Advancements in Machine Learning with Sergey Levine - #355
Published:Mar 9, 2020 20:16
•1 min read
•Practical AI
Analysis
This article highlights a discussion with Sergey Levine, an Assistant Professor at UC Berkeley, focusing on his recent work in machine learning, particularly in the field of deep robotic learning. The interview, conducted at NeurIPS 2019, covers Levine's lab's efforts to enable machines to learn continuously through real-world experience. The article emphasizes the significant amount of research presented by Levine and his team, with 12 papers showcased at the conference, indicating a broad scope of advancements in the field. The focus is on the practical application of AI in robotics and the potential for machines to learn and adapt independently.
Key Takeaways
Reference
“machines can be “out there in the real world, learning continuously through their own experience.””