Its pretty clear that the problem of solving AI is software, I don't think anyone would disagree.

But that problem is MUCH MUCH MUCH harder than people make it out to be.

For example, you can reliably train an LLM to produce accurate output of assembly code that can fit into a context window. However, lets say you give it a Terabyte of assembly code - it won't be able to produce correct output as it will run out of context.

You can get around that with agentic frameworks, but all of those right now are manually coded.

So how do you train an LLM to correctly take any length of assembly code and produce the correct result? The only way is to essentially train the structure of the neurons inside of it behave like a computer, but the problem is that you can't do back-propagation with discrete zero and 1 values unless you explicitly code in the architecture for a cpu inside. So obviously, error correction with inputs/outputs is not the way we get to intelligence.

It may be that the answer is pretty much a stochastic search where you spin up x instances of trillion parameter nets and make them operate in environments with some form of genetic algorithm, until you get something that behaves like a Human, and any shortcutting to this is not really possible because of essentially chaotic effects.

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dan_mctree an hour ago | parent [-]

>So obviously, error correction with inputs/outputs is not the way we get to intelligence.

This doesn't seem to follow at all let alone obviously? Humans are able to reason through code without having to become a completely discrete computer, but probably can't reason through any length of assembly code, so why is that requirement necessary and how have you shown LLMs can't achieve human levels of competence on this kind of task?

	▲	ActorNightly an hour ago \| parent [-]
		> but probably can't reason through any length of assembly code Uh what? You can sit there step by step and execute assembly code, writing things down on a piece of paper and get the correct final result. The limits are things like attention span, which is separate from intelligence. Human brains operate continuously, with multiple parts being active at once, with weight adjustment done in real time both in the style of backpropagation, and real time updates for things like "memory". How do you train an LLM to behave like that?