Posts

Google DeepMind’s roadmap treats future AI agents as operational actors that may need containment, monitoring, and layered controls, borrowing ideas from cybersecurity and safety engineering.

DARPA’s new DICE (Decentralized Artificial Intelligence through Controlled Emergence) program may be one of the strongest real-world signals yet that biological coordination principles are moving into operational AI architectures.

AgentSociety proposes a framework where autonomous agents cooperate through mechanisms borrowed from social choice theory and liquid democracy. Agents delegate authority, route information, and form consensus-based decision paths using only local knowledge and incentive-compatible behaviour.

29-Nov-2026 Hong Kong - DAI 2026 places coordination, markets, agent infrastructure, and societies of autonomous agents at the center of distributed AI research.

“Agentic AIs are a feral technology… they are projected to become a wild, self-sustaining, population.” Co-organised with Morgan Stanley, this upcoming Santa Fe Institute gathering takes place 15-Sept-2026 in NYC.

If there is a single institution that has consistently explored how intelligence emerges from interactions rather than instruction, it is the Santa Fe Institute.

A June workshop dedicated specifically to distributed collective intelligence, including bio-inspired approaches, decentralized trust systems, artificial life concepts, and collective behavior in smart systems.

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.

The paper proposes an “Internet of Agentic AI” in which autonomous agents discover each other, negotiate responsibilities, exchange context, coordinate workflows, and operate across organizational boundaries.

A great article to capture the principles we use at adaptive-emergent. Lessons forgotten in the cloud. https://www.tredence.com/blog/agentic-swarms-lessons-from-nature-for-machine-intelligence