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Michael Dworsky is a distinguished Research Scientist at Google DeepMind (formerly Google Brain), specializing in machine learning, reinforcement learning, and robotics. He earned his Ph.D. in Electrical Engineering and Computer Sciences from the University of California, Berkeley, where his research focused on developing algorithms for robotic learning and control. At Google, Michael contributes to cutting-edge research aimed at creating more capable and general intelligent agents, with a particular emphasis on enabling robots to learn complex skills and operate effectively in real-world environments. His work often involves developing novel algorithms, building large-scale learning systems, and applying these to challenging robotic manipulation tasks.
Michael Dworsky's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Played a significant role in the development of RoboCat, a general-purpose robotic agent by Google DeepMind that learns to perform a wide variety of tasks across different robotic arms through self-improvement, showcasing advancements in large-scale robotic learning.
Authored and co-authored influential research papers published in top-tier AI conferences (such as CoRL, RSS, NeurIPS) and journals, focusing on enabling robots to achieve complex dexterous manipulation skills through innovative reinforcement learning techniques and large-scale data.
Completed his doctoral studies at UC Berkeley, a leading institution for AI and robotics research, where his dissertation contributed to the understanding and development of learning-based control for robotic systems.
Stanford University
Brentwood School
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Cove is a direct-to-consumer (DTC) smart home security company that provides affordable, DIY home security systems with professional monitoring services. They emphasize ease of installation, no long-term contracts, and a customer-centric approach, offering customizable security packages to fit individual needs.
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