“Facebook” is a large organisation: there is a team (led by Yann Le Cun) that does research and supports image-recognition, NewsFeed and ad-market optimisation,

“Facebook” is a large organisation: there is a team (led by Yann Le Cun) that does research and supports image-recognition, NewsFeed and ad-market optimisation, but this is not exactly what Mark suggested he would dibble with. Those handle was is de facto an industrial problem. He is more curious about the ability of using AI for daily interactions (hence the reference to what are movie characters): do notions like personality, convenience and interface, implicit assumptions matter? If he asks “Buy a new set t-shirt” will the robot be able to joke “which colour?” (MZ notoriously only wear the same grey model). I would look into what Messenger wants to be doing (or, what Slack is doing) to see the implications: can small companies do what Uber does with the key-word integration in chat? Is it creepy, hackable, tedious? This of this like his dog’s Fb page: it’s building empathy for the users of the Facebook platform. First problem he’ll probably have to find: Who to call when saying “Call Mike!”? Of course “Mike” is probably the Mike with whom he has the closest ties (based on Facebook graph data) — except his VP of Engineering, Mike Schroepfer, is known as “Shrep”, so that’s probably not him: how easy is it to program something that can learn that seamlessly? In which case the ambiguity too high, and Jarvis should ask for confirmation vs. just casually saying the full name out loud and wait a second? How to measure ambiguity? Would it be simpler to just start calling people with non-ambiguous name? Would he feel like sharing his code with peers? His heuristics? How to gather that “Mike” is still in Europe where it’s 3AM, vs. was in Europe for in last post and actually just landed?