Comment by Hugsun
It might understand the concept of it having limitations, but it can't AFAIK reliably recognize when it does or doesn't know something, or has encountered a limitation.
It might understand the concept of it having limitations, but it can't AFAIK reliably recognize when it does or doesn't know something, or has encountered a limitation.
There is an important difference between humans and LLMs in this context.
Humans do in most cases have some knowledge about why they know the things they know. They can recall the topics they learned at school, and can deduce that they probably heard a given story from a friend who likes to discuss similar topics, etc.
LLMs have no access to the information they were trained on. They could know that everything they know was learned during the training, but they have no way of determining what they learned about and what they didn't.
If you think about it, those criticisms extend to human thinking too. We aren't infallible in all situations either.
It's only when we can interact with the environment to test our hypothesis that we then refine what we know and update our priors appropriately.
If we let LLMs do that as well, by allowing it to run code and interact with documentation/the internet and double-check things its not sure of, it's not out of the question LLMs won't eventually be able to more reliably understand its limitations.
As they are currently constructed, I would say that it is out of the question.
Humans usually know (at least roughly) the source of anything they know, as there will be a memory or a known event associated with that knowledge.
LLMs have no analogous way to determine the source of their knowledge. They might know that all their knowledge comes from their training, but it has no way of knowing what was included in the training and what wasn't.
This could maybe be achieved with some more fancy RAG systems, or online training abilities. I think an essential piece is the ability to know the source of information. When LLMs reliably do, and apply that knowledge, they'll be much more useful. Hopefully somebody can achieve this.
Its the same thing as with humans, thats right. It doesn't do Logical reasoning but even the best humans stop at some level.
But if you read all the knowledge of humans, were does your reasoning start? Probably at a very high level of it.
If you look at human brains, we conduct experiments right? As a software developer, we write tests. ChatGPT can already run python code and it can write unit tests.
We do not use proofs when we develop. An AI could actually doing this. But at the end its more of a question who does it better, faster and cheaper eh?