each G for the past fourteen years the ieee present of the ieee jack it cool be signal processing metal the some portal or fun the refer to as the kill be metal it's what i you refers to as a major metal it was found about the ieee signal process society has been generously funded since its creation but the texas instruments company jack you'll be love to be in an engineer use was an inspiration to many do decided to pursue electrical engineering as a career well he is no longer an are males his influence contain as of already mentioned because it's a major metal the ieee jack he'll be signal processing metal is presented by of the ieee with the ieee medals and awards ceremony the will be held issue you're in august and san francisco california however it is been the practise of the metals down in society that would be us to present a special commemorative plaque from the society to the kill be metal B recipient this year the recipient of the two thousand eleven ieee jackie a skill we signal processing metal is in great do over shape professor over a is receiving this honour or for pioneering contributions and you theory and applications of wavelets and a filter in could not be with us today we she will receive the metal at the ieee tripoli medal ceremony in august in san francisco but i do recommend we go for a round of applause in it since yeah ladies and gentlemen that concludes today's ceremony i want to thank you all for attending the in the at triple you signal processing society order order B against than a that triple follows the recipient of the ieee james flanagan at speech processing metal and the research you know of the ieee tripoli jet kill be metal the so sorry hold as awards ceremony and really and i cast a look forward to seeing you again next year thanks again i john for something thing all these works and can grow to your workplace so this is closing that the official opening and sort money and that the and let me thank our musicians mister hour and mister of ski for making this a a more you and okay thank you we are on time it's miracle the we are moving on to the technical program of for conference the first one talk i will come on the code um uh are or for a speaker and a from a nokia and professor before cory one and from helsinki university of technology we will present or for a speaker and should six Q where is send them and uh i have a great place or to introduce the an our to speaker but that it really a in or was present or and that of market research and nokia research center break was to enable a new business opportunities for not yeah race the responsible for you you know we're white that first struck in the and work closely we or not give a a in to promote open in the base and working phone research is in collaboration with we we equal global research universities and is i believe that means that expense what of time not only in is of this but also at the airports and a and it well it's a T in computer science from the universal of think in one and he joint here in do got from for as the results go in software applications well is previous positions include working at a at and T you go uh and uh us a visiting research scientist at a so things where can going to the wells role called the also for email a or and cool or able or for more than the or as would a i of a a personal computer science social science statistics and holes like that some of these papers are are are very can the school of single produce or so including machine learning and and uh uh um okay okay is been also used to professor at to use C berkeley and stanford it works is other interest include a a a a a long board surfing and scroll boarding and i think that's why you like look in california would i that the crib leads to work in a and risky more much of a is and i enjoy every ladies and gentlemen of and it could be very oh do you know ahead okay good morning um those of you who are right from uh uh U S i know it's very early in the morning high i came from the your can the data from on but i'm uh like uh was mentioned i've spent a lot of times on the plane side actually not sure which time zone i'm and in um what i was thinking about what's the topic that i would like to touch to for sets are how would i say wide scope audience i chose data and they are multiple reasons of choosing data one was that i spend more than twenty five years some my life for searching for the medical data set that could prove that my method some better than the other um a i for charlie that search um of course uh was a a a a difficult one not only because of the maybe the problems with my methods but the access to data and um having worked long in the field and and and looking at multiple datasets i know that where we use of lee and in that type of a situation ease the fitting are methods to that particular datasets that we have a or generating synthetic datasets which we know that will have their own problems when when you use them some my feel was a lot of what you would call machine learning or information T legal learning or bayesian learning one of the reasons is i i was so on the bayesian learning as we will hear um later on during the conference was that as i had so little data at the bayesian let's some what's uh easier methods to apply than the frequent just methods so i decided to talk about data today just because i think it's a very common topic for most of the things that you see the con for uh but i'm taking a very different approach spend again a a lot of time of doing um the i writing papers on on on on the different that a mathematical properties of of learning and also implementing that different algorithms and today i'm and going back to my roots of hacking so i'm celebrating this year forty years of hacking which is a long time and and taking a little bit just an perspective as people see now so let's start uh the the title to make sense of as that of by twelve well might wonder what those green things that they are that the going it's not the warm gain the famous weren't gain that just to be in in in the old days and on the mobile phones so if you look at those uh green thing a new reveal something out of eight actually it nice a description of representation all a mobile device is that would be in a moving the cool going round that white yeah area are use the congress centre so those would be the sensors that would be driving around of roads in in the device sees uh that you carry with you so here really uh typically nowadays which why call mobile computers because some of can be just and this so everything is a computer to me now this is synthetic data as we say but that's zoom a little bit so this is real data and this is real data as collected by did not get devices in prague a by looking the navigation request oh the different devices in real time you know so pretty posing them on this plane with the court in eight and the timing i think it's see there is no matter and the name but after a while you see just thing developing nicely to that map of prop so if we go for are and assume i'll this is a similar picture of europe up as seen by billy in some cory is all the all be max navigation not just by the way there are some interesting cultural differences this speaker start mining this as the topic of day um the green areas in fronds and also in russia so that the uh the the those areas the people are more interested in navigation as opposed to seven your of what the point of interest meeting finding restaurants or uh those are much more calm so there's a multitude of day that that i've face in my current to life it's also an a i the be do prove each to be an and here where this they are and the C or or search of mine is starting to be fulfilled we have access to data in a a totally new way is to to to develop of computers to to develop and of a multiple different aspects that i that touched so first i wanna uh this costs would you some of the source is of this type of data that that is available to you i my papers is to challenge you later on to think about what do you need to do what do you need to think about when you in real life want to address datasets like this and you wise thing and and uh so of making sense of the state so first of all i showed you now data that was based on the G P S location information in a time code actually actually mobile device already already like some multiple the for and sensor data at the same time we don't that they have a X are meters yeah actually for me camera and audio is also a a a a a sensor so each of these sensors that you at that is this device that that now so prevalent adds a new layer and there um more or more sensors that are coming a in the different radios that we are adding to these devices you're a more or more a a sensor data that coming from the same source is but at E to do is uh uh base layer of of location and time why do why consider a location and time to be different than the ad because from my perspective location and time can dish the usefulness of a lot of the data so if you don't know your location many of the application for example like asking where the close beer part don't make very much sense so what some location and time of very fundamental but beyond that you can add more and more layers and you in up in these piles of data which of course if you collapse them shows how he man amount of data we have available already from this type of the don't that about it the well at least i it a part of my language but only row room full of geeks so we most of us are so excited about that the different numbers i i was always possible i i one studied mathematics that they are these different terms for the same numbers and and of four in particular could be just as we are particularly excited of using uh just power some two so we talk about set up now now set up what is an interesting number because it's the time um currently approximately this year although much of the data E is in fact copies of each or we are producing a one point to set up of digital information but it it this number also as any a large number tends to be uh difficult to to grasp so um it before sort of try do uh look at the different sources of this at let's try to sort of reflect the little bit what it is so uh okay it's approximately close enough to be six that we am ten to the power of twenty one so we have twenty one zeros but that doesn't tell us too much so uh typically E um if you want to just to get an idea of a big number or you should reflect it with uh some major that you know so let's say that one but of this would be one meter and a good question to you is that now okay if if we have set meters oh but this that's how long what that this that's speech if we start from here is it here from to moon here to to peter here to i'll for sent that already okay so those have very clever and fast with the uh and know something about astronomy would figure out that this is is that meters is actually uh the same as the diameter of the milky way approximately which is about hundred thousand like your a lot of it's a big number now i actually prefer somewhat the the that bit more mundane uh reference sees that uh you can find on on on the net that when we were a looking at the numbers so one is that set up by just amount of information if all the people on uh at would be to twenty four seven four hundred year or it would be like seventy five really and sixteen gigabytes i had for a of the data which actually fills at four times the more line time uh but my favourite he's that if you like T V shows it would be watching the the you know the he C uh series or actual the first is sort of series all the T V series twenty four uh a four hundred and twenty five million years continuous talk about the sort of a getting bored a bit probably someone that okay now um the standard answer when a what we look at this type of a large dataset is that hey we should be using a approximations we should be using sampling we should be doing you know not exact things we we should be somehow you know many lady uh the the data set and then is that is correct it's actually very old idea um in this scare out have lights this is a very old tab eight thousand years old it it's the babylonian tablet that in fact shows a a approximation all the uh the square root a a a a a a unique uh square as sorry at the diagonal don't our uh although a unit square uh then that allows us in fact to do uh a square with calculation a for construction and and and complex so also to approximate measures sum of course of very all thing now unfortunately uh approach in a measures also as we know lose information set K C that is perfectly fine certain cases uh it cost is by sees that we know what will be very hard but the amount of data that we are talking about today by four requires as to go to these approximate method of course oh good have like was pressing the wrong but so let's look at a little bit about the source C east of the data now at this is a different picture than the previous ones because this is not showing the absolute capacity it is still the relative capacity of the type of the data that that is available for you go so in the old days when i remember one computer networks started the remember forty years of hacking one time there's a lot of F T P traffic going on E became very popular in the early eighties uh there was something like telnet i don't know how many remember or anything like that and but if T P was by far did don't mean a uh D that that was available meeting file transfer from one place do not that's to nineteen ninety ninety only nineteen nineties we all know um the one of the still annoying fact to the computer scientist that the physicist so the introduced the the H U T P protocol and and the way but it was not the computer this should and the web was born as only as you can see the if T P part start diminishing diminishing proportionally remember this is a proportional of the act up some will not a you know a amounts are going up all the time and to way easy grabbing a more and more she newsgroups are pretty happy that tell let this sort of disappearing email keeps it sort of a constant and in that if you go further to dine T five where has already captured half of the traffic and you see in the upper corner or something interesting like data appearing from individual peer-to-peer communication of the computer which didn't used to be a case in the past because we only had this few mainframes frames go and if we go even further to two thousand we did see that the video and video information starts to grab a larger and larger here oh the digital traffic now way be still strong but we D L the the purple part uh ease ease just morning there at the corner peer-to-peer and web dominating but it's scroll very fast so if we go no further of course to two thousand five you see that the video is getting bigger and um i don't know what a a because of the various different type of legally shoes another is used the the uh the sort of percent each of a peer to peer anyway not growing anymore to saying way and way is going down and if you a ripe to two thousand ten one could argue now that one the most important and interesting data sources that we and yeah is the video and nice there is no sign of it going down at the moment it actually if you believe just go which of course uh can be a little biased you the video will be so dominating at in the next couple of years on the network traffic that it will be the majority of and when is in fact going down proportion which is quite obvious because you think about the bits required from of the normal web back so when the quality sort that type of data that that he's he's moving around in these networks is obviously you video data so a lot of the things that i used to be interested in which where relate with sort of pattern matching in text or some stuff in the files of music is actually replace now in in stress to do this type of the mining or a a processing of video that that was the web now a king about where i just one of major something which it because it touched me so much in a related to well sort talk about video i wanna touch something um that a three D really captured my heart in in march in long beach ten this was there raw is from mit media lab where on capturing ninety thousand hours of video all he's child growing up and mining that we deal uh in such a way that for example he could show in the speed up manner or the development of the work water in he a you know in the the the language development of the time again a unique experiment but related to topic even more interestingly he's company as blue then is working and and delivering a they are sort of a uh and now it takes or visualization all uh both of the tv V broadcast real at with the social networking track basically linking something that is shown on the T V on the discussion that you have one on the net okay the little but different domain as a reference of this is the large had collider for those of you who have not seen that right picture um i do remember that basically when the large had drunk lighter in and the data read was planned there was a lot of talk about the capacity capacities now first of all a happened collider has a hundred and fifty million sensors so that's a lot of sensors an and we all know of course that these sensors are also proved using then the data with that in yeah so of very rapid speech so uh the actual approximate uh so the bound of data with you about in this a structure used one paid the bite per second i do remember that the original specs when we started doing the data rate i i i of was there in the in this huge european union consort you which has its benefits and a normal of your opinion and "'cause" so a a is uh we were talking about four point five that are bytes per second so the the the bottom some got up okay hundred fifty million sensors cool so this is the physics six experiments this is the science big science you know what does it do with you know the regular well or whatever it is this that very special device expensive device put some that that us come back this is now a picture of all of the whole well related to the picture use of already and you know prod your up um the the different uh core on on the on the navigation this based on twenty billion court now remember what i showed you earlier this a button one point two billion a devices currently on a that that of course and the number of a mobile device is is a four point or more than four billion if each of these one point to build and device has ten sensor it's ten more than ten bill sensors these ten billion sensors although they don't feet the sis that with the same speed than a large how drum or would be are still is super substantial amount of data that is available for and this is i'm not talking about the future somewhere i'm talking about the actual today not saying that all that sensor information is now at where collect the in one place but it really really really ease shown the potential and the different uh past that we have in the fit i mean the different types of sensors in this mobile about computers and i mentioned the sensors that are relay a with the a lot of the user in the phase or or or very different types of a uh uh uh uh a sort of uh positioning and so on but this an interesting you uh source that at to this sensor wall and that's the cognitive radio i so that the of some papers in a common give radio in this conference as use one to just want to point out that from this that about uh perspective for those also you by the way to calm radio used in the then and make a a location of the radio spectrum uh in such a way that the device itself can actually choose which part of the spectrum meet using uh a it's signal a transmission uh actually can be used for a out of things do and and a for the sensor at of so that put detailed introduction of county the radio will already bring that a again at new very interesting source of since information which is in the infrastructure itself so the traditional picture of having the device is talking to a power sell power and we'd already know something about the sting all strings that they can year uh a how to sell power can recognise of nice that the device is gonna change to a picture which is a much more mesh what a device are aware of each other's press sense or partially aware of each other's presence in different type a radius spec now these fingerprinting information ads and not the layer again which is inherent to the billy and mobile about computer infrastructure that we have well and that the source of data available for us all in that one is ease the social media there's currently about how nine hundred million social media users in the well of course if you look at that um that in principle means that there's is but something like one one point five billion of it's just social networks every day each of these base it's leaves a trace or a is a a operation and of course if you want do uh divide this we know what that a majority of this is coming from a single source place book seven hundred million currently but the important part here is that this about thirteen billion or more pieces of content axe by these users and this is the richest just context we have a one uh for for my because this is a uh as you know in face book or sort of information of all different types it is it is both image we is it's is a low eighties textual data E Ds a different lean C is sort of informative in a very different additional things that you can uh a of course C in the social space is that we have about sixty billion three expected in two thousand eleven and this sixty billion to and uh is still a growing number because we have a four hundred sixty thousand you tweeter are guns at a daily which by the is not to growth rate because there are also people that a drop that or accounts but still shows that the actual so the that population is growing and of course back to our favourite video that is that a lot of the traffic and in in the picture that showed you earlier comes from you two but uh of course in areas like in you dies states another it comes also from net flicks and so so thirteen million hours of video on in you to that doesn't look at very big number think about i was talking about the billions of there but these to remember that these videos are in fine it snippets or so so that two these thirteen billion our is much more uh in the number of videos that we have a below um G do pushed on on but so that million hours of video a it to you thirty five hours a new video uploaded per so those are you working on video mining you have great future and no head of now i'm i'm an optimistic and possibly person so i like this thing when all my life that things go up and the are upper right corner i like things growing i like things becoming more challenging i like things become fast there small bigger and so what's the problem well the problem is that as opposed to you know having this thing on the paper what as to form a or even ask calculation in your machine we're talking about real systems you and this data that exist somewhere we need to access it we need do you hand the like and if you want to make use of a we need to be build systems that that that sort of a a a a a able to do or what but what happens if you are not careful of building this just a that's a crack this actually uh the the the cover is from an older days but it to tall some ten we know that that the one some point decline in new york stock exchange in in a very short period of time which actually result of a complex a cohort it yeah a computer software that where of course doing uh uh uh what they are supposed to do they are competing on the market in the super whom human human speech the available data that they have making it looking at weak signals and in sort of a a uh a sort of a a or a the crash so like i always point out it's nice to write a paper then have a good learning out and a good predictive model a bit to be much more certain and when you start applying that in the real well and you course some interventions in the real world the two very different so what i want to talk about i was talking about the what now what is the data available i would like the little bit touch how and why wide what want to do it for this audience i mean i'm not talking in operating system conference i'm not talking in a networking conference on not talking about uh the people even in my formal of those databases database community when i was a can be just signed this undergrad i've as support about the memory computing trade and a little bit later i was told about the paging and you know virtual memory and and somewhat asked my point is that we are now unfortunately in a different architecture we are using a difference just a and when we are writing our algorithm and when we are running them we need to take into account to a a to greedy D tells which are beyond the turing machine yeah even beyond the for neumann sort of traditional computer model we need to look at that aspect if we really wanna work in the real with this data uh this a be yeah between what is the practise shouldn't traits correct in in in in in menu plating in of so called internet companies for example for the data and the work we do and the very at once work we do in a sophisticated methods of understanding that sometimes these things the gap is smaller sometimes it's much lot what a talk about a a and you with how a all the important aspects of this just then that we should take into account what we are writing our algorithm when we are you know building them for that the by well not building them for the uh well like my favourite was the or dataset that a over fit it so badly and list the city one of the things that has changed dramatic is that when we you building things we don't need bill them a in such a way that we have to uh make sure that the maximum requirement is somehow con because in the old days when you had a computer it had a certain amount of uh computing power said amount of memory and was a box some no L this C is an should of course that has sort of sneak in with clout so L L this T allows you to use dynamic to computation power or of a larger or a in today is such a way that you don't have to uh uh so the the three D term mine you model the competing power do you use no this is a to to the same development of you had in the uh i guess a into that read data structure of course where one has six table set and then the dynamic to and you defined find a dynamic table and you don't have to care about the the that that you will ever go wild so this feature where you need more data and you just grad more of the competing power and then at the same time of course this is meaningful for only because you have multiple users at the same time sharing this particular pull you will goal uh to a much lower T so in some sense this ls this city has um allowed us to do uh things which were not add all uh feasible in in the past it was not that long ago i think about seven eight years ago we were running multinomial pca out a on on eight i if fixed cluster for a search and stuff actually doing sort of uh search engine uh a probabilistic modeling all the the work of course is in in in a hundred million documents or more and a typical run there was deep limited by competing power that we have so we we had to run like three weeks in a role in a small cluster together get a model of like to fifteen million or twenty male and documents those you not be a a a no pca or mode only piece you knows that it sort of a under you do something clever it's actually quite computationally intensive thing and and there was no way you doing any kind of dynamic things so all our experiments where where sort of restrictive by to computing power at the university which was not that great so we we had to work on but the the L to sit B for as a historical remark it's to an to you very old knowledge and my okay very uh quotes from the science fiction church or uh as many of the computer size yeah ideas have a are very only in church or is this first uh commercially sold um story by our to see clock uh from this thing size fiction called uh a a rescue party and rescue party most telling about at race a call uh how do already a place called powered or with the race some power or yeah had a collective mine and depending on the problem in the universe the that race collected more minds dynamically to solve the problem so but in that today if you had to read a really big problem telepathic connection in the different places and the unit thus allowed to solve much harder problem this is nine this was really really are so fifty so the uh a sort of or was a used how well some of the site fix at uh and a or to reflects of a of the future a second aspect well as a list this C you might think okay so it's the cloud stuff is the robustness are rocks this argument easy a very complex one uh because it's basically depend on one um what do you wanna do so this is nice result by eric rule or from cow and this that depending on which time men she's you are interested in meeting you're accessing some data and you want to do a consistent access or you should be able to access when partitions are allowed in the network or yeah data should be always available if need you concept set is five or all of these at the same time of the you can only go in in this different or warners or a different of borders of the trying is such a way that if you wanna do for example search uh you're actually very petition for and at you have certain type of consistency but not all things are always a or you bit or end where you don't care about consistency at all you just basically are doing uh transfers but you very tolerant for petitions as as those who want to legally imposed against the this type of a part of C no uh and things have very available and on the other hand in this just just do body data bases that many many years ago and is working on them the consistency and availability a very important but they were not very tolerant for partition now why this is important this is important because we have talking about highly to but it just of remember i was talking about one billion devices that does the sitting in different parts of the well yeah can make it by different make words a or actually allowing different types of but uh uh mouth functions and there is them there is no consist then everything use up all the time notion i all so when you building you out rhythm they cannot be based bone getting all the necessary information but by necessity is you of course i all assume that you already figured out that in this is that the by well the outward have to be on line H batch algorithms of taking you know this twenty billion queries and running them and doing it it usually not the way to go because the response times uh for the problems that you want saul i'm not uh these so we had a ct and robust but the the one thing that is so dear to my heart these energy so i i preached just every place i'd bin now for the last two years i'm preaching it here too and i'm pointing out if five where a do that i would go to this field of energy efficient compute so my argument is that the current architecture as we will see these fun the mentally imposing the similar even theoretical call uh sort of boundaries and to to to computing ask we used to do with memory and computing energy is this so so let's look at the real life situation why of things become difficult it's it's stick exam O or of a a a a processing that you you know normally you used to this type of about processing where you have a single box now we are in a well what we a multiple devices that i connected to each other and you have your how or it your great algorithm and doing the video stuff has a choice where to go where to execute to let to look about this because it this problem in particular because E a very import if you to could the it look at the experience domains it it's experience i ancient you can of course running everything in in in the device itself which is the you know the this type of that mobile computer you could do the video editing here you get the video you at to here uh you get and the display well we know that uh in the case of a larger things this will be very very very slow all the user experience will be pretty bad and then in addition there might be some other sort of a user experience issues that yeah but it's basically little of course we can do peer to peer so we can steal somebody's else computing interesting idea taking a little bit more computational power or from the neighbourhood to do the video eating fine or what we can of course to ease that we think all okay we have this yeah last the city up there we have the clout so we send the P deal uh to uh the the actual data up to the cloud to be processed there where you can the fast process of course there are you add now talk to transmit so in the user experience die main should you one of the things that you want to use lee from a user perspective to uh uh just optimized is the time it and can't use it doesn't care where it happens you just as soon that these meeting we are living in a very be a well this is the pure experience per spec if you look at the economics perspective oh this one again if you to everything in the device itself not is that i now divided in that's a way that the law were in use the device upper in these the cloud in in the middle this of transmission somebody have to pay for the clout so but in the the day it usually doesn't come from from a from nowhere so you have to you have to pay for that economics of the cloud but form a a a a again at a user perspective you also paying on the transmission data com in most places though that will also be expressed but then we come to the very fundamental question if it do the video at eating on the device you're running out of energy in the car and mode very fast and we all know already that that even taking pictures not even at thing on the video well run out of our batteries very so okay not a very not a very feasible thing so what about if we just put it on the clock so i mean then we don't run out all sort the next thing is do we can steal our neighbours energy doesn't make you very popular because the the person who want to make a call next time and doesn't have any energy anymore probably doesn't like very much the idea that uh uh uh he or she has support your video at T if you put go to the cloud side we all know the problems already that this is like a no free lunch situation the cloud server from use is also and it might be a again G that is not immediately effect you but as a total off somebody will have a problem with the in G and we're talking about a green data centres nowadays a lot and this also fundamental lame which is an interesting question that how much can you concentrate in in a one place because you see in there bottom uh approach you're introducing new energy source every time you're uh introducing a new device that does to computing in the cloud the low energy load grows linearly at the and uh of the cloud side with respect to the customers it has to sit but even more fundamentally this trade and for D in real life tends to be controlled by the fact that sending bits but much more energy than computing part it is because of the the coding in that we have you know we are so far from the uh channel limit made that basically uh we are essentially uh i have to put much more power than we would need to to send uh the but be to to correct the noise errors that we have but basically this balance is good to did date almost all of the the the data manipulation i've been talking to do the balance between what do you compute locally and you energy where do you put where you have the energy of here and then what's the transmission energy did you are doing if you think about rendering for example watch screens directly from the class and i wanted to point out that um academically energy a a fundamental thing in a G something you cannot chi so it's very appealing theoretically in real life systems the the economics and experience are the ones that really also dictate what will be uh used in pratt so my question i sort of problems that i one lee would you is that basically we know and that shown that we have multiple sources of data available the question is that what's to a kid had talk so how do we capture parse and analyse on them on the fly meaning that that one do things on wine and radically different source sees this is um uh you know the sense sorry fusion he's one term that people use and different commune his we use different terminology to more me just the head of is attributes of source of that the second question ease the architecture question what what like take to build these socket to that actually a robust but and have strong elastic properties how do you right go out it means such a way that and even if you running in the signal much i would write the running T with what one billion device cross the uh maybe with the cloud component the third question is that how do we tackle this energy efficient computing because in fact and like i say and from the theoretical perspective almost like a the perspective that you had this after a four and model you can look at energy as a the different component there and do a lot of analysis even a like we need to balance environment concerns but this is practicalities and the in user experience for this and just now why Y in or G so fundamental to me it's fundamental for a reason that this first time in in my lifetime we are reaching the levels that then i can argue that i can foresee service sees that had not be bill not because of the call reasons but because of the reason that we don't not have enough energy on yeah the runs at to six billion user service what a run on the device and what is run on on the on the back so this is what i wanted to leave you a today i just one to remind you that my medic search for the medical data sets that quest actually has been filled i have always think than things and and a well exciting me there lying there and now i see that about twenty five years of my life i haven't solved very many things related but this this is i've sold a lot of things would related but i don't think would you guys in a community with the great P H student is that i've have the privilege to work with but basically i guess said i now know that we are facing an air a so there are almost need to our exist then is that we as a research communities need to address in a different way okay so that's what i want to say to stop thank you very much for your attention i Q for very exciting presentation we we have a very challenging research problems to work on with a whole community here so problem in in them scientific uh uh uh four as for global a local uh energy consumption and problem of the whole or and uh we have a time for couples or questions so please okay as mike so excellent i very much oh two two we a so i know it's your or good thing of be important in this environment our privacy and security and so i i so the like my own close excess there have yeah for all network we work yes and i deliberately chose not the say the work privacy and security as somebody characterised rice me a long time ago that henry if we reset aspect you always doing is violating i C really people's privacy and that's of them and no i think it very seriously yeah i just decided to leave it for the question because i knew that the question what car and of course first of all at so the that they can very sign this perspective the more we get or information the more i can reverse engineer that's a fundamental that and i could even do it in the ways that people think it uh you know you you and and mice thing sell you at run noise but if you can predict the noise model you can reverse engineer a lot of stuff and you could do very complex things now for me first of what privacy is always a trade off it strike a reliability really this is certain pay all you get from something and certain cost that you have if the cost is higher than the pay off you should not do it so the cost for your privacy and and the aspect you should be able to first of all use and always be able to opt out that that's that's a the the first but the second i of point out that that learned that and never thought so much was that the or a lot of things where you could do a a or trained how to get and alice without violating any kind of privacy ask you basically at hating like this traffic sure sure the ear that does that just totally and no anonymous no idea who is their don't will the individual points are followed in a sequence yeah just point in the time in the data say you don't know that they coming from the same source you can still do a meaningful alice that's the first good second good nice for research community that the are privacy preserving make is that you can build in this yeah sort of put the traffic ways of handling this thing so it's a future research brought and a third question is that i usually do the channel see how many you guys in this room has actually to of your cookies i mean just to be very popular just to be very popular but also this some if fit of not turning of them more relays in this and that again so i E each very cultural location only what happens but i hope we you and and my main point always is uh and it is nice you should know and use should be able to opt out but if this it twice if you want to uh a a a a get some benefit out of that information that is available security ease of different ish i i think everybody shares the the the question of the security problems uh the concept of the security problems that we have and and D sub very complex is used again called zero even regular to issues that we face a different ways in your a a in us any nation my lattes are working and i'm working on growth economies to was than well and i can tell you that these issues a very different in different mark security uh protocols are a good research topic do i think the the privacy consent tends to be the higher one among the people a we know all the problems that currently are face books and google another side facing it is but don't i decided not to it over in for size this because i was talking from a size perspective and thus a recess perspective but we have to be of course it it just about that a a work we do to right right no short question and hopefully a ask