> To effectively predict the next token it needs a good idea of what comes after the next token.

And that's all it needs. Not reasoning.

Save us from the reasoning / sentience / consciousness / thinking semantic quicksand.

Babbage’s Analytical Engine didn’t actually analyze anything, and terminology hadn’t gotten any more clear-cut since.

	▲	RetroTechie an hour ago \| parent [-]
		+1. Inputs, processing & memory do the job. I suspect exact and/or universal definitions for intelligence, self-awareness, 'feelings' etc will prove to be elusive, and best we'll get is systems/robots etc behaving as if possessing those qualities. With some tests to put a number on them. Downside is that may apply to us humans too.

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wongarsu 3 hours ago | parent | prev | next [-]

At some level of performance reasoning becomes the most effective method to predict the next token

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chrisjj 3 hours ago | parent [-]

Chatbot "reasoning" arises from some level of the performance of the particular user, not of the chatbot.

	▲	astro1234 2 hours ago \| parent [-]
		I’m curious what this means? I think the evidence is pretty convincing that, while brittle, there is reasoning going on (though it depends on your definition of reasoning which I’m curious what that is for you).

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rlt 2 hours ago | parent | prev | next [-]

Isn't "reasoning" in LLMs just training it to have an internal monologue to think through problems like a human would? i.e. extra tokens.

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vidarh 3 hours ago | parent | prev | next [-]

How do you define reasoning in a measurable way?

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anuramat 3 hours ago | parent [-]

I keep asking the same question, and I think the steelman version would be "has metacognitive patterns similar to humans"

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pixl97 2 hours ago | parent [-]

I think the anthropomorphic view of this is dangerous in the long term as it starts the argument that anything that isn't reasoned by a human isn't reasoning at all. This just changes the argument from LLMs can reason like a human to LLMs can't reason at all while ignoring the third possibility of "LLMs can reason not like a human".

One of the biggest things I've learned after the event of LLMs is that humans definitions of intelligence/thinking/reasoning/consciousness/etc are very poorly defined. Not just across society at large, but the sciences themselves.

	▲	sigbottle an hour ago \| parent \| next [-]
		> I think the anthropomorphic view of this is dangerous in the long term as it starts the argument that anything that isn't reasoned by a human isn't reasoning at all. Something like this is actually a stance in the tradition of inferentialism (see the term sapience). Though "reasoning" isn't like, turing machine computability in this space; from what I understand, it's some abstract notion of the "space of reasons". I don't really understand it, honestly. There's some merit to this, IMO. When an LLM goes wrong, do you blame the person or the LLM? As in, would you throw said LLM in jail, and hold the LLM accountable? Not right now, at least. I'm not sure if that's what is meant by the "space of reasons", but the intuition is that 'reason' can mean a lot of different things, pragmatically speaking. Reason as a legible audit trail is one of those ways. But that's arguably getting into the social aspect of 'reason' (important!) and not like, what STEM people traditionally think of as 'reason'.
	▲	AlienRobot 22 minutes ago \| parent \| prev [-]
		I may be wrong but I think the word you want is anthropocentric, not anthropomorphic. Anthropomorphism is turning something that isn't human into something human, e.g. an AI, while anthropocentrism is taking human as the center and default state of things.

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jimbokun 3 hours ago | parent | prev [-]

What’s the difference?

	▲	chrisjj 39 minutes ago \| parent [-]
		Is regexp or compiler lookahead reasoning? No. Mistaking chatbot lookahead as reasoning comes with being gulled by the "artificial intelligence" sales pitch.