Effective inventory management for today's food supply chain businesses can be challenging – managers must ensure adequate stock for daily order fulfillment, avoid oversupply of highly perishable ...

An introduction to the open-source LMOS platform and its Kotlin-based Arc framework for building, deploying, and managing ...

What’s needed is a “paved road” for agent connectivity: infrastructure that handles tool authentication, rate-limiting and monitoring consistently across all agent tools. This lets developers focus on ...

Capital One, committed to staying at the forefront of emerging technologies, recently launched a production-grade, state-of-the-art multi-agent AI system to enhance the car-buying ...

The architecture of the MG agent are designed, which processes the three control layers via information exchange among neighbouring agents. The proposed framework is validated in a ...

As digital transformation accelerates, the real challenge for businesses is no longer just experimenting with AI but scaling it strategically to stay competitive. An AI-first approach goes beyond ...

To flexibly and robustly handle diverse problems, AI systems can leverage dual-process theories of human cognition that ...

AI innovation in agentic AI, agents and new products in 2025 is led by AWS, Databricks, Dataiku, Google Cloud, GitHut, IBM, ...

AI disclosure requirements are essential to managing risk as artificial intelligence plays a growing role in the power grid.

VB Transform brings together the people building real enterprise AI strategy. Learn more Palo Alto-based Catio was awarded “Coolest Technology” at VentureBeat Transform 2025 in San Francisco on ...

The multi-agent system is the optimal solution to complex intelligent problems. In accordance with the game theory, the concept of loyalty is introduced to analyze the relationship between agents' ...