Because self-supervised pretraining derives its targets automatically from the data, a corpus of ten trillion tokens can be used for pretraining without needing ten trillion human-provided labels.

True. Correct — the training signal is generated mechanically from the text's own structure, so corpus size is limited only by data availability and compute, not by how many examples humans can annotate.

Self-supervised pretraining objectives Interview Q&A

Self-supervised objective

An objective that derives its own training targets from the structure of the raw input itself, rather than from labels a human attached separately.

Example

In ‘The cat sat on the mat,’ the model sees ‘The cat sat on the’ and must predict mat — the target came from the text itself, no annotation required.

Why this scales

Because the target is carved out of the same raw text the model already has, every sentence in a massive corpus becomes a training example automatically. No human writes 'the answer is mat' — the pipeline generates it mechanically. This is what lets pretraining consume web-scale text: signal volume scales with raw text volume, not with annotator hours.

Myth

Self-supervised must mean there’s no real training signal — it’s basically the same as unsupervised learning, where the model just finds patterns with no target to be right or wrong about.

Reality

There is a genuine target at every step; it’s just built automatically from the input (e.g., a held-out token or masked span) instead of being labeled by a person. The model is still scored against a correct answer — that answer just wasn’t handwritten.

Self-supervised pretraining

Sourcelabels come from the data itself, e.g. the next token in the same sequence.
Scalegrows with raw text volume, since no human ever touches an example.

Supervised fine-tuning

Sourcelabels come from external annotation, e.g. a person marking sentiment.
Scalebounded by how many examples humans can label, so datasets stay much smaller.

Self-supervised pretraining objectives

Self-supervised objective

Why this scales

Sources

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