11–20 of 279 posts
One interesting quirk with Claude is that it has no idea its Chain-of-Thought is visible to users. In one chat, it repeatedly accused me of lying about that. It only conceded after I had it think of a number between one and a million, and successfully 'guessed' it.
One interesting quirk with Claude is that it has no idea its Chain-of-Thought is visible to users. In one chat, it repeatedly accused me of lying about that. It only conceded after I had it think of a number between one and a million, and successfully 'guessed' it.
The fact that it was ever seriously entertained that a "chain of thought" was giving some kind of insight into the internal processes of an LLM bespeaks the lack of rigor in this field. The words that are coming out of the model are generated to optimize for RLHF and closeness to the training data, that's it! They aren't references to internal concepts, the model is not aware that it's doing anything so how could it…
But as you say, currently, they have zero "self awareness".
The fact that it was ever seriously entertained that a "chain of thought" was giving some kind of insight into the internal processes of an LLM bespeaks the lack of rigor in this field. The words that are coming out of the model are generated to optimize for RLHF and closeness to the training data, that's it! They aren't references to internal concepts, the model is not aware that it's doing anything so how could it…
When we get to the point where a LLM can say "oh, I made that mistake because I saw this in my training data, which caused these specific weights to be suboptimal, let me update it", that'll be AGI. But as you say, currently, they have zero "self awareness".
While I believe we are far from AGI, I don't think the standard for AGI is an AI doing things a human absolutely cannot do.
The fact that it was ever seriously entertained that a "chain of thought" was giving some kind of insight into the internal processes of an LLM bespeaks the lack of rigor in this field. The words that are coming out of the model are generated to optimize for RLHF and closeness to the training data, that's it! They aren't references to internal concepts, the model is not aware that it's doing anything so how could it…
When we get to the point where a LLM can say "oh, I made that mistake because I saw this in my training data, which caused these specific weights to be suboptimal, let me update it", that'll be AGI. But as you say, currently, they have zero "self awareness".
Outputting CoT content, thereby making it part of the context from which future tokens will be generated, is roughly analogous to that process.
The fact that it was ever seriously entertained that a "chain of thought" was giving some kind of insight into the internal processes of an LLM bespeaks the lack of rigor in this field. The words that are coming out of the model are generated to optimize for RLHF and closeness to the training data, that's it! They aren't references to internal concepts, the model is not aware that it's doing anything so how could it…
This in a nutshell is why I hate that all this stuff is being labeled as AI. Its advanced machine learning (another term that also feels inaccurate but I concede is at least closer to whats happening conceptually)
Really, LLMs and the like still lack any model of intelligence. Its, in the most basic of terms, algorithmic pattern matching mixed with statistical likelihoods of success.
And that can get things really really far. There are entire businesses built on doing that kind of work (particularly in finance) with very high accuracy and usefulness, but its not AI.
The fact that it was ever seriously entertained that a "chain of thought" was giving some kind of insight into the internal processes of an LLM bespeaks the lack of rigor in this field. The words that are coming out of the model are generated to optimize for RLHF and closeness to the training data, that's it! They aren't references to internal concepts, the model is not aware that it's doing anything so how could it…
[EDIT] The forms of their input & output and deliberate hype from "these are so scary! ... Now pay us for one" Altman and others, I should add. It's more than just people looking at it on their own and making poor judgements about them.
Earlier quoted context omitted.
When we get to the point where a LLM can say "oh, I made that mistake because I saw this in my training data, which caused these specific weights to be suboptimal, let me update it", that'll be AGI. But as you say, currently, they have zero "self awareness".
> When we get to the point where a LLM can say "oh, I made that mistake because I saw this in my training data, which caused these specific weights to be suboptimal, let me update it", that'll be AGI. While I believe we are far from AGI, I don't think the standard for AGI is an AI doing things a human absolutely cannot do.
Earlier quoted context omitted.
> When we get to the point where a LLM can say "oh, I made that mistake because I saw this in my training data, which caused these specific weights to be suboptimal, let me update it", that'll be AGI. While I believe we are far from AGI, I don't think the standard for AGI is an AI doing things a human absolutely cannot do.
All that was described here is learning from a mistake, which is something I hope all humans are capable of.