The eminent Prof. Dawn Song joins me on the keynote stage of the Open Data Science Conference (ODSC) West in San Fran for a exceptionally deep, live episode on Responsible Decentralized Intelligence.
Dawn:
• Leads trailblazing research at the intersection of deep learning A.I. and decentralized systems like the blockchain.
• Has been Professor in the Computer Science Division of University of California, Berkeley for 15 years.
• Is Founder of Oasis Labs, a data privacy startup.
• Co-directs the Berkeley Center on Responsible Decentralized Intelligence.
• Is part of the illustrious Berkeley AI Research (BAIR) Lab.
• Has authored 300+ papers that have been cited over 80,000 times!
• Has won countless major awards including a MacArthur Fellowship ("genius grant").
Today’s episode is a deeply technical one that will appeal primarily to practitioners like data scientists, but it does have take-away points that will allow any interested listener to become abreast of the massive emerging potential of decentralized intelligence.
In this episode, Prof. Song details:
• What decentralized intelligence is and how it relates machine learning (particularly deep learning) to other emerging technologies like the blockchain, differential privacy, federated learning, and homomorphic encryption.
• What a “Responsible Data Economy” would look like, with specific real-world examples from her applications of her research to industry.
• Specific resources that she has developed to allow data scientists and software developers to easily develop and deploy privacy-preserving machine learning applications.
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