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