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Extracting concepts from GPT-4

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Re: Extracting concepts from GPT-4

#151
post #149
post #148

Earlier quoted context omitted.

What, you aren’t allowed to own kitchen knives? Or Google search somehow doesn’t return the chemical processes to make Sarin? Come on now.

> What, you aren’t allowed to own kitchen knives? You're not allowed to be in possession of a knife in public without a good reason. https://www.gov.uk/buying-carrying-knives You may think the UK government is nuts (I do, I left due to an unrelated law), but it is what it is. > Or Google search somehow doesn’t return the chemical processes to make Sarin? You're still missing the point of everything I've said if you t…

Same as you’re not allowed to commit eg election or postal fraud using LLMs. Are you allowed to carry a hammer? You can use that to kill people. You can also mow them down with a car, push them in front of a train with your bare hands, poison them with otherwise benign household chemicals and so on. It’s the applications that should be regulated, not the underlying tech

Re: Extracting concepts from GPT-4

#153
post #123

Earlier quoted context omitted.

> I'm curious what those things are. > At least to me, it isn't obvious that LLMs solve any of their many applications from the past year "very well". I worry about failures (hallucinations, misinterpretation of prompts, regurgitation of incorrect facts, violation of copyright, and more) That’s a list of things that gets clicks in the popular press. Some solutions I love: Recording a video and creating a transcript f…

> That’s a list of things that gets clicks in the popular press. Are you saying they're nonissues in practice? I agree that most of those points have shown up in the news, but they're also things that I have personally observed when interacting with LLMs. Of your (and sibling commenters') cited use cases, I see a number of scenarios where AI is used to perform a quick first pass, and a human then refines that output…

> This is one of those cases where I would like to better understand the false negatives. If a human reviews the output, then okay, false positives are easy enough to override. But how bad is a false negative? Is it just unnecessary expenses to the company, or does it expose them to liability?

In the companies I know about, these invoices requesting overpayment just got paid. So, worst case, it’s the same. But best case there is way way way more money to save than the cost of the service.

Re: Extracting concepts from GPT-4

#154
post #123

Earlier quoted context omitted.

> I'm curious what those things are. > At least to me, it isn't obvious that LLMs solve any of their many applications from the past year "very well". I worry about failures (hallucinations, misinterpretation of prompts, regurgitation of incorrect facts, violation of copyright, and more) That’s a list of things that gets clicks in the popular press. Some solutions I love: Recording a video and creating a transcript f…

> That’s a list of things that gets clicks in the popular press. Are you saying they're nonissues in practice? I agree that most of those points have shown up in the news, but they're also things that I have personally observed when interacting with LLMs. Of your (and sibling commenters') cited use cases, I see a number of scenarios where AI is used to perform a quick first pass, and a human then refines that output…

> This is useful in itself, but surely you too can see the potential for abuse? (This is literally putting words in someone else's mouth.)

If I was a famous actor, I would demand it. I don’t want people hearing different voices for different movies. I want them to hear my voice. And I’d want it to be authentic. Seeing lips move to the wrong words does not help make a connection.

As for abuse, sure. Not sure anything has had worse abuse than database technology. There should definitely be an avenue for the government to shutdown any database instance anywhere (like California is doing with AI). I would have shutdown data broker databases long ago.

Re: Extracting concepts from GPT-4

#155
After anthropic's recent article, this seems almost like making excuses for not having published similarly meaningful contributions.

I see a lot of "interpretability is hard" and "we're working on it" in this article but no impact as of yet.

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