How bees, ants, and fish led us to multi-agent AI — and why it is so hard to secure

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This article explains how multi-agent AI evolved from ideas inspired by bees, ants, fish, and other collective systems. It traces the concept through swarm intelligence, distributed AI, reinforcement learning, and modern agentic systems. The piece also highlights why securing these systems is difficult, especially when agents interact across Kubernetes, IoT, and edge environments. Positive Technologies uses the discussion to frame the technical risks and the broader shift toward autonomous, distributed AI architectures.

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