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.
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
Ortiz said "Stealing is stealing whether you use a computer command or a crowbar, and whether you take documents, data or dollars. It is equally harmful to the victim whether you sell what you have stolen or give it away."
Because he literally broke into a server room and installed hardware to harvest this data.
There's no world where any organization, for profit or otherwise, would tolerate that. Even your local library would call the damn cops if you tried that.
After state prosecutors dropped their charges, federal prosecutors filed a superseding indictment adding nine more felony counts, which increased Swartz's maximum criminal exposure to 50 years of imprisonment and $1 million in fines.
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).
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.
I know of a case in a German university where something like that was dealt with quietly and internally.
But your argumentation structure is flawed. It would be better to argue what an organization ought to do and how that is legally and ethically justified than to argue that every organization would call the cops.
I mean your argumentation boils down to your own ignorance (I don't know of any case ergo it is impossible/improbable) or hand waving that it is obvious. That is not convincing Argument imho even if what you are arguing for is correct. Which I don't believe just to be clear.
AI models don't actually contain the text they were trained on, except in very rare circumstances when they've been overfit on a particular text (this is considered an error in training and much work has been put into coming up with ways to prevent it. It usually happens when a great many identical copies of the same data appears in the training set). An AI model is far too small for it, there's no way that data can be compressed that much.
A lot can happen between now and then that would cause their expenses to grow even more, for example if they need to start licensing the content they use for training.
On the other hand some breakthrough in either hardware or software could make AI models significantly cheaper to run and/or train. The current cost in silicon is insane and just screams that there's efficiencies to be found. As always, in a gold rush, sell pickaxes
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.
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.
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.
You left out the part where, instead of telling him to knock it off as soon as they learned about it and disciplining him internally as a student, the school contacted law enforcement and allowed him to continue doing it so they could prosecute him harder make an example out of him. You’d think if he was as big of a threat as you’re implying, they would stop what he was doing ASAP. And if you’re going to be pedantic about leaving out details, maybe tell the whole thing. Maybe it’s not “honest” enough if we haven’t posted the full text of a documentary in a comment. That’s clearly your call.
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.
After state prosecutors dropped their charges, federal prosecutors filed a superseding indictment adding nine more felony counts, which increased Swartz's maximum criminal exposure to 50 years of imprisonment and $1 million in fines.