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Yann LeCun on GPT-3
211–220 of 253 posts
Re: Yann LeCun on GPT-3
#212Reading this is really interesting: > GPT-3 doesn't have any knowledge of how the world actually works. I think this is a philosophical question. There is a view that, basically, there is no such thing as knowledge, just language (or, at least, there is no distinction between knowledge and language). In this view, all there really is is language, which is mostly composed of metaphors and, ultimately, metaphors only r…
If GPT-3 has a consistent position on anything, it's only because the corpus it was trained on was consistent about it. So, for example, it will reliably autocomplete Jabberwocky because there are a lot of copies of this poem in the corpus and they are all the same. If there were two versions of this poem that started the same way, it would pick between the variations in the corpus randomly. In other cases it might c…
I agree with you in that I would make a strong distinction between what a model like GPT-3 does and whatever it is that humans do.
But I do think you're missing the point just a bit. When we speak and think, we use all kinds of metaphors that express judgements about the world, usually without realizing it. In other words, the way we use language encodes concepts in a deep way.
To borrow an example from George Lakoff, we, in English, use war-metaphors to talk about arguments. Of arguments and of wars you can say things like "he's marshalling his forces," "they're ceding their territory," or "she's girding her defenses". In fact, almost anything you can say about a war you can also say about an argument. In American politics, with regard to partisan squabbling and the filibuster, we talk about "the nuclear option". The fact that these metaphors make sense to us indicates a judgement, something like "arguments are like wars". That judgement shows up in billions of lines of English scraped from the internet and can be fed into a model, allowing GPT-3 to "make that connection" via purely statistical methods.
Yes, this is a bit like asking "what a library believes". But a lot of these metaphors show up in our languages and, in a way, they express judgements, which is something akin to a belief. Does that mean a library has beliefs? Is this all knowledge is? I wouldn't go that far. But the argument is an interesting one and worth raising.
Re: Yann LeCun on GPT-3
#213I think I disagree about the lack of quality as part of a "dialog system". The examples given in that piece don't show any priming (e.g. the one calling for suicide...). I would definitely not use such a model in a fully automated manner, but the outputs are better than that of most humans in many cases, and could support a human-in-the-loop system.
Here is an example I ran that was not cherry picked (I ran only 2 prompts like this, both were equally good).
Think about how many people you know who would respond as well? (I don't know about you, but I definitely feel like I'm at a bit of a cliffhanger at the end also!)
----- Prompt ------
Mike is a mediator and crisis counselor.
===
User: My dad is always getting sucked into conspiracy theories and it's getting worse. I'm worried since he recently bought a gun. I'm not sure what's going on in his head. What I should do? What should I say?
Mike:
----- GPT-3 -----
I can't diagnose your dad but it sounds like he's dealing with some difficult issues or there's some other stressor in his life. When people feel under stress or are dealing with difficult issues it's common for them to look for meaning and solutions outside themselves. It's helpful to approach him in a non-judgmental, non-confrontational way to start a dialogue. It sounds like you're already trying to do that. I'd suggest that you let him know that you're concerned and you want to be helpful. Then ask him what he's going through and how you might help.
Listen to him without judging, interrupting or trying to solve things. Let him know you're there for him and that you care. You could also let him know that you're concerned about his gun and the consequences of using it.
If he's willing to talk, when he feels like it, he might feel relieved to have someone to talk to.
If he's not willing
Re: Yann LeCun on GPT-3
#214Earlier quoted context omitted.
His next paragraph claims that Nabla "debunks" the idea that "large language models" can be used in healthcare. That's not just "some people have unrealistic expectations" it's "this tool, when when more advanced and find tuned, will never be appropriate to use in a very broad class of use cases". He also says "GPT-3 has no knowledge of how the world works", which is clearly an overstatement meant to clear up hype, b…
>For example, GPT-3 knows more trivia than I do. no it doesn't, GPT-3 is a very sophisticated parrot. it doesn't know any trivia, it knows how to put the most likely string of characters next to the one it just saw, it doesn't matter what the text represents. That's the difference between you and the model. It's basically the Chinese room. You can make an analog GPT-3 by asking a question, recording your answer, hand…
AlphaGo doesn't know anything about the game of go. It "just" manipulates symbols, runs instructions on its CPUs and GPUs, illuminates pixels on the screen for a human to see.
It just also "happens" to be the case that if you interpret those pixels as go moves and play those moves against the world champion human go player then eventually that human will hold a press conference announcing to the world that AlphaGo has won the match.
Re: Yann LeCun on GPT-3
#215Yann is starting to sound like his good buddy Gary Marcus
Re: Yann LeCun on GPT-3
#216Earlier quoted context omitted.
>For example, GPT-3 knows more trivia than I do. no it doesn't, GPT-3 is a very sophisticated parrot. it doesn't know any trivia, it knows how to put the most likely string of characters next to the one it just saw, it doesn't matter what the text represents. That's the difference between you and the model. It's basically the Chinese room. You can make an analog GPT-3 by asking a question, recording your answer, hand…
AlphaGo doesn't know anything about the game of go. It "just" manipulates symbols, runs instructions on its CPUs and GPUs, illuminates pixels on the screen for a human to see. It just also "happens" to be the case that if you interpret those pixels as go moves and play those moves against the world champion human go player then eventually that human will hold a press conference announcing to the world that AlphaGo ha…
Yes that is entirely true, but the world of Go is very small and unambiguous in terms of goals, rules and so on. A little less than chess, but it's still a game with a well structured world and simple rules. AlphaGo understands as little about Go as Stockfish does about Chess or your TI-83 understands about maths. That they're good at it has almost nothing to do with (generalised) intelligence, and it's no coincidence that the performance of RL say, in games is insanely better than it is when applied to real-world, open-ended problems.
Deep Mind made a 'superhuman' Breakout bot, but if you messed with the panel at the bottom it sucked. It hadn't learned what the panel is or what the game is about, it had just learned to rearrange pixels. You can get away with this in one version of Breakout, but in the real world it's brittle and useless
Re: Yann LeCun on GPT-3
#217Earlier quoted context omitted.
His next paragraph claims that Nabla "debunks" the idea that "large language models" can be used in healthcare. That's not just "some people have unrealistic expectations" it's "this tool, when when more advanced and find tuned, will never be appropriate to use in a very broad class of use cases". He also says "GPT-3 has no knowledge of how the world works", which is clearly an overstatement meant to clear up hype, b…
>For example, GPT-3 knows more trivia than I do. no it doesn't, GPT-3 is a very sophisticated parrot. it doesn't know any trivia, it knows how to put the most likely string of characters next to the one it just saw, it doesn't matter what the text represents. That's the difference between you and the model. It's basically the Chinese room. You can make an analog GPT-3 by asking a question, recording your answer, hand…
Ok, fine. It doesn't "know" any trivia. It'll still crush me in a trivia contest:
"Q: Who was president of the United States in 1801? A: Thomas Jefferson was president of the United States in 1801.
Q: What city is in the northwest corner of Ohio? A: Toledo is in the northwest corner of Ohio.
Q: What highway do you take to get to North Lake Tahoe from Oakland? A: Highway 80 is the highway you take to get to North Lake Tahoe from Oakland.
Q: What are Darius's abilities in League of Legends? A: Darius's abilities in League of Legends are: Apprehend, Decimate, Noxian Guillotine, Crippling Strike, Apprehend [sic], and Hemorrhage.
Q: Who did Capablanca defeat to become world chess champion? A: Capablanca defeated Lasker to become world chess champion."
Of those 5 questions, I could answer #1 after deploying a mnemonic and some math, and #2 if you gave me multiple choice of the top 5 cities in Ohio, and I would miss the rest.
Re: Yann LeCun on GPT-3
#218Earlier quoted context omitted.
> GPT-3 doesn't have any knowledge of how the world actually works. It only appears to have some level of background knowledge, to the extent that this knowledge is present in the statistics of text. But this knowledge is very shallow and disconnected from the underlying reality. Without excessive effort, humans don't have any knowledge of how the world actually works. They only appear to have some level of backgroun…
This is just not true. For example, all humans have the notion of object permanence, developed by about six months of life. Object permanence is the notion that things don't go away just because you can't see them. ML systems need to be specifically trained to have object permanence, and GPT-3 almost certainly does not possess it. Like, I get that it's hip to booster ML and GPT-3, and all of the stuff humans can do s…
Object permanence isn't even defined in the stateless world of the GPT-3 API.
My comment was merely a jab at Yann's poor argument. I don't find humans to be trivial at all, but neither do I believe that they are infinitely complex.
The linked Nabla article is fair, albeit I would appreciate more technical details. It seems to be using the API in zero-shot fashion, which is not what one would do to get the most out of it.
Re: Yann LeCun on GPT-3
#219Reading this is really interesting: > GPT-3 doesn't have any knowledge of how the world actually works. I think this is a philosophical question. There is a view that, basically, there is no such thing as knowledge, just language (or, at least, there is no distinction between knowledge and language). In this view, all there really is is language, which is mostly composed of metaphors and, ultimately, metaphors only r…
Tell that to all the other animals on Earth. Do they not also have knowledge? Do you really think they encode their knowledge in language? Do you really think that humans are so special as to encode all their knowledge in language? Watch a movie. Listen to a song. Examine a piece of art. Feel sculpture. Play a guitar. Dance. There is a segment of the software community that is highly language centric/adept. But that…
>Tell that to all the other animals on Earth. Do they not also have knowledge? Do you really think they encode their knowledge in language?
Well, actually, yes, they do. Many animals have elaborate languages encompassing many concepts. Crows can explain to one another what a human looks like, for example.
Re: Yann LeCun on GPT-3
#220Really? I have been doing research on language models in medical diagnostics even before GPT-2, and found that when trained and applied in certain ways, language models (even much smaller than GPT-3!) are very good at diagnosis predictions, they can compete with much more complex symptom checkers at that.
Proof: Link to my paper (written back in 2019) and a bit less technical article. http://www.dialog-21.ru/media/4632/tarasovdplusetal-069.pdf https://www.linkedin.com/pulse/language-models-multi-purpose...
I applied for GPT-3 access on the next day since the application form was available, described my research and experience in detail, but there was no reply.
Now, they gave access to these people at nabla, and they just asked a bunch of stupid questions using top-k random sampling to generate answers and claimed that this debunks something. This study debunks nothing and proves nothing, it is stupid and only done to get some hype from GPT-3 popularity.
Ok, I am sorry for being rude, but I am really upset because I spent years working on this problem using whatever computational resources I could get and obtained some interesting results, and based on these I think that GPT-3 should be capable to do amazing things for diagnostics when used properly. Why won't OpenAI give access to a researcher who wants to do some serious but a bit mundane work, but gives it to people who use it to create hype?