For robots to keep up with the pace of technological innovation, machine learning has become paramount. While robots are already effective at alleviating the manual operation of routine tasks, an intelligent robot should also be able to process their commands with future actions in mind.
For robots to keep up with the pace of technological innovation, machine learning has become paramount. While robots are already effective at alleviating the manual operation of routine tasks, an intelligent robot should also be able to process their commands with future actions in mind.
We are announcing the release of our state-of-the-art off-policy model-free reinforcement learning algorithm, soft actor-critic (SAC). This algorithm has been developed jointly at UC Berkeley and Google, and we have been using it internally for our robotics experiment.
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For robots to keep up with the pace of technological innovation, machine learning has become paramount. While robots are already effective at alleviating the manual operation of routine tasks, an intelligent robot should also be able to process their commands with future actions in mind.
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We are announcing the release of our state-of-the-art off-policy model-free reinforcement learning algorithm, soft actor-critic (SAC). This algorithm has been developed jointly at UC Berkeley and Google, and we have been using it internally for our robotics experiment.
Researchers built the first visual SLAM processor on a single chip that provides highly accurate, low-power, and real-time results.
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