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and artificial intelligence uh i'm delighted to say that we're gonna handle better manoeuvre
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superior intelligence add j. stuart good friend a colleague of mine to lead us through this session chase to it
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and welcome all you're you're probably wondering who is this strange man with this odd wearable
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around his back because i notice some one of the only people here with this wearable which is extremely interesting one dry clean only
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and uh the thing that's interesting about it is that the italians do not
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have a monopoly on this technology this was actually made in ireland
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so there we go i'd like to move into our conversation here about new
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technology it's extremely interesting one uh one machine learning and hey i
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uh if you couldn't backstage is now as we were preparing a you would have heard
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and i hope you will hear in our conversation that we're gonna have now ah
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some strong opinions on the subject we have a very good discussion very good
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debate going on where all this is going with machine learning and
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a i and some of it follows on from andy washes comments at the beginning of the day which i hope you heard about
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where things are going on how i machines are going to help us in in doing what we
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do and what the limits are if they're already what's so i would like to introduce now
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the people who are gonna help us in this discussion and uh we got a really
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great wind up with people from sport can from technology uh first of all uh
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pause
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also joining us your and one who is he a senior they hate innovation technology from the yes
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boy away from the broadcast also distribution a java okay who it is founder of from canada
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welcome all
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channel as i was just saying that we were we were having quite a good discussion uh in the uh
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it behind a curtain here about uh if a guy and a
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machine learning first why should probably preface this by saying that
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most of this discussion as i think many of you understand
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is about the production of content and about the delivery
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of content uh to the market so uh
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oh the two gentleman from federations here uh and uh or other
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colleagues or uh looking at how to produce content how to
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do it effectively and and using the tools uh that are out there i should say that they they come from different
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perspectives uh on the the subject and big well i i think i'll start with you
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uh which wind a question about that because i think about
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has already dropped with both fee into this space of of a of a a i and
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machine learning in terms of what it is that you do so if you could
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maybe take us through we're it's sets within what you do and why it's important
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so jumping with two features are quite a strong word i think we're still scratching the surface but
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four years ago or management folders logos we need to accelerate the
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growth of feeble we need to make sure the basketball continued
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uh being a being out there and and we need to be more
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aggressive on the market uh and and be more more visible so
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how it quickly related to to me to to my my uh my department is the fact that
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as have all digital wars digital upon when we need to be
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more reasonable uh create more content and distribute more content
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and this with a very common constrain let's budget or sooner kind of budget
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and that's how after couple discussions with some company we come up uh
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uh we met some company could actually provide a scenario solution
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that would allow us to to do that to do that exactly so create really a lot more content in the shoulder
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uh i'm off time and to distribute it to a a much much bigger audience that we never did
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so talking about funds obviously but not forgetting all federations those are guys or consuming content a lot
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uh stakeholders like players as well and media uh and broadcasters so yeah it's really are
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enabling this uh this type of content production and and enabling us to scale
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i just think at what we're saying before hand is that it's responding to
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a a trend uh it's not technology in search of
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a of an application it's it's responding to something
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that's that the audience wants and that the market what's yeah i mean we
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discussed this earlier in digital is creating new ways of consuming content
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a final becoming more and more more fines and and others actually are becoming more and
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more particular in how they wanna receive the content only wanna consume the content
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and i'll bring a traditional way of producing on then we'll just know enable us to to answer those
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uh see someone would not necessary lawyers are set or label because you have to remember that fee but i still like uh
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a midsize international federation we don't have the means of others like maybe you are five
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so we need to for me to find ways to to accommodate these new trends
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i'm keeping in mind also that and be a huge player
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in where the digital is driving or extending fans ought
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to consume content is giving them the condom they want so uh such feeble being also basketball we would be
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in the you know we won't be uh looking good uh if we were not able to actually repeated something similar
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but you're saying in terms of the volume of of what we're talking about you were saying tens of thousands of
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oh yeah of clips annually literally yeah uh with the same who
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more or less the same production team uh about five
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six seven people depending on on on events we've managed to
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multiply um no i can even know exactly but
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thirty forty e. x. the number of you do that we're creating a on a yearly basis
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nick let dale you you at the way for continuing to use traditional means let's call it human
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means of doing this are you planning on making a tradition a a transition again
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i mean not as well it would be the the different solutions uh
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it's important and that's what it is just uh uh i think that the the human beings as you said
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i mean the production done by human beings for one that's something we really need to uh to remember to make sure that
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the the contents with the awful human beings as the sound okay or for everyone yeah
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that we need a louder for particular place yeah so that that's yeah something which is important if
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we want to go for the best possible then the worse and uh for the moment
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he's the base the really is
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sure for that
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but yeah it's of course see uh you know we can use different ways and the f. is it but
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based on the well typical uh uh we i to sort of
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is this still i i think it's still quite here i don't know if we can um we can turn it up
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um one of the things that you would mention before at the very start you said that this is
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a kind of you can get into this subject publicly because in the beginning was the network
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yes explain what that what that means in georgia just gonna picture of your headset other the thing is that
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being that was the the network the the development of of the the the telecommunications a network
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capacities is really the enabler of uh yeah it without the network nothing works including
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really need to make sure that uh we're doing the right thing yeah
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the problem it working place and then we can use it
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uh was also mentioned you know your that one thing that has really changed
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a lot of thing is the fact that that everything is bi directional
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so you can send the content uh was with the viewers can also
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send information and is a complete change compared to the previous situation
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any as a it gives the the proceed from a i used in the beauty that is as as a
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fantastic to to create this to create additional compares to multiply the the the the content so it
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it's a new tool that is enabled by the the network that that's what i
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am doing basically but yes it's it's it opens a lot of gets
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yeah and if you could be before we jump into it if you could tell us a bit about what e. d. s. is doing and
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where you are in the spaces of a a i already so because
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we've had to federations your perk a provider of solutions like
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well maybe before really don't need to some examples um it's very interesting to hear i mean to i
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mean nothing opposing but complimentary point of view because that's also what uh with with what we think
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if they it there with the need to create more content uh more cost effective uh content
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um and for the same or lower a clearer productions the question is how can we also
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made as much as possible to produce we've limited for in higher rents productions is
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not getting with the crew because they need to focus on storytelling on creative things
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and what we want to do is retrieve aunt production techniques that can help
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and for the automation and make suggestions help the creative of storytelling part
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and we do that by automating some part and by off loading let's say more cumbersome activities
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so one of the things that we're other rather recently
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product tallest is based on automatic camera calibration today
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the operators need to calibrate uh the camera and the creative value in that
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for the limited we've rather want people to concentrate on what can you do once you have a calibrated a camera
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then you can add graphics uh i mean for thing with a nice little sideline for soccer
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'cause you're just sitting next to me that there are other ideas uh that we have
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and other actions i mean activity that we're working on if
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the um what's old with the automatic cameras selection
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what that is is we have an automatic system that can say liked automatically which is
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the best camera up to look at so you could say
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okay wait then we can automated production well yes
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maybe for other work here or production but not for hire your productions there we want to use this
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two supports either active to support operators to make suggestions would operate
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without a look that camera angle there's something to see
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went to consider that or using that information to prepare replace or to prepare highlights
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just to be able and that's the value of artificial intelligence
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and machine learning is to be able to do more
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artificial intelligence will all slowed things and is capable of dealing with more contents more personalised content
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rather than the say the operator or the director that's generating one mace when feeds
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to be on their using a on you could create many more personalised fee
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uh in soccer you would say okay i want to feed focusing all my method for instance
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or i want to feed actually a bit emphasising my thing because i like my team
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and that's the value that it brings and by using all these yeah elements um that's what we want
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to give obviously your customers to make them produce more and better to better serve their audience
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and there was the idea parallel uh a parallel production as you mentioned before like a lot
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uh when we were talking that sometimes on the same uh event on the playing field
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different camera angles might be suitable to different platforms absolutely yep that we can
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do that in the say in two ways that either we say okay
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um the cameras on the page and the official when got director for gays
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you feed to be able to put on there we can t. and it's a bit and say okay i want to see a feat
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this is in favour of my thing 'cause i like my team or i want to see a feat
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that uh favourites um in attacks or that's that favour some other things and then
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you can really or the favour specific player and then you get really generate
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it's much more uh of these fees and ultimately that's uh what
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today's view worse want really want more personalise the content
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and that's what a i can't win without exploding the number of uh people
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and not because we don't want to have this people but there's
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no place to put them and they simply do not all uh exist
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coming back to what you said is it is also not just
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personalising feats but also targeting feats to specific a device
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and therefore we're working on the tool that what we call automatic framing basically what
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it does is it cuts out a part of the full h. d.
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view image of relates the video of um the reason for that is if you want to publish let's say on the mobile phone
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for soccer of full wide view of a soccer page i mean
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your players will be ones millimetre higher so on your
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i mean mobile phones plane that's not very pleasant to watch so we cut down
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it's really the part of the video where the heat of the action is
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and that's some interesting information but also can be used for stuff
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the one oh sorry nickel out there that sorry uh for example a lot of people
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watching sports on on their mobile phones uh if the data that you get in
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uh a square picture maybe more interesting than a rectangular pitcher for example in this kind of solution of low to
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create a split peter so people can watch on them away from that you could for example so that's
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something which is better and it doesn't change the the the the the whole view
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of the content but with leaves actually evolving that it's improve what a
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i brings there is that it interprets the image and so it can really
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show this is where human people this what human person we've watched
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and that's different that's it to compare to more traditional approaches that would get parts uh left
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in light of uh of the image really show there is where the action a seven
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there's an where you commit all this is a little bit different uh we're talking here back camera automated
00:15:07
let's say a a assisting production uh using the
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tools um your a company is about using
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a machine learning in a slightly different way could you tell us how that works out
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yeah him because machine learning a i slightly in a different way
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and b. b. n. a. i platform that watches the gains
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and you think you know beyond a broadcast the eight or any i their visual information and it can but
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somehow talking gains eight process that begins in real time
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and it generates tracking data and and action
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well it turns out that everyone a is and what everyone is doing at every
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say can again so we end up with a massive pile of data
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many many pains beach are extremely difficult for human being to interpret
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then be use machine learning a high and bitch because game models and they can tell us
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and for example how much an action of the play yeah contributes to the outcome again i think didn't talk
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this way we can add quantitative late compared tactics the strategy is
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effecting play yeah a place up my aunt not and
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then we can find interesting that's the way we can find and things that are
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important for fact we can generate personalise this story is looking at the data
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back thing with the data but not necessarily talking about data
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we get the numbers we find interesting it's though is the
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pair them with videos and they show those videos
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be create content we have comments and a fan but
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at the game differently so basically the big
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we try to change the bay that at people are watching the game like it's going to be a new experience air
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getting more information cater what's your create friends about the things that you hear and back
00:17:02
to it that you know the us to question backstage that i just uh
00:17:07
thinking about which is how good or you're predicting the outcome of matches use your technology you're saying
00:17:13
you're quite good so actually you could get to a point relate were you could say
00:17:18
yep they're gonna win this one here think it hypothetically i can predict the outcome again so i'll
00:17:27
no one gets to play even know who is going to maine but honestly us
00:17:31
forces not about predicting the gay if there's always onset think the and
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i can major things that our national but there are many other factors and
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again that can't be midget can't be quantified and we watched again
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we didn't see it good looking for a surprise might be
00:17:49
we know that this tactic is not going to work against sets in fact they
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played by another team and be half is sort of quite they tell but
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was it works and it is chords and that's the moment that you want
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to make and story and that's the moment that you're predictive model face
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yes we have air their predictive capabilities we can't predict the outcome of the games but
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we are not using things to predict the outcome getting big take those
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predictions let's say we can say but with the expected escort
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up again or what would be the expected a score of one
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is this big play yeah in that page and maybe
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we can see the results and we can find discrepancy and we can generate s. stories based on that thought that
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it's going to be the neil kind of experience of watching again
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it's all about emotion ultimately and and and the human element
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um and what what we can what i just like to ask everyone here is
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to be clear for the audience also that that the human eye the human element remains in all
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this at least for now like this what we were debating a little bit behind the scenes
00:18:59
because they all you were saying it's a tool it's important recognise that it is that you all the question for
00:19:04
you or someone saying the idea that this is gonna put people out of work is just not the case
00:19:08
oh it's i don't it's not the case i mean in our in our situation or when we
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brought in that the the this machine to create content uh smart content and automated content
00:19:18
our it'll team started to get a grey hair and you know heart attacks and and and shaking but there's only
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relies uh for a couple of weeks that the machine was actually doing all the liberties work for them
00:19:30
the boring work if i can say do you know the content that goes out and that
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is just consume very quickly and then from the wave where's the could actually shift
00:19:38
their focus on the more premium qualitative type of content and seventy
00:19:43
that's totally change the perspective of the of the job
00:19:46
and they're actually you know with the machine no because it frees up so much time for
00:19:51
them to give them even more budget to work on on bigger and nicer products or
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i i i know at the moment i i don't i'm not afraid
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of abuse i see this as a huge facilitator as a curator
00:20:02
uh and we just have to uh that's maybe the way we
00:20:06
wanna producing the way we wanna distribute brings to what
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the machine is able to give us a bit like when computers came out everyone was scared like we're gonna be
00:20:16
our work plan and we see today that it's giving us more work
00:20:19
uh norwegians and uh and and we are more productive so
00:20:25
and i don't see a without computers these days yeah that computers and cell phones directly
00:20:30
likely you're quite optimistic about this because you were saying the human element
00:20:33
is so fundamental i mean everything is and sports about fashion
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it's live it's it's happening and that's what we wanted to believe and
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want to communicate these these fashion to the to the viewers
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the machine is just here to help us in it but uh i i i've
00:20:50
i don't see any kind of coffee between the machine and human uh_huh
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the two on the doing the same thing and the machines are here to do a lot of
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automatic things all boring things because they are so fast a regular yeah they are so but consistent
00:21:06
but the passion is not coming from consistent and you use the use the point that would sit down
00:21:12
head butting somewhat of a football match the machine would've would've ignored that because it wasn't relevant
00:21:17
to the attorney for the football that that it's not it's not the official event
00:21:21
yeah so yeah that's the one clip all of all the continent can be created so
00:21:27
so and and the the mission can bring a lot of things but different in that the special
00:21:32
sessions not going from formation get fashion coming from human beings doing an activity and then
00:21:38
do some things that i think in the way of actually no choice also to embrace this we are in a we're in the race
00:21:47
uh where everyone has a right older to stay outside you know on the surveys to be seen and so on so
00:21:54
and people asking more content everyone is asking more content even other machines are asking more count and so if
00:21:59
if you wanna stay there visible uh so that you can speak to sponsors so that
00:22:04
you can speak to your audience you need to be able to kind of
00:22:07
much what you can get off of a artificial intelligence and and what you
00:22:11
can get all the little things people ah watching sports on different devices
00:22:17
and that's one of the girls to adapt the content specific device
00:22:21
and the aspect ratio for example is something really important
00:22:25
i think this is the direction of frame that shows the you will have that in the best
00:22:30
possible content on the device of their choice and and this is where we should go
00:22:37
and machines can bring a lot of added value to that by the way if
00:22:40
there are questions you're just raise your hand i'll throw you the uh
00:22:44
or someone will bring you the the uh the box here so that you
00:22:48
can ask it um but please don't hesitate just jump in um
00:22:53
the question of style comes up and i don't know how important it
00:22:56
is really a colour uh is is where you mentioned before i
00:23:01
is is are we going toward say uh i uniform style of
00:23:07
production and of of content so that it's all gonna become the same cookie cutter that we're gonna see for everything
00:23:14
or is this only going to be at certain levels of of of for
00:23:18
that i think we're going total opposite actually on the machine is smart
00:23:23
cool artificial intelligence and is able to actually customise the content the way the receiver wants
00:23:29
to wants to see it so in our case for instance we get publishers
00:23:33
uh in in various different countries and they tell us okay i don't
00:23:37
care about okay i'm friends i don't care about uh spain
00:23:42
i just wanna get the clips of friends sent to my mailbox and a package
00:23:47
just this way with this intro video with the role within i'll probably do
00:23:51
no mention is able to do that in a complete different way then we'll be doing it for the for the spanish probably sure soul
00:23:58
i'm i'm really uh i'm not so sure that we're gonna go into something like a flat
00:24:04
boring uh 'cause the machines i was actually going to learn from from what people
00:24:09
and we'll have that so that i i fully agree on everything we had been because even that even when using machine
00:24:15
uh learning or that's artificial intelligence you can teach learn design
00:24:19
the system so that it implements this different uh flavour
00:24:23
i mean the example that i gave okay the food they just
00:24:26
selects the best the camera and produce has a program feet
00:24:30
you can tune that's this them to make it even if it the style of the french producer or
00:24:35
german producer that have different ways of uh of working so even in the a. on itself
00:24:41
you can difference hate and ultimately it's because the people
00:24:45
want to see that a different station but
00:24:48
the only is more really in in support it so you still have the director
00:24:55
really focusing on the creative apart but the director oscar the ice is than
00:24:59
a beer yeah system um give me a shot of that player
00:25:04
in current systems uh it will take time and you need these people are not waiters to really
00:25:09
assuming on the specific player and i can do that and they do a great job
00:25:13
but unfortunately they will only zoom in on one or maybe two by using this system
00:25:19
you can have the other system zooming in all all players on the field and having the director really big
00:25:25
the one that uh he or she wants depending on what's what's the personal style
00:25:30
depending on what the style of the country of the sport um depending on
00:25:35
the motion that the rector once but in the gain 'cause that's the little where
00:25:40
i see uh at least that this this moment the big difference haitian between
00:25:45
the humans and analysis analysis them it's it's in supporting that it will you will
00:25:52
off load things to the only system even things that look a complex light
00:25:56
following a player or selecting the best the camera angle but ultimately it's
00:26:02
the fall protection through the plane and the most um a little story to bring it home telling
00:26:08
viewing for the audience that's humans to the audience and that
00:26:12
is not in the standalone mode that actually is
00:26:15
bi directional that takes into account the motions that live in the stadium during the match
00:26:21
and that use that into account to really can create compelling a story and and the i. system
00:26:27
maybe we'll do it once but to they you really need to human humans to do that
00:26:32
i just add a comment about this that i and their bit the current and machine
00:26:36
learning techniques for example you can you would send a supervisor reinforcement learning and
00:26:41
given machine that trans to do some exploration you generate you know
00:26:46
what they use r. f. fan once the see like
00:26:49
it but i find cancer bought a set seventeens our second
00:26:53
play yes but you get a chance to machine too
00:26:56
and make some exploration and create some other contents for that you there
00:27:02
and then it eh images that interaction and see and it may
00:27:06
just be the user enjoys the new content or not and if it
00:27:09
is the right direction to go it probably does that more
00:27:13
to art and that kind of a theme that then issues and so
00:27:18
we can get mission the chance to do some exploration but
00:27:21
yeah all the mission learning models they on not
00:27:25
quite good beget there in future but at the moment uh you have some tools that we can leverage
00:27:32
but there there's been helpful questions that call them the passion i'm interested in a specific scene
00:27:39
and it's good like this so they they can give us i mean some some indications on okay view these other takes the okay
00:27:46
so i mean they can bring us a lot of things but that's where the human beings are so good that is
00:27:52
yeah it's something into generic this passion so for me it's it's really a complete i mean
00:27:57
something whether it be there's no there's no and no uh with
00:28:02
a i completely agree with your weak and three morphine
00:28:05
amended yeah i'm not going to remove humour from below piedmont to make things better for humans and they want to
00:28:12
they know is that make things is not meant not lives easier
00:28:16
as a producer as content producer i want to have hundred different that's the reason i chose the best
00:28:24
mark rather than looking at everything myself i want to get like that's a about this than that
00:28:32
asked them every day how slight interesting is the what is
00:28:37
that you've fallen uh in the past few objects
00:28:40
rather than myself looking at those things so it's basically the the like the
00:28:46
final decisions because uh it's a learning techniques are not there yet
00:28:52
it is the current techniques that are out there that this that
00:28:55
we can do is to follow it by hillman and
00:29:00
design something that behave exactly like backed producer but this is
00:29:06
something i don't want to be the ones that way
00:29:08
above a question production i think that uh a machine learning or activity intelligence can bring
00:29:15
any right older closer to lose something rather right now like
00:29:18
the currency that will everyone's talking about engaging religion um
00:29:22
what you were mentioning about you know being able to create stories based on the data that the remote to collect
00:29:28
now we have actually even robots we we tried that actually doing one or
00:29:32
more events would all the phase book robot that was able to
00:29:36
communicate with every fans already at a suburb run level every one was every fine was able to request
00:29:43
a particular type of content so it's pretty nice for every player uh
00:29:47
from that for every player i want bands or one yes it's
00:29:50
and and the next level is really having a conversation so watching the
00:29:55
game and say hey hey buddy whatever you wanna call it
00:29:57
uh what do you think your who's gonna be next core or how high is this guy jumping because
00:30:03
finds also getting should rejected you know they are used to to get this from other people so
00:30:08
i see a if you're a see huge player for engagement
00:30:13
if i can ask you that you censor face book is the faces of box part but
00:30:19
basically it was a perfect face book enable you to do that correct yeah so you build an interface
00:30:25
in the background and you use these book messenger i guess it's possible with any other messengers
00:30:30
and then you interact with the rubber soul ours what again very surface
00:30:34
level but i'm sure in the very near future we will have
00:30:38
these guys you're the new building machine are actually able to have a
00:30:41
conversation with you we saw it from good okay so it so
00:30:45
again questions if there are any please just stick your hand up and we'll here's one right here in the front
00:30:52
rather than throw this all the way across the room
00:30:59
thank you a question for leisure and you talked about a machine learning for contents creation
00:31:06
now if you can be right so many things on our past games what about using it
00:31:09
for training or coaching performance are you doing better thank god we have two different product
00:31:16
one is take back to art and a digital media and broadcast there's the
00:31:21
other one is for teens and then i did look at player's performance
00:31:27
they look at the historical data and and we provide
00:31:30
access actionable insights for co chairs for acting analysis
00:31:34
big weekend then then what might it around the are nothing to replace a coach
00:31:39
we want to build an assistant coach that provides information and digest information and
00:31:44
bring something to the core which that coach can make a better decision informed decision
00:31:49
also all they can and they have escorting product we can look
00:31:54
at a play yes in mind our legs and all
00:31:57
they are playing and we can't really comment players based on the playing s. i. based on
00:32:02
at that time and then we can say that these two might be a good faith
00:32:06
for your team if he is uh if these other players are eighteen days a these
00:32:12
new players have kind of similar ascii is and they are playing the same aside
00:32:17
uh that's a good team products that we have and uh
00:32:23
it's been useful um i'll be back more than a half of that trade
00:32:27
in their past three seasons in n. h. l. north american hockey league
00:32:32
so it shows that half of the trace have been back it they target real information not basically got thing
00:32:41
the the one of the things that was commented on uh you know this is something you said that the trend that
00:32:46
uh it's not the digital has certainly created a a completely new i
00:32:51
mean it has created new ways of consuming but that the personalisation
00:32:55
friend the the desire the market was all ready there or what was going to grow anyway
00:33:01
will i strongly believe that indeed this personalisation um something
00:33:05
that people want and they just isolation isn't
00:33:10
that isn't able actually just in the same way that i think that artificial intelligence as such
00:33:16
it's not the goal for a like paul tells if the means any turns out to be
00:33:21
i mean the most interesting means that we have at our disposal at this a
00:33:24
moment to get there but the intrinsic needs of other say of humans to
00:33:30
to get information to be entertained in to be that
00:33:34
in a personal way i mean that's that's there
00:33:38
and we now have the tools i mean to filename to answer that uh that need and
00:33:43
that's what we should embrace uh that you can do that now and we should do
00:33:48
it seems that there's quite an optimistic uh outlook on all the so if whether there's optimism
00:33:54
or not there's a there's a it seems to be an acknowledgement that it's essential
00:33:58
to do this it's the only way to go to in order to cope with demand and cope with the way that the the market is going so um i
00:34:05
want to thank our our panelists here um if there are any more questions we
00:34:09
do have one more that we we do have time to fit in
00:34:17
i think um my question addresses to both nicholas federations
00:34:23
uh the is a i also to got uh some data for your sponsors
00:34:30
good question have uh not yet on you if you wanna maybe you're more than something that's like i mean yes and no i mean we
00:34:38
we are gathering information i mean but the gathering of information doesn't imply
00:34:42
that use a and it's it's the tool again but uh one
00:34:49
it's an additional two let's say i were i don't know if it's called a or
00:34:53
not it's again a tool that is able to underlies moving images or or contents
00:34:59
uh just like some of the tools measure you know exporter on t. v. so
00:35:03
we're starting to use this to measure it ought to try to to to
00:35:07
get a new the value of all the digital activities that were going
00:35:12
'cause one of the downside if i can say of creating all this content is that content is
00:35:17
scaling like like crazy and it's true that we have a little bit of trouble of controlling where it's going and
00:35:23
understanding exactly were things or or ending up and how they're being consumes alright these liberals or well known
00:35:31
thank you very much to this panel uh and i hope you'll join me

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Conference program

Welcome Words by David Eades
David Eades
15 May 2018 · 9:06 a.m.
Welcome Words by Philippe Leuba
Phillipe Leuba, Chef du Département de l'Economie et du Sport
15 May 2018 · 9:08 a.m.
Welcome Words by Grégoire Junod
Grégoire Junod
15 May 2018 · 9:13 a.m.
Welcome Words by Benoit Mariani
Benoit Mariani
15 May 2018 · 9:15 a.m.
Hacking the Future
Andy Walshe
15 May 2018 · 9:25 a.m.
Talkback Session: Smart Venues, Moderated by David Eades
Daniel Marion, John Rhodes, Claire Lewis
15 May 2018 · 10:18 a.m.
Talkback Session: Wearables and Data, Moderated by David Eades
Terho Lahtinen, Jean-Christophe Longchampt, Christophe Ramstein, Patrick Schoettker
15 May 2018 · 11:04 a.m.
Talkback Session: Fans and Data, Moderated by Rebecca Hopkins
Horesh Ben Shitrit, Pete Burns, David Lampitt, Clemens Schnellert
15 May 2018 · 11:46 a.m.
Interviews, Moderated by David Eades
Stéphane Guerry, Joey Tan, Olivier Glauser, Albert Mundet
15 May 2018 · 1:45 p.m.
Talkback Session: Machine Learning and AI, Moderated by Jay Stuart
Nicolas Chapart, Nicolas Déal, Johan Vounckx, Mehrsan Javan
15 May 2018 · 2:37 p.m.
Speech
Jochen Färber
15 May 2018 · 3:14 p.m.
Talkback Session: NextGen Video & Engagement, Moderated by Nicolas Henchoz
Christoph Heimes, Spencer Nolan, Pedro Presa, Alexandra Willis
15 May 2018 · 3:30 p.m.
Interview on Security
Earl Crane
15 May 2018 · 4:08 p.m.
Talkback Session: Cyber security and Digital Security, Moderated by Sébastien Kulling
Dang Duy, Thomas Shorrock, Jean-Pierre Hubaux, Simon Trudelle
15 May 2018 · 4:19 p.m.
Introduction of Day 2
David Eades
16 May 2018 · 9:35 a.m.
Social Business and Sport
Muhammad Yunus
16 May 2018 · 9:38 a.m.
Talkback Session: Designer Bodies - Yes or No? Moderated by David Eades
Roland Sigrist, Vincent Gremeaux, Carlos Canto Alvarez, Véronique Lugrin
16 May 2018 · 10:27 a.m.
Talkback Session: Designing for the Future, Moderated by Jay Stuart
Ali Russell, Emilio Risques, Véronique Michaud, Thilo Alex Brunner
16 May 2018 · 11:08 a.m.
Talkback Session: Protection through Innovation, Moderated by Mike Miller
Liam Mc Tiernan, Laurent Mekies, Eric Nauman, Martial Saugy, Mathieu Saubade
16 May 2018 · 12:04 p.m.
From Racing to the Road
Laurent Mekies
16 May 2018 · 1:32 p.m.
Talkback Session: Understanding the eSports Ecosystem, Moderated by Jay Stuart
Brent Barry, Anna Baumann, Julien Delalande, Michael Journot, Carlos "ocelote" Rodriguez Santiago
16 May 2018 · 2:05 p.m.
Talkback Session: What's next in eSports? Moderated by Lars Stegelmann
Brett Abarbanel, Stefan Kuerten, Jan Pommer, Federico Winer
16 May 2018 · 3:05 p.m.
Closing Words
David Eades
16 May 2018 · 4:06 p.m.