Abstract: Multi-agent systems have become a research focus in the control field due to their ability to complete complex tasks that single agents cannot achieve independently, with state ...

Visual Studio Code 1.109 introduces structured, multi-agent workflows that move AI assistance beyond single-chat interactions. Parallel subagents enable concurrent task execution without consuming the ...

Since last spring, OpenAI has offered Codex. What started life as the company's response to Claude Code is becoming something more sophisticated with the release of a new dedicated macOS app. At its ...

What if your AI could think like a hive mind, tackling complex problems with the precision of 100 synchronized agents? In this guide, Sam Witteveen explains how Kimi K2.5’s new Agent Swarm system is ...

Traditional processes used to discover new materials are complex, time-consuming, and costly, often requiring years of sustained effort. Recent advances in large language models (LLMs) have ...

Airtable is applying its data-first design philosophy to AI agents with the debut of Superagent on Tuesday. It's a standalone research agent that deploys teams of specialized AI agents working in ...

Anthropic reveals when multi-agent systems outperform single AI agents, citing 3-10x token costs and three specific use cases worth the overhead. Anthropic published detailed guidance on multi-agent ...

The big AI companies promised us that 2025 would be “the year of the AI agents.” It turned out to be the year of talking about AI agents, and kicking the can for that transformational moment to 2026 ...

We collaborate with the world's leading lawyers to deliver news tailored for you. Sign Up for any (or all) of our 25+ Newsletters. Some states have laws and ethical rules regarding solicitation and ...

LangChain releases comprehensive guide to multi-agent AI systems, detailing subagents, skills, handoffs, and router patterns with performance benchmarks. LangChain has published a detailed framework ...

David Talby, PhD, MBA, CTO at John Snow Labs. Solving real-world problems in healthcare, life sciences and related fields with AI and NLP. The early adoption patterns of generative AI (GenAI)—dumping ...

Abstract: Multi-Agent Reinforcement Learning (MARL) has proven to be effective in learning cooperative policies, where agents learn decentralized policies, sharing the same network parameters, through ...