A new study reveals that top models like DeepSeek-R1 succeed by simulating internal debates. Here is how enterprises can harness this "society of thought" to build more robust, self-correcting agents.
A new technical paper titled “Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration” was published by researchers at Harvard University and Google research groups.
New development framework and services fast track multi-agent adoption by enabling interoperability and scalability to transform business processes TEANECK, N.J., Jan. 16, 2025 /PRNewswire/ -- ...
As AI-assisted coding becomes more common, a new pattern is emerging: multi-agent workflows. A multi-agent workflow refers to using various AI agents in parallel for specific software development life ...
This weekend Open AI has introduced Swarm a “educational framework exploring ergonomic, lightweight multi-agent orchestration“. Evening developers to use the experimental sample framework to build ...
How event-driven design can overcome the challenges of coordinating multiple AI agents to create scalable and efficient reasoning systems. While large language models are useful for chatbots, Q&A ...
In March, AWS announced the general availability of its new multi-agent capabilities, bringing the technology into the hands of businesses across almost every industry. Until now, organizations have ...
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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