The article discusses the shift from evaluating AI as an individual assistant to the concept of collective intelligence. The author notes that while we previously compared one human to one agent, OpenAI's recent experiment with 10,000 agents solving the Navier-Stokes problem changes the paradigm. Scaling intelligent systems requires new approaches to management: task distribution, group coordination, and the synthesis of intermediate results. Unlike human mathematicians, where managing a 'division' of scientists becomes a complex bureaucratic task, AI agents allow for the efficient scaling of computational resources to solve fundamental problems. The author emphasizes that the future lies not just in improving the quality of a single AI, but in the ability of systems to work as a coordinated swarm, where the number of agents directly converts into scientific progress, overcoming the limitations of human management.
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