> You're assuming that AI skeptics agree that models are demonstrating intelligence along the same axis as humans and that with further improvement they will become equivalent to humans.
No definitely not saying this and I don’t quite know what it means
> Model reasoning is on an s-curve, which is improving.
Is this saying two different things? I think I might agree with this in principle as in maybe there is some sort of s curve or something like it but do we see evidence of this? Where?
> Model intelligence is not the same as reasoning. It's a different axis, and one I have not seen much movement on.
Can you clarify this? What is the distinction and what makes you say you have “not seen much progress?”
> See, humans have a recursive form of intelligence which is capable of self-reflection and introspection. LLMs can only reason about tokens which have already been emitted
LLMs do self reflection and introspection in context, and tweaks such as value functions (serving a similar purpose to intuition or emotion) may make this better? Why do you feel self reflection and introspection are a fundamental limitation here? Models reason over tokens they have emitted and also with their own sense and learned behavior already. Are you just talking about continual learning? Also I feel people just latch onto LLMs as if this is all of AI. Why? SSMs, memory networks, recurrent neural networks etc etc etc are all part of AI but aren’t as popular because they can’t yet compete with LLMs in terms of scaling laws and training efficiency due to e.g. hardware and software optimization and investment being focused on LLMs. If something else comes along that works better we’ll just start scaling that.
> Humans and LLMs do not share the same form of reasoning, and general human-like intelligence will not arise from the current architecture of LLMs.
Very strong statement, any theoretical or experimental basis for this? I also don’t particularly care personally other than as a point of curiosity. Why does it matter if AI systems will develop equivalent reasoning mechanisms as humans? In fact it may be much better not to.
> Therefore it is a mistake to assume that continual improvement on the reasoning scale will result in something that is equivalent enough to humans to replace all labor.
Idk I didn’t say this explicitly but I also dont think it matters if we have a system “equivalent to humans” or one that “replaces all labor”.