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

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.

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.

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.

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

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Operation Dream Job is evolving once again, and now comes through malicious dependencies on bare-bones projects.

Claude Code vs ChatGPT Codex compared for performance, pricing, workflows, and privacy to find the best AI coding assistant ...

Researchers found that AI chatbots like ChatGPT, Claude, and Gemini are not good at producing secure passwords.

Why write ten lines of code when one will do? From magic variable swaps to high-speed data counting, these Python snippets will transform your code.

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