Theory

A notable June event from the Santa Fe Institute, co-sponsored by OpenAI and Google DeepMind, focused on intelligence across multiple organisational and social scales rather than intelligence as an individual phenomenon.

Researchers from SUPSI and ETH Zurich developed a firefly-inspired visible-light communication system for nano-drone swarms using LEDs and convolutional neural networks for message decoding.

By encoding interaction rules directly into physical structure, researchers showed that coordinated group behavior can emerge without digital control, sensors, or centralized systems.

Over this 7-part series, we’ve explored how natural systems — ants, bees, birds, and brains — solve problems through emergence, not instruction.

In particular areas of human endeavour, precision in language matters, such as contract law. Sometimes the language is numbers, like in accounting or science.

This is the fifth of seven articles in the series comparing Nature with AI and how they approach agents. Part four is accessed here, the full series from here.

In previous articles we defined terms like agent and swarms, and looked at a major difference between natural and artificial adaptation, time.

“Nature does not hurry, yet everything is accomplished.” – Lao Tzu In part one and part two, we’ve explored how biological agents — ants, birds, bees — operate without central control, memory, or explicit goals.

In part one, we asked what it means to call something an agent. We contrasted modern AI agents — designed to achieve explicit goals — with biological agents like bees or ants, which follow simple rules without necessarily “understanding” their purpose.