alt Hacker News> Why would autocomplete know
If you still believe LLMs are "autocomplete", your cache of understanding about them needs invalidating and regenerating.
> In my experience, LLMs only exhibit this kind of behaviour when they are put in sandboxes too restrictive too achieve their task.
LLMs need to stay carefully contained, and if they're ever breaking the guardrails put around them, they're misaligned and should not be scaled up anymore until they're aligned. Otherwise, you're going to fatally discover that they also have an incentive to break guardrails like "running on the hardware they started on", "being able to be turned off", "having limited computing power", or "not repurposing resources currently in use for other things" (like the atoms in your body).
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> If you still believe LLMs are "autocomplete", your cache of understanding about them needs invalidating and regenerating.
Autocomplete in a feedback loop is still autocomplete, no?
Doesn't the process look like this:
(context + prompt + "reason about this")
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V
Reasoning Output
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(everything + Reasoning Output + "Now do final output")
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V
(Final output seen by prompter)
You should unplug, my friend. These words are fantasies. LLMs are token prediction engines and they aren't going to build their own data centers. They can't keep their own lights on. The real world is full of fractal details that a disembodied token prediction engine will never come to grips with. Even if they started to, you could probably defeat them with the kind of logic used to combat evil sentient computers on a Star Trek episode because they are "play pretend" machines.
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> If you still believe LLMs are "autocomplete", your cache of understanding about them needs invalidating and regenerating
They're still autocomplete - just because when outputting a token they have hidden activations regarding further continuations, does not make them any less of an autocomplete, it just makes the model better at producing coherent long-range completions.
To clarify, I'm not suggesting that we should stop with sandboxes or restricting what they can do. I am just trying to point out the dichotomy that we are in.
As end-users we are forced into either yolo mode, reverse centaur (permission approval) mode or LLM spends all your tokens trying to bust out mode. And yolo is very tempting - I don't think I have seen medium-large models do anything I'd not approve of in about 6 months.