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> 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.

Fascinating reasoning. Should we conclude that humans are also incapable of intelligence? I don't know any human who can fit a terabyte of assembly into their context window.

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Any human who would try to do this is probably a special case. A reasonable person would break it down into sub-problems and create interfaces to glue them back together...a reasonable AI might do that as well.
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On the other hand the average human has a context window of 2.5 petabytes that's streaming inference 24/7 while consuming the energy equivalent of a couple sandwiches per day. Oh and can actually remember things.
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>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?

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> 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?

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Couldn't you periodically re-train it on what it's already done and use the context window for more short term memory? That's kind of what humans do - we can't learn a huge amount in short time but can accumulate a lot slowly (school, experience).

A major obstacle is that they don't learn from their users, probably because of privacy. But imagine if your context window was shared with other people, and/or all your conversations were used to train it. It would get to know individuals and perhaps treat them differently, or maybe even manipulate how they interact with each other so it becomes like a giant Jeffrey Epstein.

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