Show HN: How LLMs Work – Interactive visual guide based on Karpathy's lecture

This technical guide demystifies how large language models are built, from data collection through training to inference, revealing that model quality depends critically on data curation, tokenization efficiency, and massive-scale transformer training. For IT leaders, understanding LLM architecture is essential for making informed decisions about AI adoption, cloud infrastructure requirements, and vendor selection as these models become central to enterprise operations. The exponential improvement in training efficiency and accessibility means organizations must now actively evaluate LLM capabilities and integration strategies rather than treating them as emerging technologies.