Chapter
Exploring the Intersection of Computer Science and Biology
2:36:11 - 2:43:47 (07:36)
The intersection of computer science and biology has given rise to the idea that algorithms can be very explanatory in fields like ant colony behavior. There is still uncertainty around where a smooth analysis fits into this and its relationship with the noise in the system, but this can be elucidated by deeper mathematics that are currently being obfuscated.
Clips
The speaker shares their theory on how the proof of P not equals to NP may eventually happen by obfuscating underlying mathematics.
2:36:11 - 2:37:52 (01:41)
Summary
The speaker shares their theory on how the proof of P not equals to NP may eventually happen by obfuscating underlying mathematics.
ChapterExploring the Intersection of Computer Science and Biology
Episode#166 – Cal Newport: Deep Work, Focus, Productivity, Email, and Social Media
PodcastLex Fridman Podcast
The host discusses contention resolution and the source coding theorem, explaining how there may be another representation of the Turing machine.
2:37:52 - 2:39:34 (01:41)
Summary
The host discusses contention resolution and the source coding theorem, explaining how there may be another representation of the Turing machine. He also mentions a new paper he has submitted on the same problem.
ChapterExploring the Intersection of Computer Science and Biology
Episode#166 – Cal Newport: Deep Work, Focus, Productivity, Email, and Social Media
PodcastLex Fridman Podcast
The speaker talks about the explanatory power of algorithms in understanding complex biological systems, and how fundamental ideas are all interconnected in a kind of evolutionary tree.
2:39:34 - 2:43:47 (04:13)
Summary
The speaker talks about the explanatory power of algorithms in understanding complex biological systems, and how fundamental ideas are all interconnected in a kind of evolutionary tree.