ai.bythebay.io: Ted Graham Interview

you you [Music] you so I work on autonomous and connected so I work on autonomous and connected cars for General Motors amongst other cars for General Motors amongst other things but that's kind of a key focus things but that's kind of a key focus area and AI is the practice that is area and AI is the practice that is really helping us make great games in really helping us make great games in terms of mapping in terms of we're just terms of mapping in terms of we're just being able to the further safety of being able to the further safety of passengers we've been able to apply it passengers we've been able to apply it into the realm of sales we've been able into the realm of sales we've been able to apply to the realm of prognostics and to apply to the realm of prognostics and diagnostics so it's got a wide range of diagnostics so it's got a wide range of applications we focused a little bit applications we focused a little bit more on machine learning than sort of more on machine learning than sort of general AI but it's definitely a key general AI but it's definitely a key part of what we're doing a jam so right part of what we're doing a jam so right now if you've got data sets that you now if you've got data sets that you know the some of the leading researchers know the some of the leading researchers can work with and trained and you've got can work with and trained and you've got a great advantage there's a lot of stuff a great advantage there's a lot of stuff around some healthcare records or around some healthcare records or radiology scans that have been powering radiology scans that have been powering some some innovative new startups when some some innovative new startups when we get into the the realm of tagging we get into the the realm of tagging images and recognizing objects and images and recognizing objects and localization we're going to need to localization we're going to need to continually add more data not just data continually add more data not just data that we collect but that is collected in that we collect but that is collected in new areas that is under construction and new areas that is under construction and changing all the time so I others one of changing all the time so I others one of both the opportunities and challenges both the opportunities and challenges right now so it's a talent play for me you know so it's a talent play for me you know there's an interesting board downstairs there's an interesting board downstairs here where it shows the companies here where it shows the companies looking for AI machine learning talent looking for AI machine learning talent and people who are looking to be hired and people who are looking to be hired and there's a real imbalance there and there's a real imbalance there there's a lot fewer talent than is there's a lot fewer talent than is needed and if you look at the very top needed and if you look at the very top most productive talent a lot of them are most productive talent a lot of them are being kind of brought into companies being kind of brought into companies where they're not available to to others where they're not available to to others and you know usually use the example of and you know usually use the example of Carnegie Mellon which had 32 of their Carnegie Mellon which had 32 of their top engineers kind of scooped up by uber top engineers kind of scooped up by uber so you know we're worried a little bit so you know we're worried a little bit about the brain drain in some of the about the brain drain in some of the academic the leading academic programs academic the leading academic programs because we want to train more and more because we want to train more and more of these people and it's not going to of these people and it's not going to happen if we take them out at that sort happen if we take them out at that sort of in a teacher trainer labs or level low is such a diverse group of people low is such a diverse group of people today we had people from a city-planning today we had people from a city-planning point of view talking about Singapore we point of view talking about Singapore we also had people the funding side looking also had people the funding side looking for you know how do we give the food to for you know how do we give the food to kind of get up to the next level and we kind of get up to the next level and we had people sort of very deep in terms of had people sort of very deep in terms of like George Hotz and coma AI and expose like George Hotz and coma AI and expose on you know that the real bleeding edge on you know that the real bleeding edge of what can be done from an open source of what can be done from an open source point of view so it's not often you have point of view so it's not often you have that variety in one room and I really that variety in one room and I really appreciated that appreciated that you you [Music] you you