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OpenAI, Google and Anthropic are struggling to build more advanced AI

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625 points lukebennett | 1 comments | 13 Nov 24 13:28 UTC | HN request time: 0s | source
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nerdypirate ◴[14 Nov 24 18:01 UTC] No.42139075[source]▶
"We will have better and better models," wrote OpenAI CEO Sam Altman in a recent Reddit AMA. "But I think the thing that will feel like the next giant breakthrough will be agents."

Is this certain? Are Agents the right direction to AGI?

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xanderlewis ◴[14 Nov 24 18:06 UTC] No.42139151[source]▶
If by agents you mean systems comprised of individual (perhaps LLM-powered) agents interacting with each other, probably not. I get the vague impression that so far researchers haven’t found any advantage to such systems — anything you can do with a group of AI agents can be emulated with a single one. It’s like chaining up perceptrons hoping to get more expressive power for free.
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j_maffe ◴[14 Nov 24 18:19 UTC] No.42139320[source]▶
> I get the vague impression that so far researchers haven’t found any advantage to such systems — anything you can do with a group of AI agents can be emulated with a single one. It’s like chaining up perceptrons hoping to get more expressive power for free. Emergence happens when many elements interact in a system. Brains are literally a bunch of neurons in a complex network. Also research is already showing promising results of the performance of agent systems.
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1. xanderlewis ◴[14 Nov 24 22:27 UTC] No.42141876{3}[source]▶
That’s the inspiration behind the idea, but it doesn’t seem to be working in practice.

It’s not true that any element, when duplicated and linked together will exhibit anything emergent. Neural networks (in a certain sense, though not their usual implementation) are already built out of individual units linked together, so simply having more of these groups of units might not add anything important.

> research is already showing promising results of the performance of agent systems.

…in which case, please show us! I’d be interested.