's being down voted because your number is really off. Libgen's corpus is 100+ TB

I upvoted this comment because, though the number is wrong, it proves the point. The fact that the correct number proves the point even more, is a reason _not_ to downvote the comment.

RTBF isn't about having your information wiped from the internet. Its a safe assumption any public information about you is completely out of your control as soon as its public.

RTBF is about getting companies to get rid of any trace of you so they cannot use that data, not removing all traces about you across the internet.

Also a neurodivergent person I feel very much discriminated against when a whole continent weaponizes the law to protect scam artists who weaponize their social skills to steal from people. It makes me feel unwelcome going to Europe and for all the handwriting about Europe’s poor economic performance it is yet another explanation of why Europe is falling behind — their wealth is being stolen by people who can’t be held accountable.

Correct me if I'm wrong, but I always took RTBF to mean you have the right to be forgotten by any specific service provider: that you can request they delete the data they have that relates to you, and that they forward the request to any subprocessors. That's fairly reasonable and doable, it is enforced by GDPR and a number of other wide-reaching laws already, and it is a relatively common practice nowadays to allow users to make such requests with certain guarantees.

It never meant that you have the right to ask "the Internet" as a whole to scrub you from all possible records, that's indeed ludicrous. And if someone took it to mean that and they were pushing for it, they were just confused, no serious law ever proposed that.

Once something is spread, it is there, forever.

Really depends on the content. Tons of websites are going down everyday, link rot is a real thing. Internet archive or people don't save nearly everything.

Something I should do more often is saving mhtml copies of webpages I find interesting.

They often aren't like you're describing, though. For example, pdfs with high res images embedded that are drafts of future book or pamphlets prints. These can be hundreds of Mbs for a single pdf with less than 100 pages, and are so common in marketing departments that it's hard to imagine that you could fit anywhere close to all the pdfs on 8TB.

I've been doing some work for an infrastructure company as well. They have a total of about 1 billion pages of PDF documents in their archives. If we assume even just 30 KB per page (which is quite low, all the PDFs I just randomly checked were higher, sometimes quite a bit so), that's already 30 TB of PDFs, just for that one company with 1B in annual sales.

I'm doing some work for a company that handles scanned documents (PDFs which are purely images) and they accumulate about 15 TB / year. Of course the actual amount of information is relatively small, just inflated by being scanned. Probably 80% of them were typed up, printed, and then scanned or faxed, and of course the first thing we do is OCR them to try to recover the original text and formatting...

Anna's archive has some 300M pdfs.

Living in Belgium, I first thought that it was about the TV/radio service. Never saw the acronym R.T.B.F.

No, the Safedocs dataset is unprocessed pdfs.

From the article:

Specifically, when Common Crawl gets to a pdf, it just stores the first megabyte of information and truncates the rest.

This is where SafeDocs or CC-MAIN-2021-31-PDF-UNTRUNCATED enters the picture. This corpus was originally created by the DARPA SafeDocs program and what it did was refetch all the different pdfs from a snapshot of Common Crawl to have untruncated versions of them.

No torrents at all in this data, all publicly available/open access. Mostly scientific pdfs, and a good portion of those are scans not just text. So the actual text amount is probably pretty low compared to the total. But still, a lot more than 8TB of raw data out there. I bet the total number of PDFs is close to a petabyte if not more.

Just wondering what do you collect?

I can't speak for the OP, but you can buy optical media of old out-of-print magazines scanned as PDFs.

I bought the entirety of Desert Magazine from 1937-1985. It arrived on something like 15 CD-ROMS.

I drag-and-dropped the entire collection into iBooks, and read them when I'm on the train.

(Yes, they're probably on archive.org for free, but this is far easier and more convenient, and I prefer to support publishers rather than undermine their efforts.)

I have >10TB of magazines I've collected so far, and I could probably source another 50TB if I had the time. I'm working on uploading them, but I've had too much on my plate lately: https://en.magazedia.wiki/

There is a significant issue with copyright, though. I'll remove anything with a valid DMCA, but 99.9% of the world's historical magazine issues are now in IP limbo as their ownership is probably unknown. Most of the other .1% aren't overly concerned as distribution is their goal and their main income is advertising, not sales.

I think that would be legally iffy for the stuff like collections of old magazines that were purchased on CD/DVD and such :/

You can apply statistical techniques to anything you want. Embeddings are just vectors of numbers which capture some meaning, so statistical analysis of them will work fine.

It doesn't take away the torrents, no?

In biomedical research or tangential fields, author order generally follows these guidelines:

First author(s): the individual(s) who organized and conducted the study. Typically there is only a single first author, but nowadays there are often two first authors. This is because the amount of research required to generate “high impact” publications simply can’t be done by a single person. Typically, the first author is a Ph.D. student or lab scientist.

Middle authors: Individuals that provide critical effort, help, feedback, or guidance for the study and publication of the research. Different fields/labs have varying stringencies for what is considered “middle authorship worthy”. In many labs, simply being present and helping with the research warrants authorship. In other labs, you need to contribute a lot of energy to the project to be included as an author.

Senior author(s): The primary investigators (PI’s) or lead researchers that run the lab that conducted and published the study. The senior authors are typically the ones that acquire funding and oversee all aspects of the published research. PI’s have varying degrees of hands-on management.

There is some variation in whether the central research question for a manuscript is developed by the first vs. the senior author, but usually it’s the senior author. Also, the first and senior authors typically write the manuscript and seek edits/feedback from middle authors. In other cases, there can be dedicated writers that write the manuscript, who sometimes do/don’t get middle authorship. A main takeaway is: the general outline I’ve provided above is not strictly adhered to.

I’ll take some liberty to apply this outline to this article at hand:

First Author: G. Newton (OP). The scientist who mostly likely conducted all of the data mining and analysis. He likely wrote the article as well.

Middle Author: A. Callahan. It seems like this author was a grad student at the time the article was written. She likely performed essential work for the paper’s publication. This could’ve been: helping with the analysis, data mining, or ideation.

Senior Author: M. Dumontier. A data science professor, now at Maastricht U. He’s a highly cited scientist!

Lastly… if you check out the acknowledgements, you can see three additional names. These people likely helped with setting up compute access, editing, or general ideation.

This is a cool manuscript! Hopefully this overview isn’t TMI and provides some insight into the biomedical/data science publication process.

Thanks! Yes, I'm sure using modern hardware and modern techniques would improve both computation time and results.

You don't want the footer or navigation in the output. Ideally you want the main content of the page, if it exists. How do you assign header level if they're only differentiated by CSS left-margin in a variety of units? How do you interpret documents that render properly but are hardly correct HTML?

hi! i used the average accuracy over the entire dataset made originally made by the llm