Researchers have introduced a new framework that trains multiple AI agents at the same time, with each agent taking on a specialized role. The goal is to handle complex, multi-step tasks more reliably through clearer division of labor and tighter coordination.<br /> The article Multi-agent training aims to improve coordination on complex tasks appeared first on THE DECODER. [...]
Researchers at Google and MIT have conducted a comprehensive analysis of agentic systems and the dynamics between the number of agents, coordination structure, model capability, and task properties. W [...]
Enterprise teams building multi-agent AI systems may be paying a compute premium for gains that don't hold up under equal-budget conditions. New Stanford University research finds that single-age [...]
As enterprise codebases grow, AI agents tasked with analyzing them are buckling under the weight of long-horizon tasks that require multiple interactions and tool calls. Dividing the work among a team [...]
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 [...]
Enterprise AI has a new infrastructure problem: companies are accumulating agents faster than they are developing systems to govern them.Gartner estimates that the average global Fortune 500 company w [...]
Baseten, the AI infrastructure company recently valued at $2.15 billion, is making its most significant product pivot yet: a full-scale push into model training that could reshape how enterprises wean [...]
Adding an AI agent to Slack sounds appealing to many enterprises — but, as VentureBeat has experienced ourselves first hand — the reality is often far more complex and clunkier than it first seems [...]
Anthropic on Tuesday unveiled a suite of updates to its Claude Managed Agents platform at its second annual Code with Claude developer conference in San Francisco, introducing a new capability called [...]
One of the key challenges of current multi-agent AI systems is that they communicate by generating and sharing text sequences, which introduces latency, drives up token costs, and makes it difficult t [...]