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Eric Yuan's Comparison of Machine Reading Comprehension Datasets.Qi Wu et al.'s Visual Question Answering: A survey of Methods and Datasets.Gabriel Synnaeve's WER are We collation of speech recognition performance data.The Swedish Computer Chess Association's History of Computer Chess performance.Katja Grace's Algorithmic Progress in Six Domains.

Sarah Constantin's Performance Trends in AI.

Jack Clark and Miles Brundage's collection of AI progress measurements.

Rodrigo Benenson's "Who is the Best at X / Are we there yet?" collating machine vision datasets & progress.

Contact: contributions from: Yann Bayle, Owain Evans, Gennie Gebhart and Dustin Schwenk. Original authors: Peter Eckersley and Yomna Nasser at EFF. To begin with, we're focused on gathering it. You can use this Notebook to see how things are progressing in specific subfields or AI/ML as a whole, as a place to report new results you've obtained, as a place to look for problems that might benefit from having new datasets/metrics designed for them, or as a source to build on for data science projects.Īt EFF, we're ultimately most interested in how this data can influence our understanding of the likely implications of AI. This pilot project collects problems and metrics/datasets from the AI research literature, and tracks progress on them.