It's an interesting thought experiment but I tend to disagree overall. I don't think a self driving car is a data-center on wheels. It will not have 100(!) se

It's an interesting thought experiment but I tend to disagree overall. I don't think a self driving car is a data-center on wheels. It will not have 100(!) servers built in it. It will have one (or two for redundancy) PCBs with just the right enough of processing power in whatever form makes sense, multiple cores, ASICs, etc. (which would be less than 100 server worth). I would agree that the more compute cycles will move out to the edge. This is already have been happening with smartphones and will continue with other intelligent devices. The more computers we have in our environment the more the overall portion of cycles move to the edge. The depiction of a smartphone as a dumb terminal isn't that accurate. A smartphone can and does do a lot of things locally. My bet is there is a lot more compute power in all the phones today than in AWS EC2. (though maybe not compute $'s) The comments on machine learning don't make sense. There is a lot more data for machine learning in the aggregate of all the devices so it will naturally happen in some centralized location. While there can be some machine learning in the edge machine learning is a lot more effective on the aggregate centralized data. So data from the edge will get pulled to central large scale systems. The result of this learning can be pushed back out to the edge to be applied (e.g. in the car). EDIT: He later on modifies his statement about machine learning happening in the edge and rather some "selection" of the data will be used for machine learning in the cloud... Still doesn't quite add up.