The Omniglot challenge: a 3-year progress report

Brenden M. Lake, Ruslan Salakhutdinov, Joshua B. Tenenbaum

Research output: Contribution to journalReview articlepeer-review


Three years ago, we released the Omniglot dataset for one-shot learning, along with five challenge tasks and a computational model that addresses these tasks. The model was not meant to be the final word on Omniglot; we hoped that the community would build on our work and develop new approaches. In the time since, we have been pleased to see wide adoption of the dataset. There has been notable progress on one-shot classification, but researchers have adopted new splits and procedures that make the task easier. There has been less progress on the other four tasks. We conclude that recent approaches are still far from human-like concept learning on Omniglot, a challenge that requires performing many tasks with a single model.

Original languageEnglish (US)
Pages (from-to)97-104
Number of pages8
JournalCurrent Opinion in Behavioral Sciences
StatePublished - Oct 2019

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Psychiatry and Mental health
  • Behavioral Neuroscience


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