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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Python Nicknamed 'The Baroness' Breaks Record for World's Longest Snake with Over 23 Feet of Scales
"This snake could easily swallow at least a calf, if not an adult cow," an explorer and natural history photographer said of ...
ThreatsDay Bulletin tracks active exploits, phishing waves, AI risks, major flaws, and cybercrime crackdowns shaping this week’s threat landscape.
Melissa Horton is a financial literacy professional. She has 10+ years of experience in the financial services and planning industry. NicoElNino Simple random sampling gives each member of a ...
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Google AI Studio: What is it and how does it work?
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