Why the Future of Machine Learning is Open Source with Huggingface’s Clem Delangue
After starting as a talking emoji companion, Hugging Face is now an organizing force for the open source AI research ecosystem. Its models are used by companies such as Apple, Salesforce and Microsoft, and it's working to become the GitHub for ML.
This week on the podcast, Sarah Guo and Elad Gil talk to Clem Delangue, co-founder and CEO of Hugging Face. Clem shares how they shifted away from their original product, why every employee at Hugging Face is responsible for community-building, the modalities he's most interested in, and what role open source has in the AI race.
Hugging Face website
The $2 Billion Emoji: Hugging Face Wants To Be Launchpad For A Machine Learning Revolution - Forbes
[01:53 ] - how Clem first became interested in ML, being shouted at by eBay sellers, and the foretelling of the end of barcode scanning
[3:34 ] - early iterations of Hugging Face, trying to make a less boring AI tamagotchi, and switching directions towards open source tools
[5:36 ] - advice for founders considering a change in direction, 30%+ experimentation
[7:39 ] - 1st users, MLTwitter, approach to community
[10:47 ] - enterprise ML maturity, days to production
[12:54 ] - open source vs. proprietary models
[15:56 ] - main model tasks, architectures and sizes
[19:12 ] - decentralized infrastructure, data opt out
[24:16 ] - Hugging Face’s business model, GitHub
[28:09 ] - What Clem is excited about in AI