Chapter
The Role of Categorization and Understanding in Problem Solving
20:06 - 26:03 (05:56)
The usefulness of categorization and its limitations in problem-solving are discussed, with a focus on the role of self-supervised learning versus supervised learning.
Clips
The idea of a perfect taxonomy or categorization system is a flawed one, as any categorization can always be blended, leading to the creation of new categories.
20:06 - 22:59 (02:52)
Summary
The idea of a perfect taxonomy or categorization system is a flawed one, as any categorization can always be blended, leading to the creation of new categories. Machine learning approaches often assume that it is possible to create a perfect taxonomy, but this may not be possible.
ChapterThe Role of Categorization and Understanding in Problem Solving
Episode#206 – Ishan Misra: Self-Supervised Deep Learning in Computer Vision
PodcastLex Fridman Podcast
The categorization and classification of data is still useful for solving problems, but self-supervised learning should be the foundation upon which it sits.
22:59 - 26:03 (03:04)
Summary
The categorization and classification of data is still useful for solving problems, but self-supervised learning should be the foundation upon which it sits. Categorical relationships provide useful taxonomies, but it is the self-supervised understanding of concepts that will ultimately allow for deeper problem-solving capabilities.