7 ms·

I think we are past the "just predicting the next token" stage. GPT and it's various incarnations do exhibit behaviour that most people will describe as thinkin

by jatins 4y ago

I think we are past the "just predicting the next token" stage. GPT and it's various incarnations do exhibit behaviour that most people will describe as thinking

localplume 4y ago
thats because people anthropormophize literally anything, and many treat some animals as if they have the same intelligence as humans. GPT has always been just a charade that people mistake for intelligence. Its a glorified text prediction engine with some basic pattern matching.
- int_19h 4y ago
  "Descartes denied that animals had reason or intelligence. He argued that animals did not lack sensations or perceptions, but these could be explained mechanistically. Whereas humans had a soul, or mind, and were able to feel pain and anxiety, animals by virtue of not having a soul could not feel pain or anxiety. If animals showed signs of distress then this was to protect the body from damage, but the innate state needed for them to suffer was absent."
  - bun_at_work 4y ago
    Your comment brings up the challenge of defining intelligence and sentience, especially with these new LLMs shaking things up, even for HN commenters. It's tough to define these terms in a way that includes only humans and excludes other life forms or even LLMs. This might mean we either made up these concepts, or we're not alone in having these traits. Without a solid definition, how can we say LLMs aren't intelligent? If we make a definition that includes both us and LLMs, would we accept them as intelligent? And could we even exclude ourselves? We need clear definitions to talk about the intelligence and sentience of LLMs, AI, or any life forms. But finding those definitions is hard, and it might clash with our human ego. Discussing these terms without definitions feels like a waste of time. Still, your Descartes reference reminds us that our understanding of human experiences keeps changing, and our current definitions might not be spot-on. (this comment was cleaned up with GPT-4 :D)
- nuancebydefault 4y ago
  It's a charade, it mimics intelligence. Let's take it ine step further... Suppose it mimics it so well that it becomes indistinguishable for any human from being intelligent. Then still it would not be intelligent, one could argue. But in that case you could also argue that no person is intelligent. The point being, intelligence cannot be defined. And, just maybe, that is the case because intelligence is not a reality, just something we made up.
  - Jeff_Brown 4y ago
    Objective measures of intelligence are easy to come up with. The LSAT is one. (Not a great one -- GPT-4 passes it, after all -- but an objective one.) Consciousness, on the other hand, really might be an illusion.
deleted 4y ago
[deleted]
a_wild_dandan 4y ago
Yeah, calling AI a "token predictor" is like dismissing human cognition dumb "piles of electrical signal transmitters." We don't even understand our minds, let alone what constitutes any mind, be it alien or far simpler than ours. Simple != thoughtless. Different != thoughtless. Less capable != thoughtless. A human black box categorically dismissing all qualia or cognition from another remarkable black box feels so wildly arrogant and anthropocentric. Which, I suppose, is the most historically on-brand behavior for our species.
- WoodenChair 4y ago
  It might be a black box to you, but it’s not in the same way the human brain is to researchers. We essentially understand how LLMs work. No, we may not reason about individual weights. But in general it is assigning probabilities to different possible next tokens based on their occurrences in the training set and then choosing sometimes the most likely, sometimes a random one, and often one based on additional training from human input (e.g. instruct). It’s not using its neurons to do fundamental logic as the earlier posts in the thread point out. Stephen Wolfram explains this in simple terms.[0] 0: https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/ https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-...
  - TchoBeer 4y ago
    >based on their occurrences in the training set the words "based on" are doing a lot of work here. No, we don't know what sort of stuff it learns from its training data nor do we know what sorts of reasoning it does, and the link you sent doesn't disagree.
    - WoodenChair 4y ago
      We know that the relative location of the tokens in the training data influences the relative locations of the predicted tokens. Yes the specifics of any given related tokens are a black box because we're not going to go analyze billions of weights for every token we're interested in. But it's a statistical model, not a logic model.
thomastjeffery 4y ago
Just because GPT exhibits a behavior does not mean it performs that behavior. You are using those weasel words for a very good reason! Language is a symbolic representation of behavior. GPT takes a corpus of example text, tokenizes it, and models the tokens. The model isn't based on any rules: it's entirely implicit. There are no subjects and no logic involved. Any "understanding" that GPT exhibits was present in the text itself, not GPT's model of that text. The reason GPT can find text that "makes sense", instead of text that "didn't make sense", is that GPT's model is a close match for grammar. When people wrote the text in GPT's corpus, they correctly organized "stuff that makes sense" into a string of letters. The person used grammar, symbols, and familiar phrases to model ideas into text. GPT used nothing but the text itself to model the text. GPT organized all the patterns that were present in the corpus text, without ever knowing why those patterns were used.
- Jeff_Brown 4y ago
  > GPT used nothing but the text itself to model the text. I used nothing but my sensory input to model the world, and yet I have a model of the world, not (just) of sensory input. There is an interesting question, though, of whether information without experience is enough to generate understanding. I doubt it.
  - thomastjeffery 4y ago
    Not true. You used evolution, too. The structure of your brain growth is the result of complex DNA instructions that have been mutated and those mutations filtered over billions of iterations of competition. There are some patterns of thought that are inherent to that structure, and not the result of your own lived experience. For example, you would probably dislike pain with similar responses to your original pain experience; and also similar to my lived pain experiences. Surely, there are some foundational patterns that define our interactions with language.
  - dTal 4y ago
    In what sense is your "experience" (mediated through your senses) more valid than a language model's "experience" of being fed tokens? Token input is just a type of sense, surely?

by jatins 4y ago

I think we are past the "just predicting the next token" stage. GPT and it's various incarnations do exhibit behaviour that most people will describe as thinking

localplume 4y ago

thats because people anthropormophize literally anything, and many treat some animals as if they have the same intelligence as humans. GPT has always been just a charade that people mistake for intelligence. Its a glorified text prediction engine with some basic pattern matching.

int_19h 4y ago
"Descartes denied that animals had reason or intelligence. He argued that animals did not lack sensations or perceptions, but these could be explained mechanistically. Whereas humans had a soul, or mind, and were able to feel pain and anxiety, animals by virtue of not having a soul could not feel pain or anxiety. If animals showed signs of distress then this was to protect the body from damage, but the innate state needed for them to suffer was absent."
- bun_at_work 4y ago
  Your comment brings up the challenge of defining intelligence and sentience, especially with these new LLMs shaking things up, even for HN commenters. It's tough to define these terms in a way that includes only humans and excludes other life forms or even LLMs. This might mean we either made up these concepts, or we're not alone in having these traits. Without a solid definition, how can we say LLMs aren't intelligent? If we make a definition that includes both us and LLMs, would we accept them as intelligent? And could we even exclude ourselves? We need clear definitions to talk about the intelligence and sentience of LLMs, AI, or any life forms. But finding those definitions is hard, and it might clash with our human ego. Discussing these terms without definitions feels like a waste of time. Still, your Descartes reference reminds us that our understanding of human experiences keeps changing, and our current definitions might not be spot-on. (this comment was cleaned up with GPT-4 :D)
nuancebydefault 4y ago
It's a charade, it mimics intelligence. Let's take it ine step further... Suppose it mimics it so well that it becomes indistinguishable for any human from being intelligent. Then still it would not be intelligent, one could argue. But in that case you could also argue that no person is intelligent. The point being, intelligence cannot be defined. And, just maybe, that is the case because intelligence is not a reality, just something we made up.
- Jeff_Brown 4y ago
  Objective measures of intelligence are easy to come up with. The LSAT is one. (Not a great one -- GPT-4 passes it, after all -- but an objective one.) Consciousness, on the other hand, really might be an illusion.

deleted 4y ago

[deleted]

a_wild_dandan 4y ago

Yeah, calling AI a "token predictor" is like dismissing human cognition dumb "piles of electrical signal transmitters." We don't even understand our minds, let alone what constitutes any mind, be it alien or far simpler than ours. Simple != thoughtless. Different != thoughtless. Less capable != thoughtless. A human black box categorically dismissing all qualia or cognition from another remarkable black box feels so wildly arrogant and anthropocentric. Which, I suppose, is the most historically on-brand behavior for our species.

WoodenChair 4y ago
It might be a black box to you, but it’s not in the same way the human brain is to researchers. We essentially understand how LLMs work. No, we may not reason about individual weights. But in general it is assigning probabilities to different possible next tokens based on their occurrences in the training set and then choosing sometimes the most likely, sometimes a random one, and often one based on additional training from human input (e.g. instruct). It’s not using its neurons to do fundamental logic as the earlier posts in the thread point out. Stephen Wolfram explains this in simple terms.[0] 0: https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/ https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-...
- TchoBeer 4y ago
  >based on their occurrences in the training set the words "based on" are doing a lot of work here. No, we don't know what sort of stuff it learns from its training data nor do we know what sorts of reasoning it does, and the link you sent doesn't disagree.
  - WoodenChair 4y ago
    We know that the relative location of the tokens in the training data influences the relative locations of the predicted tokens. Yes the specifics of any given related tokens are a black box because we're not going to go analyze billions of weights for every token we're interested in. But it's a statistical model, not a logic model.

thomastjeffery 4y ago

Just because GPT exhibits a behavior does not mean it performs that behavior. You are using those weasel words for a very good reason! Language is a symbolic representation of behavior. GPT takes a corpus of example text, tokenizes it, and models the tokens. The model isn't based on any rules: it's entirely implicit. There are no subjects and no logic involved. Any "understanding" that GPT exhibits was present in the text itself, not GPT's model of that text. The reason GPT can find text that "makes sense", instead of text that "didn't make sense", is that GPT's model is a close match for grammar. When people wrote the text in GPT's corpus, they correctly organized "stuff that makes sense" into a string of letters. The person used grammar, symbols, and familiar phrases to model ideas into text. GPT used nothing but the text itself to model the text. GPT organized all the patterns that were present in the corpus text, without ever knowing why those patterns were used.

Jeff_Brown 4y ago
> GPT used nothing but the text itself to model the text. I used nothing but my sensory input to model the world, and yet I have a model of the world, not (just) of sensory input. There is an interesting question, though, of whether information without experience is enough to generate understanding. I doubt it.
- thomastjeffery 4y ago
  Not true. You used evolution, too. The structure of your brain growth is the result of complex DNA instructions that have been mutated and those mutations filtered over billions of iterations of competition. There are some patterns of thought that are inherent to that structure, and not the result of your own lived experience. For example, you would probably dislike pain with similar responses to your original pain experience; and also similar to my lived pain experiences. Surely, there are some foundational patterns that define our interactions with language.
- dTal 4y ago
  In what sense is your "experience" (mediated through your senses) more valid than a language model's "experience" of being fed tokens? Token input is just a type of sense, surely?