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The question at hand is whether GPT can create new/original ideas, not whether natural language is most suited to model the physical world and its logic. It is

The question at hand is whether GPT can create new/original ideas, not whether natural language is most suited to model the physical world and its logic. It is sufficiently suited to create a model suitable for communication, to generate new ideas, and to reason logically about the world, as we do without math or other more formal languages every day. That being said, GPT is also able to generate working code and correct mathematics so there is some evidence he has an internal model of those languages too, and some evidence that those capacities do not strictly require a distinct architecture.

fauigerzigerk 4y ago
>It is sufficiently suited to create a model suitable for communication, to generate new ideas, and to reason logically about the world, as we do without math or other more formal languages every day. I'm not convinced that it has ideas or that it does logical reasoning. What I can see is that it emits text that is similar to what a person might write if they had ideas or did some (rather flawed) reasoning. But I also see that it often emits text that a person with these language skills and this breadth and depth of knowledge would never write, because it betrays a complete lack of understanding of what is being said and why it is being said. For instance, a person is unlikely to casually make up some statistically plausible numbers when asked about a particular company's financials (unless the intention was fraud). That's because a person would have an idea of the purpose of financial reports and the purpose of the question and draw the conclusion that made-up numbers are useless. And the reason for this strange lapse is not lack of information. If you asked an LLM about fabricated financials, it would go on and on about financial fraud and things like that, suggesting an understanding of the purpose of these numbers as well as very deep knowledge of the subject. To me, this and many other weird inconsistencies suggest that LLMs have absolutely no idea what they are talking about. And generating statistically plausible sequences of words that were never written before is not the same thing as having a new idea. In any event, I am optimistic that this technology can be very useful in the right context.
- ad404b8a372f2b9 4y ago
  (With regards to the quoted text, "it" referred to natural language, not ChatGPT. You were questioning the sufficiency of natural language, not whether ChatGPT could do those things.) With regards to ChatGPT: Given a set of previously unseen axioms it can (sometimes) make a previously unseen and logically consistent prediction. This is what I have observed. Whether this is true logical reasoning, truly new ideas, or just an arrangement of statistically plausible characters that belies its lack of understanding is a metaphysical question akin to the Chinese room.

fauigerzigerk 4y ago

>It is sufficiently suited to create a model suitable for communication, to generate new ideas, and to reason logically about the world, as we do without math or other more formal languages every day. I'm not convinced that it has ideas or that it does logical reasoning. What I can see is that it emits text that is similar to what a person might write if they had ideas or did some (rather flawed) reasoning. But I also see that it often emits text that a person with these language skills and this breadth and depth of knowledge would never write, because it betrays a complete lack of understanding of what is being said and why it is being said. For instance, a person is unlikely to casually make up some statistically plausible numbers when asked about a particular company's financials (unless the intention was fraud). That's because a person would have an idea of the purpose of financial reports and the purpose of the question and draw the conclusion that made-up numbers are useless. And the reason for this strange lapse is not lack of information. If you asked an LLM about fabricated financials, it would go on and on about financial fraud and things like that, suggesting an understanding of the purpose of these numbers as well as very deep knowledge of the subject. To me, this and many other weird inconsistencies suggest that LLMs have absolutely no idea what they are talking about. And generating statistically plausible sequences of words that were never written before is not the same thing as having a new idea. In any event, I am optimistic that this technology can be very useful in the right context.

ad404b8a372f2b9 4y ago
(With regards to the quoted text, "it" referred to natural language, not ChatGPT. You were questioning the sufficiency of natural language, not whether ChatGPT could do those things.) With regards to ChatGPT: Given a set of previously unseen axioms it can (sometimes) make a previously unseen and logically consistent prediction. This is what I have observed. Whether this is true logical reasoning, truly new ideas, or just an arrangement of statistically plausible characters that belies its lack of understanding is a metaphysical question akin to the Chinese room.