Confidential Computing Advances
Organizations can now leverage large language models without exposing proprietary data, thanks to advancements in confidential computing. The integration of GPU enclaves in cloud environments is still evolving, presenting both challenges and opportunities for optimizing workflows. With a solid foundation built on research from UC Berkeley, there's a promising outlook for developing efficient systems that prioritize data privacy while harnessing the power of new architectures.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
701: Generative A.I. without the Privacy Risks — with Prof. Raluca Ada Popa
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