Ex-DeepMind researcher argues heterogeneous multi-objective AI systems may be more robust
AdaptiveAgents · x · 2026-10-21
In parts 11-12 of his thread on decentralized AGI, the author speculates that a heterogeneous, multi-objective intelligent system—whose components have different goals, evaluate each other, and adapt through feedback—might be more robust than one optimized toward a single objective. He also raises the ownership question: agent boundaries can be drawn arbitrarily, spanning one or many agents, LLMs and conventional software, with different owners.
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