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It’s important because solving a math problem requires you to actually understand something and follow deliberate steps. The fact that they can’t means they’re

It’s important because solving a math problem requires you to actually understand something and follow deliberate steps. The fact that they can’t means they’re just a toy ultimately.

gavindean90 2y ago
No, I disagree. It is just deliberate steps. Understanding can greatly help you do the steps and remember which ones to do. Training math is likely hard because the corpus of training data is so much less because the computers themselves do our math as it relates to computers. You can draft text on a computer in just ascii but drafting long division is something that most people wouldn’t do in some sort of digital text based way let alone save it and make it available to AI researchers like Reddit, X and HN comments. I expect LLMs to be bad at math. That’s ok, they are bad because the computers themselves are so good at math.
- waveBidder 2y ago
  you can easily generate reams and reams of long division text if you so choose, and i'd assume openai has done so to get to this point
Shorel 2y ago
No, hard disagree. It is not a toy, because language is not a toy. Language is a ridiculously powerful tool we have as humans, we just take it for granted because we are very good at it. What ChatGPT allows us is to evaluate the usefulness of language without all the other intellectual tools we have, like mathematics, logic, physics and self perception. So, the fact that a GPT model can do all those things while being just a language model is extraordinary. It is an idea serializer. Written language is not the idea, is just the serialization of the idea, the human thought. We serialize our ideas, and with a GPT we use the serialization to leverage some of the connections and behaviours of the idea, without actually understanding the meaning. This makes both tools, language for humans and GPT for computers, a powerful abstraction that allows us to not need to think about every detail because some of the logic in the ideas is covered by the serialization that language performs over the idea. I find all of this fascinating. Add the other parts of the human brain (a GPT is only the Broca's area analogue) to have real logic and physics and mathematics understanding, and the predictions about AI will be true.

It’s important because solving a math problem requires you to actually understand something and follow deliberate steps. The fact that they can’t means they’re just a toy ultimately.

gavindean90 2y ago

No, I disagree. It is just deliberate steps. Understanding can greatly help you do the steps and remember which ones to do. Training math is likely hard because the corpus of training data is so much less because the computers themselves do our math as it relates to computers. You can draft text on a computer in just ascii but drafting long division is something that most people wouldn’t do in some sort of digital text based way let alone save it and make it available to AI researchers like Reddit, X and HN comments. I expect LLMs to be bad at math. That’s ok, they are bad because the computers themselves are so good at math.

waveBidder 2y ago
you can easily generate reams and reams of long division text if you so choose, and i'd assume openai has done so to get to this point

Shorel 2y ago

No, hard disagree. It is not a toy, because language is not a toy. Language is a ridiculously powerful tool we have as humans, we just take it for granted because we are very good at it. What ChatGPT allows us is to evaluate the usefulness of language without all the other intellectual tools we have, like mathematics, logic, physics and self perception. So, the fact that a GPT model can do all those things while being just a language model is extraordinary. It is an idea serializer. Written language is not the idea, is just the serialization of the idea, the human thought. We serialize our ideas, and with a GPT we use the serialization to leverage some of the connections and behaviours of the idea, without actually understanding the meaning. This makes both tools, language for humans and GPT for computers, a powerful abstraction that allows us to not need to think about every detail because some of the logic in the ideas is covered by the serialization that language performs over the idea. I find all of this fascinating. Add the other parts of the human brain (a GPT is only the Broca's area analogue) to have real logic and physics and mathematics understanding, and the predictions about AI will be true.