Marktechpost iconMarktechpostSep 5, 2026

Adaption Labs Introduces ‘Invent a Dataset’: Training Data Generated From a Task Description, Not a Seed Corpus

A single datasets.invent call sets domains, row count, output format, and language expansion, and the rows download as JSONL, JSON, CSV, or Parquet. The dataset ID then passes straight into AutoScientist, closing an intent-to-trained-model loop.

Adaption Labs Introduces ‘Invent a Dataset’: Training Data Generated From a Task Description, Not a Seed Corpus
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A single datasets.invent call sets domains, row count, output format, and language expansion, and the rows download as JSONL, JSON, CSV, or Parquet.

The dataset ID then passes straight into AutoScientist, closing an intent-to-trained-model loop.

There is no seed corpus, no schema design, and no labeling guide.

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A single datasets.invent call sets domains, row count, output format, and language expansion, and the rows download as JSONL, JSON, CSV, or Parquet. The dataset ID then passes straight into AutoScientist, closing an intent-to-trained-model loop. There is no seed corpus, no schema design, and no labeling guide.

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There is no seed corpus, no schema design, and no labeling guide.

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