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> Also notice that in some domains ML is still behind symbolic A.I., for instance a lot of robotics and autonomous vehicles. Classical AI has failed in robotic
by lostdog 5y ago
> Also notice that in some domains ML is still behind symbolic A.I., for instance a lot of robotics and autonomous vehicles.
Classical AI has failed in robotics. There's practically no field where it does worse than in robotics. It's getting cut out of every part of every system one piece at a time, and being replaced by ML methods that really work. Even Kalman Filters aren't safe.
- iamcurious 5y agoIt's been a few years since I investigated, but Boston dynamics was using mostly old non ML methods. See [1] IIRC and Waymo vehicles used ML for some of its perception but also depended heavily on the lidar and a rules based approach. Sadly I can't find a link at the moment. What examples are you thinking of? [1] https://www.quora.com/How-does-Boston-Dynamics-use-AI-machine-learning https://www.quora.com/How-does-Boston-Dynamics-use-AI-machin...
- lostdog 5y agoHere's Tesla's AI day presentation on how they are going to use AI in their planning system because traditional methods aren't scalable enough: https://www.youtube.com/watch?v=j0z4FweCy4M&t=4392s https://www.youtube.com/watch?v=j0z4FweCy4M&t=4392s (1:20:15). You can see hints of this in presentations from the other self-driving companies. Boston Dynamics was definitely an exception for a long time. Certainly the perception systems that they are adding use ML, but you are right that they use expressly use classical methods for their control system.