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@wellecks' "The Problem is the Problem" is a must-watch for us working in autonomous research and discovery loop engineering.
Thus far, I had only considered that my discovery loops would always target solutions to problems.
I had the same core-assumption about @zhengyaojiang 's amazing AIDE² research: We run autoresearch on autoresearch to find optimal solutions to decided-upon problems, including our research methods themselves.
But what if... we use autoresearch facilities to discover juicy, interesting and important problems as well?
Mind. Blown.
Oh, and with perfect timing, AIDE²'s paper finally dropped two days ago, too. It's of course the parallel must-read of the year:
arXiv.orgRecursive self-improvement of AI research agentsAI agents are beginning to automate research and development across the AI stack, from improving training efficiency to optimizing inference. A natural next step is to improve the research efficiency of the agents themselves. When an AI research agent's own code is the object of optimization, each accepted rewrite becomes the agent that the next round edits. We refer to this loop as recursive self…↗ arxiv.org