Chapter
The Role of Locality and Trust in Privacy Discussions
58:09 - 1:04:48 (06:38)
The speaker discusses the importance of building trust and locality within communities to facilitate productive discussions about topics such as privacy.
Clips
The future of privacy may require new structures, technologies and a lot of money to be made in order to provide useful services to people, similar to how the introduction of electricity required major changes and advancements.
58:09 - 59:48 (01:38)
Summary
The future of privacy may require new structures, technologies and a lot of money to be made in order to provide useful services to people, similar to how the introduction of electricity required major changes and advancements.
ChapterThe Role of Locality and Trust in Privacy Discussions
Episode#74 – Michael I. Jordan: Machine Learning, Recommender Systems, and the Future of AI
PodcastLex Fridman Podcast
The speaker reflects on the value of trust and locality in online discussions, as opposed to the anonymity of platforms like Facebook, which can often be a "total waste of time."
59:48 - 1:01:51 (02:03)
Summary
The speaker reflects on the value of trust and locality in online discussions, as opposed to the anonymity of platforms like Facebook, which can often be a "total waste of time." They question if humans are fundamentally good in light of the negative behavior often observed in comment sections.
ChapterThe Role of Locality and Trust in Privacy Discussions
Episode#74 – Michael I. Jordan: Machine Learning, Recommender Systems, and the Future of AI
PodcastLex Fridman Podcast
The progress of technology allows individuals to be the best versions of themselves, while still maintaining their innate goodness as humans.
1:01:52 - 1:03:07 (01:15)
Summary
The progress of technology allows individuals to be the best versions of themselves, while still maintaining their innate goodness as humans. Technology can also open us up to more perspectives and greater understanding.
ChapterThe Role of Locality and Trust in Privacy Discussions
Episode#74 – Michael I. Jordan: Machine Learning, Recommender Systems, and the Future of AI
PodcastLex Fridman Podcast
This episode discusses the difference between optimization and sampling paradigms in mathematics and how they relate to finding the best point in a distribution.
1:03:07 - 1:04:48 (01:40)
Summary
This episode discusses the difference between optimization and sampling paradigms in mathematics and how they relate to finding the best point in a distribution. While optimization focuses on finding a single optimum point based on a criterion function, the sampling paradigm looks at the entire distribution.