Scott Phoenix

you mentioned IBM's Watson there they've been working for a long time you know beating all the chess Champions uh I guess deep blue is what they used to call it and that would be the perfect example of narrow just chess

it's way too early to say who's going to be the big winner on self-driving car and frankly I think the real answer to the question is that we all are going to be the big winner for sure cuz it's I don't think it's going to be one player that figures it out I think there's going to be many different alternative approaches and different different ways to to get to that same solution and they'll be suited to different markets like self-driving trucks or uh you know Uber style Transportation Systems

Google has had their self-driving cars but more important than their self-driving cars they have ways data and Google Maps data

Google search search ranking they leverage really big data sets and really big compute clusters in order to get something that is narrowly intelligent

they leverage really big data sets and really big compute clusters in order to get something that is narrowly intelligent and in the Facebook case an example of that might be something like hey let's show um you know this viral video to Men Women this age group just any number of possibilities and see what the the length of time to watch it is or something like that and then try to make some sort of assumptions and it just learns what viral videos next would make you watch longer I mean that's o