Nithin Kamath highlights how LLMs evolved from hallucinations to Linus Torvalds-approved code, democratizing tech and transforming software development.

Earlier, Kamath highlighted a massive shift in the tech landscape: Large Language Models (LLMs) have evolved from “hallucinating" random text in 2023 to gaining the approval of Linus Torvalds in 2026.

Its use results in faster development, cleaner testbenches, and a modern software-oriented approach to validating FPGA and ASIC designs without replacing your existing simulator.

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.

North Korean IT operatives use stolen LinkedIn accounts, fake hiring flows, and malware to secure remote jobs, steal data, and fund state programs.

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

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.

An AI agent got nasty after its pull request got rejected. Can open-source development survive autonomous bot contributors?

ThreatsDay Bulletin tracks active exploits, phishing waves, AI risks, major flaws, and cybercrime crackdowns shaping this week’s threat landscape.

QR codes have quietly become the remote control for everyday life, from restaurant menus to parking meters to office sign-ins. That convenience is exactly why security experts keep repeating a simple ...