Tagged “Ai”

  1. Extending makemore with an MLP, and running some experiments to minimize validation loss

  2. A neural character-level bigram language model, optimized with gradient descent rather than counted from the training data.

  3. Generalizing the statistical bigram model to arbitrary n-grams, and using it as a vehicle to explore hyperparameter tuning.

  4. Building a statistical character-level bigram language model - the first step from raw autograd toward models that emulate natural language.

  5. Extending the autograd engine with more arithmetic operations and nonlinear activations, then building a small neural network library on top of it.

  6. Implementing a scalar-valued automatic differentiation engine from scratch. First post following Karpathy's Neural Networks: Zero to Hero.

  7. A response to Cal Newport's case against superintelligence, laying out where his rebuttal of Yudkowsky's existential-risk argument goes wrong.