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Are modern LLMs closer to AGI or next word predictor? Where do they fall in this graph with 10 on x-axis being human intelligence. (programming.dev)

submitted 2 months ago by [email protected] to c/[email protected]

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Wondering if Modern LLMs like GPT4, Claude Sonnet and llama 3 are closer to human intelligence or next word predictor. Also not sure if this graph is right way to visualize it.

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[–] lunarul 4 points 2 months ago

Make a large enough model, and it will seem like an intelligent being.

That was already true in previous paradigms. A non-fuzzy non-neural-network algorithm large and complex enough will seem like an intelligent being. But "large enough" is beyond our resources and processing time for each response would be too long.

And then you get into the Chinese room problem. Is there a difference between seems intelligent and is intelligent?

But the main difference between an actual intelligence and various algorithms, LLMs included, is that intelligence works on its own, it's always thinking, it doesn't only react to external prompts. You ask a question, you get an answer, but the question remains at the back of its mind, and it might come back to you 10min later and say you know, I've given it some more thought and I think it's actually like this.