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Remember what you learned in school: Working as a team to solve a test or problem is unacceptable!!! Unless you are a company town.
All is legal in the eyes of capital.
The real golden rule
RIP AARON
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."
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).
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.
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
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.
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i agree, my problem is that it wont
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Rip Aaron
Yes.. but it was MIT that pushed the feds to prosecute.
Never forge to name the proper perp.
Disgusting. And we subsidize their existence 🤡
https://en.wikipedia.org/wiki/Carmen_Ortiz
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."
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
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I'm still blaming the MIT for that !
Anything the rich and powerful do retroactively becomes okay
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.
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.
thanks! it actually makes much sense.
welp guess I was wrong. so back to .edu scraping!
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.
Why don't you speak what you truly believe instead of copy-pasting the same gaslighting everywhere? We already made you, anyway.
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.
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.
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.
Another bootlicker spotted.
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this post was submitted on 26 Oct 2024
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