Sean Peter Michael🇻🇦

🚨Leave Netflix tonight. Watch this 2 h 34 min Stanford class. It's the clearest, most complete, and brutally honest explanation out there on how ChatGPT and Claude are really built. From Tokenization and BPE to the Transformer architecture, the training pipeline, and the next-token decoder. No fluff. No marketing. Just the truth. Doesn't matter if you've never touched a line of AI code or if you spend your days launching Agents: by the end, you'll suddenly connect a ton of pieces you've been trying to fit together for years. The real core boils down to this: How text turns into numbers the model can "eat" (BPE tokenization) The sole mission of a language model: predict the next token How the Transformer uses Attention so tokens can pass messages to each other In training, the NLL loss pushes the probability of the entire sequence In generation, the decoder builds the response token by token The big-picture view that takes most people years to form… this class delivers it to you complete in one sitting. Free up your time. This could be, no exaggeration, the most valuable class you watch this month.