Tools designed to verify and monitor physical AI systems offer value, but human oversight is needed to prevent accidents and unexpected behavior.
Researchers from Google and MIT published a paper describing a predictive framework for scaling multi-agent systems. The framework shows that there is a tool-coordination trade-off and it can be used ...
Beyond executing predefined workflows, autonomous networks must understand operator intent, reason over tradeoffs and decide what actions to take.
VS Code's AI Toolkit and Microsoft Foundry can speed up agent development, but real-world success often depends on picking the right runtime and region, keeping tool-driven context under control, and ...
Acting as AI leaders, three of the most sophisticated large language models resorted to nuclear weapons in 95% of conflict ...
Google Agent Skills address context bloat; skills load on demand from skill.md files with YAML front matter, reducing ...
Abstract: This paper explores the process and applications of AI agent development based on Large Language Model (LLM) platforms. It begins by introducing the fundamental concepts, working principles, ...
Abstract: In recent years, the Digital Twin has attracted significant attention in academia and industry as a powerful technology for creating virtual replicas of physical systems tailored to specific ...
Will fully autonomous DeFi protocols replace manual governance? We analyze the shift from DAO voting to AI-driven ...
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