The Model Context Protocol (MCP) enables AI agents to interact with external tools across hybrid environments but introduces critical security vulnerabilities, including identity theft, data leakage, ...
A growing number of organizations are embracing Large Language Models (LLMs). LLMs excel at interpreting natural language, ...
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; ...
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 ...
When your mcp client talks to a server—maybe a retail bot checking inventory levels—they usually do a "handshake" to agree on a secret key. If you use ML-KEM, that handshake stays safe even if a ...
My summer "AI email misadventures with PR firms" led me to fresh ideas on the realities of AI agents and how to get RAG use cases right. This brought us smack into "context engineering," or "the ...
Draup, a global leader in enterprise talent intelligence, today announced that its real-time workforce and labor market data ...
Is the Model Context Protocol (MCP) on the verge of obsolescence? For years, MCP has been a cornerstone in AI agent design, offering a standardized way to integrate tools and manage interactions. But ...
Explore post-quantum cryptography in federated learning for Model Context Protocol training. Learn about quantum vulnerabilities, security measures, and real-world applications.
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