NZ This 1-Hour Andrej Karpathy Lecture Explains Modern AI Better Than Most Courses

If you're building with LLMs, Generative AI, AI Agents, or Transformers, this Andrej Karpathy Stanford lecture is worth your time. In this session, Karpathy explains the evolution of programming and AI — from traditional software to neural networks, Transformers, GPTs, and what he calls Software 3.0. One of the most fascinating ideas in the lecture is how the 2017 “Attention Is All You Need” paper changed everything. The industry moved from complex recurrent architectures toward a surprisingly powerful idea: Remove the RNN. Keep attention. That architecture eventually became the foundation behind GPT and much of modern Generative AI. Karpathy also explains an equally important shift: Software 1.0 → Design the algorithm Software 2.0 → Design the dataset Software 3.0 → Design the prompt And perhaps the most provocative idea: “The hottest new programming language is English.” What you'll learn → Why traditional programming wasn't enough for many AI problems → How neural networks changed software development → Why attention became such an important breakthrough → How the Transformer architecture emerged → Why Transformers work across text, images, speech and other modalities → How GPTs can behave like general-purpose computers → Why prompts can be thought of as programs → Software 1.0 vs Software 2.0 vs Software 3.0 → Why natural language is becoming a new interface for programming → Where AI systems may evolve next If you're an AI engineer, software architect, developer, ML engineer, founder, or anyone building with LLMs, this lecture provides some of the foundations behind the technology we're using today. Watch it all the way through — there are insights here that are easy to miss if you only focus on the latest AI frameworks.