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We’re at a point where robots are becoming uncaged and we are trying to use them for more and more complex tasks, but it can be a challenge to efficiently prepare them for these new tasks. Robots are no longer operating in controlled environments that predetermine their actions, but are now using rich sensor inputs that all need to be integrated into their control systems.
Jumping on the synthetic data and simulation train, AWS recently launched WorldForge. This is their new simulation environment for robots and is quite impressive as it combines with the rest of AWS’ robotic and simulation services for everyone to use. For larger companies this means more efficient training of their existing environments, but more importantly it is also opening the door for smaller companies to also access simulated environments.
Simulated environments for training robots, self-driving cars, and many other applications are great, but have been hard and expensive for companies to build themselves. A 3D simulated environment that is low-code and has easy to follow templates can be a game changer for the simulation ecosystem going forward. I’ve mentioned the benefits of synthetic data before, and I think we’ll see more and more platforms that enable the use of synthetic data along with applications that thrive with it.
Hopefully this will make everyone’s Roomba a bit better at covering the whole room! (iRobot runs their simulations on AWS)
Chess was one of the first activities where AI started to show what it could do, but much to the disappointment of some avid chess players who worried that the computer had ruined the game. Luckily, DeepMind has been working with AlphaZero and chess champions to adapt new rules and make things a bit more exciting again.
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