Content tagged with "machine learning" (5)

You implement backprop, attention, and a GPT from scratch with no frameworks, and by the end you actually understand what the machine is doing instead of just calling library functions.

Karpathy's dense, opinionated survey of everything that changed in language models over 2025, written by someone who has built these systems himself.

The clearest visual explanation of how Transformers actually work, from self-attention to positional encodings, now referenced by courses at Stanford, Harvard, and MIT.

Karpathy builds an autograd engine from nothing, one line at a time, until backprop is something you could re-derive yourself instead of a formula you take on faith.

Anthropic's interpretability team looks inside the model and catches it planning several words ahead and reasoning in a concept space shared across languages.