An open standard that enables AI models to interact with tools, memory, and data in a structured, auditable way.

ZDNET's key takeaways Even the best AI models are challenged to carry out tasks via MCP.New benchmarks show models struggle ...

As AI development accelerates, organizations are under increasing pressure to move models from prototype to production securely and with scalability.

Imagine a world where your AI tools don’t just work for you but work with each other—seamlessly, intelligently, and without the frustration of endless custom integrations. This isn’t a distant dream; ...

Imagine you’ve trained or fine‑tuned a chatbot or an LLM, and it can chat comfortably without any serious hiccups. You feed it a prompt and it responds. However, it’s stuck in a bubble: It only knows ...

MCP certification is a hot topic in AI hiring. Here’s what courses are available now, when official certification might ...

For years, APIs have powered everything from SaaS dashboards to mobile apps. Now, a new contender—Model Context Protocol, or ...

The intelligence gap has closed. The real challenge for AI founders is no longer reasoning power. It is integration, memory, ...

Oracle announced that it is making available a GraphPipe protocol for transmitting tensor data used to create artificial intelligence (AI) models over a network. Available on Oracle’s implementation ...

More processors on SoCs means more sophisticated cache control. This article describes formal techniques for verifying cache coherency for the ARM AMBA AXI Coherency Extensions (ACE) protocol. Fig 1.