Just let anyone scrape it all for any reason. It’s science. Let it be free.
The OP tweet seems to be leaning pretty hard on the “AI bad” sentiment. If LLMs make academic knowledge more accessible to people that’s a good thing for the same reason what Aaron Swartz was doing was a good thing.
On the whole, maybe LLMs do make these subjects more accessible in a way that’s a net-positive, but there are a lot of monied interests that make positive, transparent design choices unlikely. The companies that create and tweak these generalized models want to make a return in the long run. Consequently, they have deliberately made their products speak in authoritative, neutral tones to make them seem more correct, unbiased and trustworthy to people.
The problem is that LLMs ‘hallucinate’ details as an unavoidable consequence of their design. People can tell untruths as well, but if a person lies or misspeaks about a scientific study, they can be called out on it. An LLM cannot be held accountable in the same way, as it’s essentially a complex statistical prediction algorithm. Non-savvy users can easily be fed misinfo straight from the tap, and bad actors can easily generate correct-sounding misinformation to deliberately try and sway others.
ChatGPT completely fabricating authors, titles, and even (fake) links to studies is a known problem. Far too often, unsuspecting users take its output at face value and believe it to be correct because it sounds correct. This is bad, and part of the issue is marketing these models as though they’re intelligent. They’re very good at generating plausible responses, but this should never be construed as them being good at generating correct ones.
Ok, but I would say that these concerns are all small potatoes compared to the potential for the general public gaining the ability to query a system with synthesized expert knowledge obtained from scraping all academically relevant documents. If you’re wondering about something and don’t know what you don’t know, or have any idea where to start looking to learn what you want to know, a LLM is an incredible resource even with caveats and limitations.
Of course, it would be better if it could also directly reference and provide the copyrighted/paywalled sources it draws its information from at runtime, in the interest of verifiably accurate information. Fortunately, local models are becoming increasingly powerful and lower barrier of entry to work with, so the legal barriers to such a thing existing might not be able to stop it for long in practice.
The phrase “synthesised expert knowledge” is the problem here, because apparently you don’t understand that this machine has no meaningful ability to synthesise anything. It has zero fidelity.
You’re not exposing people to expert knowledge, you’re exposing them to expert-sounding words that cannot be made accurate. Sometimes they’re right by accident, but that is not the same thing as accuracy.
You confused what the LLM is doing for synthesis, which is something loads of people will do, and this will just lend more undue credibility to its bullshit.
That would be good if they did that but that is not the intent of the org, the purpose of the tool, the expected or even available outcome.
It’s important to remember this data is not being scraped to make it available or presentable but to make a machine that echos human authography convincingly more convincingly.
On an extremely simplified level, it doesn’t want to answer 1+1=? with “2”, it wants to appear like a human confidently answering an arithmetic question, even if the exchange is “1+1=?” “yes, 2+3 does equal 9”
Obviously it can handle simple sums, this is an illustrative example
that is not the … available outcome.
It demonstrably is already though. Paste a document in, then ask questions about its contents; the answer will typically take what’s written there into account. Ask about something you know is in a Wikipedia article that would have been part of its training data, same deal. If you think it can’t do this sort of thing, you can just try it yourself.
Obviously it can handle simple sums, this is an illustrative example
I am well aware that LLMs can struggle especially with reasoning tasks, and have a bad habit of making up answers in some situations. That’s not the same as being unable to correlate and recall information, which is the relevant task here. Search engines also use machine learning technology and have been able to do that to some extent for years. But with a search engine, even if it’s smart enough to figure out what you wanted and give you the correct link, that’s useless if the content behind the link is only available to institutions that pay thousands a year for the privilege.
Think about these three things in terms of what information they contain and their capacity to convey it:
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A search engine
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Dataset of pirated contents from behind academic paywalls
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A LLM model file that has been trained on said pirated data
The latter two each have their pros and cons and would likely work better in combination with each other, but they both have an advantage over the search engine: they can tell you about the locked up data, and they can be used to combine the locked up data in novel ways.
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Aint jstor a private enterprise?
It’s a US “non-profit”. One that demands 19$ per article which they merely provide as aggregator, they don’t own shit.
Utterly absurd.
Non profit here merely means they are exemot from US income taxes so they are grifting even hardrr on us.
MIT is grifting in a similar but bigger manner.
Which means they’re adding profit margin to the otherwise zero marginal cost of said information good.
Yes… but it was MIT that pushed the feds to prosecute.
Never forge to name the proper perp.
Disgusting. And we subsidize their existence 🤡
MIT releases financials and endowment figures for 2024:
The Institute’s pooled investments returned 8.9 percent last year; endowment stands at $24.6 billion
and in due time, we’ll hack OpenAI and get the sources from the chat module…
I’ve seen a few glitches before that made ChatGPT just drop entire articles in varying languages.
Is OpenAI profitable now?
Is OpenAI open still?
No and no.
Wait, since when it had not been? Or are you telling me that vastly the fastest growing platform in history with multiple payment gates (subscriptions, pay per token, licensing etc.) was not profitable for some reason?
Not sure if you are joking but… it does not appear to be making anywhere near the amount of money that has been invested in it.
It costs a stupendous amount of money to develop the models, to train them, to rent out or just buy the hardware needed to do this, to pay for the electrical power to do this.
Not joking, I’m just underinformed
Now that I think of it, yeah, it makes absolute sense. It’s not a stable income OpenAI is based on, but rather the endless wagons of money from hyped up sponsors. Very much unsustainable.
It isn’t even close to making a profit. They are bleeding billions per year with no obvious path to breaking even, let alone profiting enough to justify their enormous valuation. It’s very much a bubble and I look forward to the day it pops.
Edit: if you want a lengthy read on the subject https://www.wheresyoured.at/oai-business/
Last time I heard no, they are burning money for training new models.
Running those datacenters is extremely expensive.
The cost is to the whole world, because they consume enormous amounts of energy and produce essentially nothing. Like bitcoin miners.
It’s following the Amazon monopolization model.
Estimates from earlier this year are that they spend $2.35 for every $1 they make.
Or are you telling me that vastly the fastest growing platform in history with multiple payment gates (subscriptions, pay per token, licensing etc.) was not profitable
Are you not aware that 99 times out of 100 if you see a tech company rapidly growing it’s completely unprofitable and not even attempting to be profitable yet? It’s called blitzscaling and is pretty clearly what openai is attempting. Like if you see a tech company quickly growing you should be assuming it’s unprofitable until proven otherwise not the opposite lol.
double standards are capitalism’s lifeblood
Find me any charitable, non-profit, or community organization that wouldn’t call the cops if someone was breaking into their networking closet to install data harvesting hardware.
why are you on here if you’re this much of a bootlicker? go pay for digital media like an idiot if you feel this way.
Remember what you learned in school: Working as a team to solve a test or problem is unacceptable!!! Unless you are a company town.
To paraphrase Nixon:
“When you’re a company, it’s not illegal.”
To paraphrase Trump:
“When you’re a company, they just let you do it.”
RIP AARON
Epstein his own life
All is legal in the eyes of capital.
The real golden rule
Who writes the laws? There’s your answer.
I’m curious why https://www.falconfinance.ae/ cares about this though.
The hell they are selling? https://www.falconfinance.ae/falcon-securities/
I did some digging. It’s a parody finance website that makes it seem like you can invest in falcons and make a blockchain (flockchain) with them. Dig a little further, go to the linked forum, and you’ll see it’s just a community of people shitposting (mostly).
Anything the rich and powerful do retroactively becomes okay
Can we be honest about this, please?
Aaron Swartz went into a secure networking closet and left a computer there to covertly pull data from the server over many days without permission from anyone, which is absolutely not the same thing as scraping public data from the internet.
He was a hero that didn’t deserve what happened, but it’s patently dishonest to ignore that he was effectively breaking and entering, plus installing a data harvesting device in the server room, which any organization in the world would rightfully identity as hostile behavior. Even your local library would call the cops if you tried to do that.
Wao, it’s not often we get to see someone posting a comment so full of shit while making sure to obscure many facts to see if it sticks.
“Can we be honest”? Apparently you cannot.
Can we be honest about this
Saying “can we be honest” isn’t a magic spell that transmutes your opinion to fact.
patently dishonest ignore that he was effectively breaking and entering, plus installing a data harvesting device in the server room, which any organization in the world would rightfully identity as a hostile.
We are in the right, so we don’t have to obscure facts.
