Learn how Zero-Knowledge Proofs (ZKP) provide verifiable tool execution for Model Context Protocol (MCP) in a post-quantum world. Secure your AI infrastructure today.

AI safety tests found to rely on 'obvious' trigger words; with easy rephrasing, models labeled 'reasonably safe' suddenly fail, with attacks succeeding up to 98% of the time. New corporate research ...

See how we created a form of invisible surveillance, who gets left out at the gate, and how we’re inadvertently teaching the ...

AI, or Artificial Intelligence, was a creation of the tech community. Imagine the same community now getting worried about its own creation. It is exactly what’s happening today at various levels. But ...

A Python library with time-based pseudo-random number generation. Features a unique mathematical rounding module, distribution diagnostics, and essential utilities.

Explore Python Physics Lesson 19 and learn how the Monte Carlo method can approximate Pi with simple yet powerful simulations. In this lesson, we break down the Monte Carlo technique step by step, ...

IBM’s ( IBM) Software and Chief Commercial Officer, Rob Thomas, wrote in a Monday blog post that translating COBOL code isn’t equivalent to modernizing enterprise systems, emphasizing that platform ...

Create an rng object with np.random.default_rng(), you can seed it for reproducible results. You can draw samples from probability distributions, including from the binomial and normal distributions.

It’s a breakthrough in the field of random walks.

Learn how to secure Model Context Protocol (MCP) deployments with post-quantum cryptography and agile policy enforcement for LLM tools.

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...