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OpenAI 7 years ago 35
Agents trained in a simulated hide-and-seek environment discovered six distinct strategies and counterstrategies through multi-agent interaction without explicit instruction. The agents progressed from simple behavior to increasingly complex tool use within a single environment. This demonstrates that competitive multi-agent training can generate emergent complexity without direct supervision or predetermined task design.
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TLDRocket
26 October 2026
Today’s biggest thread isn’t a new model release—it’s the bill coming due. Apollo Global Management says that outside the biggest technology firms, most companies still aren’t seeing measurable financial benefits from AI. In Apollo’s analysis of the S&P 493, revenue per worker has hovered at about $550,000 since 2019, a sign that productivity gains are either absent, delayed, or captured elsewhere. The implication is brutally practical: mainstream corporate AI spending is getting reframed from “growth” to “cost center,” and more CFOs are demanding clear returns before scaling experiments into full deployments.
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