ARPA-H and America’s Health: Pursuing High-Risk/High-Reward Research to Improve Health Outcomes for All
Dr. Andy Kilianski will provide an overview of ARPA-H, a new U.S. government funding agency pursuing R&D for health challenges. He will review the unique niche occupied by ARPA-H within the Department of Health and Human Services and how ARPA-H is already partnering with academia and industry to transform health outcomes across the country. Discussion [...]
Scaling up Robot Skill Learning with Generative Simulation
Abstract: Generalist robots need to learn a wide variety of skills to perform diverse tasks across multiple environments. Current robot training pipelines rely on humans to either provide kinesthetic demonstrations or program simulation environments with manually-designed reward functions for reinforcement learning. Such human involvement is an important bottleneck towards scaling up robot learning across diverse [...]
Unlocking Generalization for Robotics via Modularity and Scale
Abstract: How can we build generalist robot systems? Looking at fields such as vision and language, the common theme has been large scale end-to-end learning with massive, curated datasets. In robotics, on the other hand, scale alone may not be enough due to the significant multimodality of robotics tasks, lack of easily accessible data and [...]