Am I the only one who wasn’t particularly impressed by AutoResearch? If you looked at what the agent was actually doing, it was just tuning parameters mostly, not really trying different novel approaches.
I couldn’t help myself but consider this mostly a very inefficient variant of hyperparameter optimization, but someone correct me if I’m wrong, I may be looking at this too pessimistic.
Karpathy embedded within an organization is way more impressive than him out on his own with hot takes and little projects. I hope he does great things for Anthropic.
> Am I the only one who wasn’t particularly impressed by AutoResearch?
isn't it just a nerfed AlphaEvolve? https://arxiv.org/abs/2506.13131Inefficient variants with $100m+ worth of compute will still probably outperform the best team of researchers
I didn't dig into what the actual repository was doing, but personally, I took some inspiration from the idea after reading about it and realizing that I might have been underestimating the ability of LLMs. I put a bit more work into a performance harness I was using locally and just set some agents to brainstorming and they did seem to find some great stuff. So I don't really have a stance one way or another on this specific repo, but the general idea seems like a really good one.