Nov 4, 2021

DeepMind takes next step in robotics research

Posted by in categories: business, physics, robotics/AI

DeepMind is mostly known for its work in deep reinforcement learning, especially in mastering complicated games and predicting protein structures. Now, it is taking its next step in robotics research.

According to a blog post on DeepMind’s website, the company has acquired the rigid-body physics simulator MuJoCo and has made it freely available to the research community. MuJoCo is now one of several open-source platforms for training artificial intelligence agents used in robotics applications. Its free availability will have a positive impact on the work of scientists who are struggling with the costs of robotics research. It can also be an important factor for DeepMind’s future, both as a science lab seeking artificial general intelligence and as a business unit of one of the largest tech companies in the world.

Simulation platforms are a big deal in robotics. Training and testing robots in the real world is expensive and slow. Simulated environments, on the other hand, allow researchers to train multiple AI agents in parallel and at speeds that are much faster than real life. Today, most robotics research teams carry out the bulk of training their AI models in simulated environments. The trained models are then tested and further fine-tuned on real physical robots.

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