As an author of the blog, I'll note that this was one of the easiest applications of ADRS. Bowen, who was leading this effort, got things running within a day or two and the initial runs were with free Google credits! It was exciting to see how quickly these kinds of frameworks could be applied to real-world engineering and algorithmic challenges.
did AI explain its thinking, or could it have just stumbled upon the solution without designing it or understanding why it worked? i.e. could it have just been a hallucination that happened to work?
This is a great question! By analyzing the logs of OpenEvolve with the full model outputs, we observed how the AI got its ideas (seemed to be pulling from literature in the space) and how it tried to apply them. So in some sense, it "reasoned" about how to get better algorithms. And we saw this process proceed systematically via the ADRS framework to converge to a significantly better algorithm
Can you confirm if this generated code is the same as https://arxiv.org/pdf/2402.02447 ?
very interesting, thank you.
What does ADRS stand for?
This blog post has more accessible writing and diagrams: https://www.sigops.org/2025/barbarians-at-the-gate-how-ai-is...
From TFA: https://arxiv.org/pdf/2510.06189
> We term this approach as AI-Driven Research for Systems (ADRS), which iteratively generates, evaluates, and refines solutions.
> The central thesis of this paper is that a new class of AI-driven approaches, which we term AI-Driven Research for Systems (ADRS), is beginning to show promising results in automated algorithm discovery, and will ultimately prompt a re-evaluation of the traditional role of systems researchers.