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There’s various kinds of learning (and to be clear transformer-based LLMs do sort of “learn”). ChatGPT is a really finely tuned probability model (the tuning ca

by RC_ITR 4y ago

There’s various kinds of learning (and to be clear transformer-based LLMs do sort of “learn”). ChatGPT is a really finely tuned probability model (the tuning came during the training and that’s what I would equate to learning), but it lacks understanding. The example that’s most glaring is asking it simple math (or in Dall-E’s case, asking it to generate images of text). You’ll get outputs that are definitely in the correct form, but you won’t get the right answer, because the model links words that it’s seen in a particular before, it is ignorant to the rules of math. The funny caveat is that equations like 2+2 are so common that it will get that right, but two random four digit numbers (rarer in text) will almost always be wrong. That’s why ultimately, AI is an outcome and we will need many different tools working in concert to achieve it (to be fair, the same is true of your brain, there are plenty of uniquely architectured parts of the human brain).

kilgnad 4y ago
Well the AI has to infer what math is with many examples. You give it enough examples it will be able to calculate equations it's never seen before. But when you don't give it enough examples it does a best guess. This is what you would also do as a human if you were trying to infer the concept of Arabic numerals and math from a series of random examples. I would say based on what you have hear dall-e2 has a misunderstanding of math. Which would be isomorphic to our misunderstanding of math if we were to be put in the exact same situation.
- RC_ITR 4y ago
  >Well the AI has to infer what math is with many examples. You give it enough examples it will be able to calculate equations it's never seen before. This is categorically not true and an important distinction to understand. All OpenAI products are based on GPT, which is a language model, not a general learning model. You could feed it every math textbook in existence and the model will learn absolutely no math, other than how to repeat math that others have done for it (and the point of multiplying 4 digit numbers is that it's nearly impossible to brute force that). This is an extremely important distinction - we assume being able to describe math means that something understands math (because that is how humans work), but math is rules-based and GPT is stochastic, so it can sound like it understands math, but it does not. Now, it would be trivial to put a filter on that recognizes equations and returns an output based on regular rules-based algorithms (Google search's LLMs do this for example), but this again points out that AI is an outcome and learning isn't the solution to the problem, so much as synthesis is (again, the brain metaphor is that no matter how well trained your pre-frontal cortex is, it will be bad at making your heart beat all the time).

by RC_ITR 4y ago

kilgnad 4y ago

Well the AI has to infer what math is with many examples. You give it enough examples it will be able to calculate equations it's never seen before. But when you don't give it enough examples it does a best guess. This is what you would also do as a human if you were trying to infer the concept of Arabic numerals and math from a series of random examples. I would say based on what you have hear dall-e2 has a misunderstanding of math. Which would be isomorphic to our misunderstanding of math if we were to be put in the exact same situation.

RC_ITR 4y ago
>Well the AI has to infer what math is with many examples. You give it enough examples it will be able to calculate equations it's never seen before. This is categorically not true and an important distinction to understand. All OpenAI products are based on GPT, which is a language model, not a general learning model. You could feed it every math textbook in existence and the model will learn absolutely no math, other than how to repeat math that others have done for it (and the point of multiplying 4 digit numbers is that it's nearly impossible to brute force that). This is an extremely important distinction - we assume being able to describe math means that something understands math (because that is how humans work), but math is rules-based and GPT is stochastic, so it can sound like it understands math, but it does not. Now, it would be trivial to put a filter on that recognizes equations and returns an output based on regular rules-based algorithms (Google search's LLMs do this for example), but this again points out that AI is an outcome and learning isn't the solution to the problem, so much as synthesis is (again, the brain metaphor is that no matter how well trained your pre-frontal cortex is, it will be bad at making your heart beat all the time).