It can be computationally expensive for a robot to use any sorts of deep learning on board for improvement during work.
It takes hours if not days sometimes to train a good scaled model. Then retraining the model could take a quarter of that time, which is too much delay for a robot. However, with linear models things can be easier.
Also, there are very few people who know how to manage DNN or creating neural nets from scratch in a proper required way. Otherwise Boston Dynamics have to stick to one of the existing libraries which wouldn't be ideal.
DNN is amazing for some work that am sure they must be using them already, for example models that can help them with the feature engineering and such.
It takes hours if not days sometimes to train a good scaled model. Then retraining the model could take a quarter of that time, which is too much delay for a robot. However, with linear models things can be easier.
Also, there are very few people who know how to manage DNN or creating neural nets from scratch in a proper required way. Otherwise Boston Dynamics have to stick to one of the existing libraries which wouldn't be ideal.
DNN is amazing for some work that am sure they must be using them already, for example models that can help them with the feature engineering and such.