A "train of thought" can be seen as a trace of a depth first search where the preceding trace is used to guide termination and next expansion decisions. A similar concept, "taboo search", exists in classical constraint optimization where previous solutions are fit to a model that guides future expansion (but as the name "taboo" implies, away from uninteresting solutions).
We also have harnesses that perform breath first search.
If I tried to describe what it means to "think deeply", I would probably say a combination of both.
Ultimately I believe that we will surpass human capabilities but fail with alignment. Handing the world's resources over to stochastic systems that can evolve faster than we can reason about them simply leaves too many "interesting" outcomes that do not end well. I also expect the failure modes will be totally non-obvious.
That’s the reason we are “doing fine”. Once they stop needing you..
Also, both our comments brush over the generational struggles for fairness over the centuries. We have fought to be “fine”, it did not just happen. Without fairness being introduced by force you and I would be slaving away in some sweatshop getting paid nickels as was the norm not so long ago.
Edit: That’s also assuming you are Caucasian. If you are of a different ethnicity.. well, historically, all bets are off. You could also be the literal possession of some of these “worst people” with not even your own children considered yours.
Many types of Hitler does not make for a peaceful world all of sudden through sheer competition. It sounds nice but it will lead to certain hell.
I think this statement is continuation of the old fallacy - every generation thinks of brain in terms of what is the current technology zaitgeist is - was it 19th century when they thought brain is a network of pneumatic pipes?
The other option is that you do understand those words the same way, and the people making these (now nonsensical) anti-AI claims simply aren’t talking about the same programs/models we are. Their idea of SOTA is when chatgpt.com launched.
If you took a point sample pre-Opus, and didn’t write a good prompt, of course you would think all AI programming was worthless slop.
In any case, thanks for validating my previous assumption that people like this still exist even in the age of Opus/Fable.
Nothing. That's why it's a psychosis. It has nothing to do with the reality of how language models generate words without mental reasoning.
There is not. No one from these products is even claiming that's the case and they're so desperate to make the next big claim to re-ignite investment they'd be shouting it from every rooftop.
It's just breaking out all the reasonable probabilities around what it's been tasked with and structuring them in a way that is designed to actively look human, and then feed it back to itself. Fundamentally that's the easiest way to iterate new features when the underlying architecture of LLMs is largely "fixed" right now. The fact it is output in a way that appears to reason through each is just a technical decision that creates an illusion of reasoning.
(I am not claiming that there is none. But I personally would define "reasoning" in terms of its structure and its results, and it looks to me as if the best LLMs' "illusion of reasoning" has enough similarities in structure and results to much human reasoning that I don't see why we shouldn't also call it reasoning; if your opinion differs then I'm curious about where the disagreements lie. E.g., do we have different beliefs about what sort of thing LLMs' schmeasoning is able to accomplish, or does your notion of "reasoning" specifically require that it be done by humans, or what?)
Hell no. In very narrow tasks - yes, in vast majority, esp. involving state tracking (board games) and spatial reasoning - they are awful.