When does a text predictor become an assistant?
Next-token prediction teaches continuation. Compare how later training shapes responses to a user; the distinction does not prescribe a single post-training algorithm.
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From predicting a token to using a language model →Building a predictor makes its training target concrete. Using a trained model shows how context and instructions put that predictor to work.What does dropout do inside a GPT training loop? →The subnetworks interpretation explains why units are omitted during training. The implementation shows where the random masking happens in an actual model.What does attention add to layered activations? →A feedforward network propagates activations through its layers. Causal attention lets each position combine information from earlier tokens.
Compare the passages
it takes the model from being a document completer to a question answererwe swap out the data set now and we train on these Q&A documents