We compete with them on efficiency. On a self driving car, a 1000W machine for 3d lidar data crunching isn't really feasible. If we can provide that at 10W,which we are aiming for, then we have a selling point.
As for our training chips, without divulging too much on a public forum (I'd be happy to talk more in private or over email), I think we provide the right level of abstraction and precision which would allow a researcher to one click port a tensorflow Model (we plan to support a few others like Caffe, torch, mxnet, etc out of the gate as well) to our chips.
As for our training chips, without divulging too much on a public forum (I'd be happy to talk more in private or over email), I think we provide the right level of abstraction and precision which would allow a researcher to one click port a tensorflow Model (we plan to support a few others like Caffe, torch, mxnet, etc out of the gate as well) to our chips.