Robots that learn are an exciting path forward, yet there are differing approaches and opinions on how to make progress. The event brought together a diverse set of people from both robotics and machine learning communities as well as academics and industry leaders to create a platform to exchange ideas and address open questions in building complex robot systems.
Robots that learnare a development that will allow robots to become part of our everyday lives. While we have some ideas on how to get there, we think it is important to engage with people from other organizations and disciplines to exchange and discuss ideas. Creating these robots is inherently a multidisciplinary approach—it not only requires technical expertise, but also a deeper understanding of how these robots can be deployed safely and interact with humans in the real world.
We hosted ~80 external attendees at our office and ~200 people joined remotely via our livestream throughout the day. We had attendees from industry labs like Google, Facebook, and NVIDIA in addition to students, postdocs and professors from universities likeStanford(opens in a new window),UC Berkeley(opens in a new window),CMU(opens in a new window)andMIT(opens in a new window). We also had hobbyists, artists, roboticists, and machine learning researchers in the crowd.
Since the event was hosted at our office, we took the opportunity to perform alive demo(opens in a new window)of our humanoid robot hand manipulating a block using vision and reinforcement learning.
We were excited to show the hand to people and have the OpenAI Robotics team “on hand” to answer their questions! We hope to do this again in the future as it is a very different experience to see this in person.
We were extremely pleased with the outcome of the event—this was an experimental format and our expectations were definitely exceeded. The talks during the day led to interesting discussions within our team and resulted in some new ideas (e.g., self-supervision) and perspectives (e.g., traditional robotics vs deep learning robotics). After chatting with the participants and speakers, it was clear everyone felt they benefited from this event and left with a shared understanding of the diversity in the different approaches to solving the same problems. Given this feedback, we intend to repeat this format in the future, possibly as an annual symposium. We’ll share details about upcoming events at a later date.
If you would like to help us do research on robots that learn, please get in touch.
_Thanks to Loren Kwan, Diane Yoon, and Maddie Hall for co-organizing the event, to all the OpenAI staff volunteers, and to Blake Tucker for filming and photography._
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