Scale By The Bay 2019: Gabor Melli Interview

[Music] my name is Gabor Mele I work at Sony my name is Gabor Mele I work at Sony Playstation I'm a senior director of Playstation I'm a senior director of engineering focus on ML and AI engineering focus on ML and AI applications now this is my my second time it the now this is my my second time it the previous time was about two years ago previous time was about two years ago and it was a different organization I and it was a different organization I was focusing on natural language was focusing on natural language processing related but different than processing related but different than what I'm doing now favorite and what I'm doing now favorite and important part about my talk was important part about my talk was characterizing what an ml engineer does characterizing what an ml engineer does we've been trying to make that really we've been trying to make that really clear so that our software engineers can clear so that our software engineers can know where they can fit into that know where they can fit into that pattern and maybe even level up some of pattern and maybe even level up some of them to be software engineers them to be software engineers transitioning to ml engineers so Sony transitioning to ml engineers so Sony PlayStation's is a large organization we PlayStation's is a large organization we have many different offices and they'll have many different offices and they'll have different ambitions to do machine have different ambitions to do machine learning the work we're doing within my learning the work we're doing within my teams is to scale out all the machine teams is to scale out all the machine learning applications that we have so learning applications that we have so that others can self-serve to the work that others can self-serve to the work that we're doing so if we have features that we're doing so if we have features of all the customer they can reuse at of all the customer they can reuse at work not reinvented what a few of them there's a lot of what a few of them there's a lot of talks on machine learning is certainly a talks on machine learning is certainly a hot area and an important age hot area and an important age leading-edge area so it's been talks leading-edge area so it's been talks between er Microsoft Curie I there's but between er Microsoft Curie I there's but yes so several of them have been super yes so several of them have been super relevant to what we're doing well we've relevant to what we're doing well we've gotten into low latency frameworks or gotten into low latency frameworks or now we can do very very quick now we can do very very quick predictions now that's a matter of like predictions now that's a matter of like expanding that out to apply to so many expanding that out to apply to so many different kinds of predictions other different kinds of predictions other kinds of recommendations we still kinds of recommendations we still haven't cracked up not so we're hoping haven't cracked up not so we're hoping in the next year we can do a generalized in the next year we can do a generalized solution for it [Music] [Music] sure well I love the passion here in sure well I love the passion here in terms of really getting into the nuts terms of really getting into the nuts and bolts of how machine learning and or and bolts of how machine learning and or even scaled systems work at the panel even scaled systems work at the panel last night on server let's go really last night on server let's go really animated and I could see that there's a animated and I could see that there's a lot of depth and a lot of passion here lot of depth and a lot of passion here so I really welcome that to scale it I so I really welcome that to scale it I just keep it up this menu is really just keep it up this menu is really great for this year so that's so far so great for this year so that's so far so good yeah I can't wait to see what good yeah I can't wait to see what happens next [Music]