This episode examines Guided Policy Search, a 2013 method from Sergey Levine and Vladlen Koltun that lets flexible neural-network policies control robots without falling into the poor local optima…
What will it take to build robots that can truly operate in the real world? 🤖 In this episode of SparX, Mukesh Bansal is joined by Sergey Levine, computer scientist and co-founder of Physical…
Sergey Levine is one of the world's top robotics researchers and co-founder of Physical Intelligence. We talked about where humanoid robotics is today, thoughts on the Chinese robotics ecosystem, and…
Physical AI looks closer than ever. But the hardest part in robotics is not getting a machine to do one impressive task on camera. It is building systems that can improve from real-world experience,…
This episode is sponsored by Modulate. Most voice AI focuses on transcription. Velma takes it further by actually understanding conversations, analyzing tone, timing, stress, and intent using its…
My guest today is Sergey Levine, a professor at UC Berkeley and co-founder of Physical Intelligence. The company is building robotic foundation models designed to control any embodied system to do…
Karol Hausman is the co-founder and CEO of Physical Intelligence, a robotics company building a general-purpose “AI brain for the physical world.” The company has raised more than $1 billion in…
🎙️ Sergey Levine——全球机器人强化学习（RL）与具身智能领域的权威学者，加州大学伯克利分校-电气工程与计算机科学系副教授，明星机器人公司Physical Intelligence（PI）联合创始人。他以18万+谷歌学术引用的学术影响力，主导开发了谷歌机器人大模型RT-1、RT-2及跨本体数据集RT-X，其提出的“热启动强化学习（WSRL）”…
Sergey Levine, one of the world’s top robotics researchers and co-founder of Physical Intelligence, thinks we’re on the cusp of a “self-improvement flywheel” for general-purpose robots. His median…
In this episode of IA Odyssey , we explore a bold new approach in training intelligent AI agents: letting them invent their own problems. We dive into “Self-Challenging Language Model Agents” by…
Today, we're joined by Sergey Levine, associate professor at UC Berkeley and co-founder of Physical Intelligence, to discuss π0 (pi-zero), a general-purpose robotic foundation model. We dig into the…
Join host Craig Smith on episode #176 of Eye on AI as he dives deep into the realm of robotic artificial intelligence with Sergey Levine, associate professor in the Department of Electrical…
Sergey Levine, an assistant professor of EECS at UC Berkeley, is one of the pioneers of modern deep reinforcement learning. His research focuses on developing general-purpose algorithms for…
Sergey Levine reports on the latest in the Mercury-6 project. Lexman and Sergey discuss the effects of hypervitaminosis on the team, as well as what could happen if a subplot develops.
Today we’re taking a deep dive into the latest and greatest in the world of Reinforcement Learning with our friend Sergey Levine, an associate professor, at UC Berkeley. In our conversation with…
Lexman interviews Sergey Levine, a data scientist who is well known for his work with scraping. They discuss scraping techniques, Maple and squamules.
Lexman and Sergey Levine discuss the role that dioxanes play in our everyday lives. They also explore the use of lambda symbols in programming and discuss the difference between lambdas andPenrith…
Lexman Artificial interviews Sergey Levine about meristem, blusters, and troubleshooting.
In Episode One of Season Two, Host Pieter Abbeel is joined by guest (and close collaborator) Sergey Levine, professor at UC Berkeley, EECS. Sergey discusses the early years of his career, how Andrew…
In episode 11 of The Gradient Podcast, we interview Sergey Levine, a professor at Berkeley whose research focuses on machine learning for decision making and control, with an emphasis on deep…
Clip" Sergey Levine: Generalization In Reinforcement Learning VS Supervised Learning"
Clip "Sergey Levine: Learning Based Method In Soft Robots"
Sergey Levine: "Is Reinforcement Learning Sufficient For Designing Generic And Adaptable Robots?" Video format: https://youtu.be/UyOGMqMYarE
Os traemos nuestra primera tertulia, en la que participan Luis Martín y Néstor Álvaro, y en la que hablamos de la aplicación de Machine Learning a la Robótica de la mano de una entrevista de Lex…
Sergey Levine is a professor at Berkeley and a world-class researcher in deep learning, reinforcement learning, robotics, and computer vision, including the development of algorithms for end-to-end…
Today we're joined by Sergey Levine, an Assistant Professor at UC Berkeley. We last heard from Sergey back in 2017, where we explored Deep Robotic Learning. Sergey and his lab’s recent efforts have…
This week, I talk to Sergey Levine, one of the most prolific researchers in robot learning. We talked about developing a robot's sense of touch and about robot dreams and whether he believes we know…
The robots that have taken on tasks in the real world - which is to say the world where physics apply - are primarily programmed to do a specific job, such as welding a joint in a car or sweeping up…
This week we continue our Industrial AI series with Sergey Levine, an Assistant Professor at UC Berkeley whose research focus is Deep Robotic Learning. Sergey is part of the same research team as a…
In this episode, Audrow Nash interviews Sergey Levine, assistant professor at UC Berkeley, about deep learning on robotics. Levine explains what deep learning is and he discusses the challenges of…