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Hinton thinks LLMs can "understand" because without understanding it's impossible to predict the next work as effectively as GPT-4. The only way to do that is t

Hinton thinks LLMs can "understand" because without understanding it's impossible to predict the next work as effectively as GPT-4. The only way to do that is to understand the meaning in the text. He also says he's given GPT-4 a novel reasoning problem he invented and it successfully answered, which wouldn't be possible without a level of understanding/intelligence (although I'm not sure how he ensured the problem wasn't in its training data).

Eliah_Lakhin 3y ago
Well, my point was that the speech by itself is not a good criteria to estimate the intellect. This is not only applicable to machines but to humans as well. I assume that the primary evolutionary determined purpose of a speech function was convincing rather than the source of reasoning. Even though we use natural languages to broadcast the information, the languages usually overwhelmed with linguistics and psychological tricks to make an illusion of usefulness and novelty of this information. Even if the information was truly novel, it's usually hard or even impossible to find the roots. This is one of the reasons of why most people prefer to learn rather to invent. Broadcasting of information of inventions made by someone else is much simpler and usually more beneficial than researching something from scratch. And our natural language specifically designed for such forms of broadcastings. In this sense if the ML developers would be focused on the inventions automatisation, I would expect that they would choose something more formalised than the natural language. Anyway, whatever way and methods they chose I think the better external estimation criteria of intelligence should be the ability to make completely new things that clearly didn't exist before. Not just reasoning about existing one. After all, it's not a new thing that computers are able to deduce. Any programming language can do that better than any chat bot.

Eliah_Lakhin 3y ago

Well, my point was that the speech by itself is not a good criteria to estimate the intellect. This is not only applicable to machines but to humans as well. I assume that the primary evolutionary determined purpose of a speech function was convincing rather than the source of reasoning. Even though we use natural languages to broadcast the information, the languages usually overwhelmed with linguistics and psychological tricks to make an illusion of usefulness and novelty of this information. Even if the information was truly novel, it's usually hard or even impossible to find the roots. This is one of the reasons of why most people prefer to learn rather to invent. Broadcasting of information of inventions made by someone else is much simpler and usually more beneficial than researching something from scratch. And our natural language specifically designed for such forms of broadcastings. In this sense if the ML developers would be focused on the inventions automatisation, I would expect that they would choose something more formalised than the natural language. Anyway, whatever way and methods they chose I think the better external estimation criteria of intelligence should be the ability to make completely new things that clearly didn't exist before. Not just reasoning about existing one. After all, it's not a new thing that computers are able to deduce. Any programming language can do that better than any chat bot.