What if the next generation of AI systems could not only understand context but also act on it in real time? Imagine a world where large language models (LLMs) seamlessly interact with external tools, ...

The Model Context Protocol (MCP) is redefining how artificial intelligence (AI) systems interact with external tools and services. By addressing the inherent limitations of large language models (LLMs ...

Even the best AI models are challenged to carry out tasks via MCP. New benchmarks show models struggle when tasks become more complex. More training of AI models is required that's specific to MCP use ...

Making inherently probabilistic and isolated large language models (LLMs) work in a context-aware, deterministic way to take real-world decisions and actions has proven to be a hard problem. As we ...

AI agents and agentic workflows are the current buzzwords among developers and technical decision makers. While they certainly deserve the community's and ecosystem's attention, there is less emphasis ...

As organizations push AI systems into production, IT teams are asking how to make models more dependable, secure and useful in real-world workflows. One approach gaining traction is the Model Context ...

Artificial intelligence has gone beyond being associated with highly complex algorithms or large amounts of data. Currently, the greatest complexity in artificial intelligence rests in the way answers ...

LLMs and AI tools have transformed nearly every industry, including marketing. We’ve become accustomed to AI’s ability to: But as these models evolve, their capabilities are entering a new phase with ...

The past ten years have seen incredible advancements in the realm of Artificial Intelligence, but paradoxically, some of the most overt shortcomings of AI are still based not on intelligence but on ...

Anthropic’s model context protocol (MCP), the ‘plug-and-play bridge for LLMs and AI agents’ to connect with external tools, has received a major update one year after its launch. The developer of ...