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.

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.

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 ...

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