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EP192 Confidential + AI: Can AI Keep a Secret?

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Manage episode 442813032 series 2892548
Content provided by Anton Chuvakin. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anton Chuvakin or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Guest:

  • Nelly Porter, Director of PM, Cloud Security at Google Cloud

Topics:

  • Share your story and how you ended here doing confidential AI at Google?
  • What problem does confidential compute + AI solve and for what clients?
  • What are some specific real-world applications or use cases where you see the combination of AI and confidential computing making the most significant impact?
  • What about AI in confidential vs AI on prem? Should those people just do on-prem AI instead?
  • Which parts of the AI lifecycle need to be run in Confidential AI: Training? Data curation? Operational workloads?
  • What are the performance (and thus cost) implications of running AI workloads in a confidential computing environment?
  • Are there new risks that arise out of confidential AI?

Resources:

  continue reading

229 episodes

Artwork
iconShare
 
Manage episode 442813032 series 2892548
Content provided by Anton Chuvakin. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anton Chuvakin or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Guest:

  • Nelly Porter, Director of PM, Cloud Security at Google Cloud

Topics:

  • Share your story and how you ended here doing confidential AI at Google?
  • What problem does confidential compute + AI solve and for what clients?
  • What are some specific real-world applications or use cases where you see the combination of AI and confidential computing making the most significant impact?
  • What about AI in confidential vs AI on prem? Should those people just do on-prem AI instead?
  • Which parts of the AI lifecycle need to be run in Confidential AI: Training? Data curation? Operational workloads?
  • What are the performance (and thus cost) implications of running AI workloads in a confidential computing environment?
  • Are there new risks that arise out of confidential AI?

Resources:

  continue reading

229 episodes

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