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.

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

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.

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

Backed by The Chainsmokers, the ProducerAI platform allows users to write natural language requests — something like “make a ...

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 ...

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

Sequels carry certain expectations with them, like the promise of building on the promise of what came before and correcting past mistakes. Bandai Namco’s Code Vein 2 is exceptional in that it manages ...

This study is a valuable contribution that comprehensively identifies and characterizes LC3B-binding peptides through a bacterial cell-surface display screen covering approximately 500,000 human ...