Chapter
Building Common Sense Understanding Through Interactive Learning
03:00 - 14:51 (11:50)
The process of distilling a common sense understanding of the world through machine learning is a big challenge, as it requires the capability to take an unstructured mass of experience and transform it into knowledge. However, with interactive learning and continuous experience, acquiring a common sense understanding is much more likely.
Clips
Exploring the complex and unpredictable nature of robot capabilities as opposed to human capabilities, and the factors that affect them in day-to-day tasks.
03:00 - 06:44 (03:43)
Summary
Exploring the complex and unpredictable nature of robot capabilities as opposed to human capabilities, and the factors that affect them in day-to-day tasks.
ChapterBuilding Common Sense Understanding Through Interactive Learning
Episode#108 – Sergey Levine: Robotics and Machine Learning
PodcastLex Fridman Podcast
The challenge for modern machine learning is to utilize unstructured mass of experience to distill out something that looks like a common sense understanding of the world.
06:44 - 11:38 (04:54)
Summary
The challenge for modern machine learning is to utilize unstructured mass of experience to distill out something that looks like a common sense understanding of the world. However, it is a big challenge to take this unstructured mass of experience and distill out something that looks like a common sense understanding of the world.
ChapterBuilding Common Sense Understanding Through Interactive Learning
Episode#108 – Sergey Levine: Robotics and Machine Learning
PodcastLex Fridman Podcast
The value of experience and continuous, real-world interaction for obtaining common sense understanding in AI as compared to relying solely on machine learning algorithms.
11:38 - 14:51 (03:12)
Summary
The value of experience and continuous, real-world interaction for obtaining common sense understanding in AI as compared to relying solely on machine learning algorithms.