DeepMind researchers propose 'agentic economies' to manage AI-driven scientific discovery
weballergy · x · 2026-09-28
Nenad Tomasev, Simon Osindero and colleagues at Google DeepMind released the preprint "Agentic Economies for Autonomous Scientific Discovery" (arXiv:2609.31562).
- AI for Science is shifting from single models on narrow tasks to multi-agent systems orchestrating end-to-end research workflows.
- Current work over-focuses on reasoning and hypothesis generation while ignoring the key bottleneck: experiments are physically and economically resource-intensive.
- The paper proposes infrastructure of scientific agent economies — markets and institutions — so AI agents and human scientists can collaborate, set research priorities, and allocate scarce resources.
- The authors' takeaway: "science is more than reasoning — it is a deeply collaborative and social process, and AI science must reflect that."
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