Adhiraj Ghosh says task-adaptive batch sampling delivered a 3.33x pretraining compute multiplier

pratyushmaini · x · 2026-07-24

Adhiraj Ghosh’s Summer of Data talk covers task-adaptive data curation and adaptive batch sampling for pretraining.

• The core idea is to diversify training batches by concept/task, improving data coverage instead of sampling naively.
• The talk claims this approach produced a 3.33x compute multiplier in pretraining, implying much better efficiency for the same training budget.
• The post links the full talk and frames it as the fifth session in DatologyAI’s Summer of Data seminar series.

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