Training standard AI models against a diverse pool of opponents — rather than building complex hardcoded coordination rules — is enough to produce cooperative multi-agent systems that adapt to each other on the fly. That's the finding from Google's Paradigms of Intelligence team, which argues the approach offers a scalable and computationally efficient blueprint for enterprise multi-agent deployments without requiring specialized scaffolding.The technique works by training an LLM agent via decentralized reinforcement learning against a mixed pool of opponents — some actively learning, some static and rule-based. Instead of hardcoded rules, the agent uses in-context learning to read each interaction and adapt its behavior in real time.Why multi-agent systems keep fighting ea [...]
Microsoft today announced the general availability of Agent 365 and Microsoft 365 Enterprise 7, two products designed to bring security and governance to the rapidly growing population of AI agents op [...]
Artificial intelligence agents powered by the world's most advanced language models routinely fail to complete even straightforward professional tasks on their own, according to groundbreaking re [...]
“You can deceive, manipulate, and lie. That’s an inherent property of language. It’s a feature, not a flaw,” CrowdStrike CTO Elia Zaitsev told VentureBeat in an exclusive interview at RSA Conf [...]
Amazon Web Services on Tuesday announced a new class of artificial intelligence systems called "frontier agents" that can work autonomously for hours or even days without human intervention, [...]
A rogue AI agent at Meta passed every identity check and still exposed sensitive data to unauthorized employees in March. Two weeks later, Mercor, a $10 billion AI startup, confirmed a supply-chain br [...]
Jensen Huang walked onto the GTC stage Monday wearing his trademark leather jacket and carrying, as it turned out, the blueprints for a new kind of monopoly.The Nvidia CEO unveiled the Agent Toolkit, [...]
Fetch AI, a startup founded and led by former DeepMind founding investor, Humayun Sheikh, today announced the release of three interconnected products designed to provide the trust, coordination, and [...]
Researchers at the University of Science and Technology of China have developed a new reinforcement learning (RL) framework that helps train large language models (LLMs) for complex agentic tasks beyo [...]