Chapter
Building a Platform for Secure and Privacy-Preserving Computation for Responsible Data Economy
1:21:11 - 1:37:00 (15:48)
Oasis Labs is developing a platform for responsible data economy that combines secure and privacy-preserving computation with an immutable log of user ownership and data usage policies. The program synthesis and adversarial machine learning fields are focused on by Oasis Labs' effort to build intelligent machines.
Clips
The use of digital currency has brought up issues of data privacy and ownership of digital assets, particularly in decentralized systems like distributed ledgers.
1:21:11 - 1:26:03 (04:51)
Summary
The use of digital currency has brought up issues of data privacy and ownership of digital assets, particularly in decentralized systems like distributed ledgers. It is important to have a constructive dialogue between the different sides to come up with viable solutions.
ChapterBuilding a Platform for Secure and Privacy-Preserving Computation for Responsible Data Economy
Episode#95 – Dawn Song: Adversarial Machine Learning and Computer Security
PodcastLex Fridman Podcast
In this podcast, the concept of consensus protocols and public ledgers is discussed.
1:26:03 - 1:30:23 (04:19)
Summary
In this podcast, the concept of consensus protocols and public ledgers is discussed. The importance of ensuring a consistent and immutable view on the ledger is highlighted, and different consensus mechanisms are explained.
ChapterBuilding a Platform for Secure and Privacy-Preserving Computation for Responsible Data Economy
Episode#95 – Dawn Song: Adversarial Machine Learning and Computer Security
PodcastLex Fridman Podcast
Oasis Labs is working on building a platform for a responsible data economy that combines different technologies for securely and privately preserving computation and providing users with ownership of their data and policies for its usage.
1:30:23 - 1:37:00 (06:36)
Summary
Oasis Labs is working on building a platform for a responsible data economy that combines different technologies for securely and privately preserving computation and providing users with ownership of their data and policies for its usage. The founder, Dawn Song, shares her motivation for focusing on program synthesis and adversarial machine learning in her transition from security to AI and machine learning.