MLCommons’ David Kanter, NVIDIA’s Daniel Galvez on Publicly Accessible Datasets - Ep. 167

In deep learning and machine learning, having a large enough dataset is key to training a system and getting it to produce results.

So what does a ML researcher do when there just isn’t enough publicly accessible data?

Enter the MLCommons Association, a global engineering consortium with the aim of making ML better for everyone.

MLCommons recently announced the general availability of the People’s Speech Dataset, a 30,000 hour English-language conversational speech dataset, and the Multilingual Spoken Words Corpus, an …

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