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Multi-agent reinforcement learning driving smart factory agility
At the core of Industry 4.0, the smart factory integrates automation, mass customization, and self-organization into a highly ...
Many enterprises are moving from experimenting with single AI agents to a multi-level approach that spans functions such as ...
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Sakana AI Launches Fugu Ultra Multi-Agent System
Launch Announcement: Sakana AI officially released Fugu Ultra on June 22, 2026, as a high-performance multi-agent ...
Agentic AI in pharma advances drug discovery through multi-agent systems and self-driving labs that autonomously plan, ...
Stanford's DeLM lets AI agents coordinate without a central controller, cutting multi-agent inference costs 50% and beating ...
Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. As the CTO of an AI-native email management startup, I've spent the past year building multi ...
Plant phenotyping increasingly relies on (semi-)automated image-based analysis workflows to improve its accuracy and scalability. However, many existing solutions remain overly complex, difficult to ...
As cities increasingly rely on AI for sustainability challenges, a critical gap emerges: AI applications in urban planning and safety predominantly proceed without explicit guidance from established ...
OpenClaw and Hermes are two frameworks that, when integrated, can create a robust multi-agent system for managing complex workflows. OpenClaw, using models like Opus 46, specializes in ...
For too long, enterprises have failed to go beyond the view of AI as a product; an assistant that sits to the side, helping users complete tasks and delivering incremental productivity gains. This ...
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