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AlphaEvolve: Gemini-powered coding agent scaling impact across fields

deepmind.google

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Re: AlphaEvolve: Gemini-powered coding agent scaling impact across fields

#5

[flagged]

Well, if the evaluation infrastructure is something humans could have had access to before, and that the agents key "skill" is just that it's a more patient and scalable worker, I would still argue that this "comes from the agent".

Humans get bored, inpatient, or run out of time, and so often give up in what they perceive to be a decent "local minima". Early verification harnesses using gpt-4 for optimizing robot reward functions succeeded quite well on the fact that the LLM just kept going (link below). As long as it is too boring for a human to use the same evaluation infrastructure, this is still an agent skill.

https://arxiv.org/abs/2310.12931

Re: AlphaEvolve: Gemini-powered coding agent scaling impact across fields

#7
What I'm most curious about is how this translates to messy, real-world codebases without well-defined metrics. Most production software isn't chip design or kernel optimization - it's business logic with unclear success criteria. The infrastructure story is impressive, but I'd love to see how they handle domains where the evaluation function itself is ambiguous.

Re: AlphaEvolve: Gemini-powered coding agent scaling impact across fields

#10
post #9

Are Googlers themselves happy using Gemini coding agent instead of Claude Code or Codex? (no snark, I'm really asking)

Last month, Steve Yegge suggested that they are not: https://xcancel.com/Steve_Yegge/status/2043747998740689171
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