[Applause] ladies gentlemen thank you for inviting
ladies gentlemen thank you for inviting
ladies gentlemen thank you for inviting me here in Riga Mario Martino I come
me here in Riga Mario Martino I come
me here in Riga Mario Martino I come from Cambridge us you know and this is
from Cambridge us you know and this is
from Cambridge us you know and this is sadly the wrong way to start a TED Talks
sadly the wrong way to start a TED Talks
sadly the wrong way to start a TED Talks because we first to come here two weeks
because we first to come here two weeks
because we first to come here two weeks ago I decided to to look around what
ago I decided to to look around what
ago I decided to to look around what other people say about Chris Anderson he
other people say about Chris Anderson he
other people say about Chris Anderson he just wrote a beautiful book TED Talks
just wrote a beautiful book TED Talks
just wrote a beautiful book TED Talks and I read this book and I was not in a
and I read this book and I was not in a
and I read this book and I was not in a fight I decide to buy all the books
fight I decide to buy all the books
fight I decide to buy all the books available now for my son in my book shop
available now for my son in my book shop
available now for my son in my book shop close to my house in Cambridge about
close to my house in Cambridge about
close to my house in Cambridge about these topics and I do that all the time
these topics and I do that all the time
these topics and I do that all the time because I really love books this is a
because I really love books this is a
because I really love books this is a video that I should for you to just show
video that I should for you to just show
video that I should for you to just show to you how many book I just bought in
to you how many book I just bought in
to you how many book I just bought in the last six months so constantly I’m by
the last six months so constantly I’m by
the last six months so constantly I’m by book about different topics and you can
book about different topics and you can
book about different topics and you can see I working out of Big Data and Daddy
see I working out of Big Data and Daddy
see I working out of Big Data and Daddy of interaction design and there’s so
of interaction design and there’s so
of interaction design and there’s so many book about machine learning and
many book about machine learning and
many book about machine learning and book by made by laszlo barabasi
book by made by laszlo barabasi
book by made by laszlo barabasi William Britain David McLean 3 Kandinsky
William Britain David McLean 3 Kandinsky
William Britain David McLean 3 Kandinsky Kevin Lynch Horan Tonelli
Kevin Lynch Horan Tonelli
Kevin Lynch Horan Tonelli so many outer that really are part of my
so many outer that really are part of my
so many outer that really are part of my life
life
life Bruno Minari Iowa study eminent in a
Bruno Minari Iowa study eminent in a
Bruno Minari Iowa study eminent in a protective of million so why a book are
protective of million so why a book are
protective of million so why a book are so important I think if you look at my
so important I think if you look at my
so important I think if you look at my collection of books in the last six
collection of books in the last six
collection of books in the last six months you can see some topics emerge
months you can see some topics emerge
months you can see some topics emerge like that book the reality machine
like that book the reality machine
like that book the reality machine learning artificial intelligence the
learning artificial intelligence the
learning artificial intelligence the book they talk about user experience and
book they talk about user experience and
book they talk about user experience and information design graphic design and of
information design graphic design and of
information design graphic design and of course this is my favorite collection or
course this is my favorite collection or
course this is my favorite collection or the column regarding the field of data
the column regarding the field of data
the column regarding the field of data visualization so I come from the field
visualization so I come from the field
visualization so I come from the field of data visualization and if we look a
of data visualization and if we look a
of data visualization and if we look a little bit deeply inside we can we can
little bit deeply inside we can we can
little bit deeply inside we can we can see in every single book a story that
see in every single book a story that
see in every single book a story that are very well done about other no
are very well done about other no
are very well done about other no statistical model computational analysis
statistical model computational analysis
statistical model computational analysis anyway inside to every single book three
anyway inside to every single book three
anyway inside to every single book three something magic that we don’t really see
something magic that we don’t really see
something magic that we don’t really see so well so what is this this is just an
so well so what is this this is just an
so well so what is this this is just an analysis of the first page
analysis of the first page
analysis of the first page the book of why information growth from
the book of why information growth from
the book of why information growth from my friend this is a lead algo and I
my friend this is a lead algo and I
my friend this is a lead algo and I think it’s very appropriate to topic so
think it’s very appropriate to topic so
think it’s very appropriate to topic so why information girl and you can see so
why information girl and you can see so
why information girl and you can see so many details emerge from the knives of
many details emerge from the knives of
many details emerge from the knives of just this page and we can observe some
just this page and we can observe some
just this page and we can observe some emotional analysis and we can see there
emotional analysis and we can see there
emotional analysis and we can see there is a lot younger discussed and a lot
is a lot younger discussed and a lot
is a lot younger discussed and a lot emotional range and it is very normal
emotional range and it is very normal
emotional range and it is very normal because this is introductional page
because this is introductional page
because this is introductional page where the outer are to really present
where the outer are to really present
where the outer are to really present deeply emotional is the topic that
deeply emotional is the topic that
deeply emotional is the topic that you’re talking about this is a way the
you’re talking about this is a way the
you’re talking about this is a way the computer of looking the book so a big
computer of looking the book so a big
computer of looking the book so a big collection my big collection of book is
collection my big collection of book is
collection my big collection of book is this for my computer and for your
this for my computer and for your
this for my computer and for your computer to see if you use the right
computer to see if you use the right
computer to see if you use the right hacker it so a lot a lot of content that
hacker it so a lot a lot of content that
hacker it so a lot a lot of content that the system highlight because are
the system highlight because are
the system highlight because are particularly interesting and there is a
particularly interesting and there is a
particularly interesting and there is a interesting way to observe with a high
interesting way to observe with a high
interesting way to observe with a high of natural science of this connection
of natural science of this connection
of natural science of this connection between topics and many type of entity
between topics and many type of entity
between topics and many type of entity you can see all this connection emerge
you can see all this connection emerge
you can see all this connection emerge spontaneously because the computer
spontaneously because the computer
spontaneously because the computer recognize all this content automatic
recognize all this content automatic
recognize all this content automatic sometimes to book a related because
sometimes to book a related because
sometimes to book a related because there is the same topics in a different
there is the same topics in a different
there is the same topics in a different multiple topics in common it is very
multiple topics in common it is very
multiple topics in common it is very obviously to find a location
obviously to find a location
obviously to find a location organization company and of course a
organization company and of course a
organization company and of course a people but if you and one person can
people but if you and one person can
people but if you and one person can easily identify connection between a
easily identify connection between a
easily identify connection between a book to another but if you’re thinking
book to another but if you’re thinking
book to another but if you’re thinking about the thousand thousand convention a
about the thousand thousand convention a
about the thousand thousand convention a connection that can emerge but this
connection that can emerge but this
connection that can emerge but this analogy you can see the spontaneously
analogy you can see the spontaneously
analogy you can see the spontaneously some cluster emerges and the book will
some cluster emerges and the book will
some cluster emerges and the book will start to be together close each other
start to be together close each other
start to be together close each other because they have many entity in common
because they have many entity in common
because they have many entity in common this is only possible when you have a
this is only possible when you have a
this is only possible when you have a intelligent algorithm
intelligent algorithm
intelligent algorithm identify different type of entity inside
identify different type of entity inside
identify different type of entity inside without artificial intelligence without
without artificial intelligence without
without artificial intelligence without this machine learning system without
this machine learning system without
this machine learning system without language processing we are not really
language processing we are not really
language processing we are not really able to ever the big picture about the
able to ever the big picture about the
able to ever the big picture about the interconnection of topics that emerge
interconnection of topics that emerge
interconnection of topics that emerge from my book collection
from my book collection
from my book collection and I think this is a very common
and I think this is a very common
and I think this is a very common problem for everybody not just for me
problem for everybody not just for me
problem for everybody not just for me okay for me it’s particularly maybe I’m
okay for me it’s particularly maybe I’m
okay for me it’s particularly maybe I’m too too much obsess about this behavior
too too much obsess about this behavior
too too much obsess about this behavior to buy a book and read the paper every
to buy a book and read the paper every
to buy a book and read the paper every time there to resolve some technical
time there to resolve some technical
time there to resolve some technical problem but you know we are full of our
problem but you know we are full of our
problem but you know we are full of our brain doesn’t work really in a way that
brain doesn’t work really in a way that
brain doesn’t work really in a way that we dream sometimes we are some bias and
we dream sometimes we are some bias and
we dream sometimes we are some bias and cognitive bias and we use artificial
cognitive bias and we use artificial
cognitive bias and we use artificial intelligence maybe we can resolve this
intelligence maybe we can resolve this
intelligence maybe we can resolve this bias that system is samp
bias that system is samp
bias that system is samp like if we’re looking this guy we are
like if we’re looking this guy we are
like if we’re looking this guy we are looking we are able to image Andromeda
looking we are able to image Andromeda
looking we are able to image Andromeda Cassiopeia or this beautiful great
Cassiopeia or this beautiful great
Cassiopeia or this beautiful great picture that I’m just a projection of
picture that I’m just a projection of
picture that I’m just a projection of our fantasy because we’re really good in
our fantasy because we’re really good in
our fantasy because we’re really good in identified pattern but too much good we
identified pattern but too much good we
identified pattern but too much good we find pattern everywhere silhouette path
find pattern everywhere silhouette path
find pattern everywhere silhouette path had been exist so we have so many type
had been exist so we have so many type
had been exist so we have so many type of bias sometimes we forget that we
of bias sometimes we forget that we
of bias sometimes we forget that we project on top to the other people that
project on top to the other people that
project on top to the other people that are in front to us our personal emotions
are in front to us our personal emotions
are in front to us our personal emotions so I’m feel good today and feel
so I’m feel good today and feel
so I’m feel good today and feel optimistic and I’m able to see this a
optimistic and I’m able to see this a
optimistic and I’m able to see this a positive characteristic around all the
positive characteristic around all the
positive characteristic around all the people around to me so so many aspects
people around to me so so many aspects
people around to me so so many aspects of our life really match with our
of our life really match with our
of our life really match with our capability to absorb information from
capability to absorb information from
capability to absorb information from outside interpreted this information but
outside interpreted this information but
outside interpreted this information but so frequently this interpretation is
so frequently this interpretation is
so frequently this interpretation is wrong let’s do an experiment together to
wrong let’s do an experiment together to
wrong let’s do an experiment together to see if we are you’re able to not to fall
see if we are you’re able to not to fall
see if we are you’re able to not to fall of this player and the wearing white
of this player and the wearing white
of this player and the wearing white t-shirt and count how many times they
t-shirt and count how many times they
t-shirt and count how many times they passes a basketball each other so let’s
passes a basketball each other so let’s
passes a basketball each other so let’s see together the video count because
see together the video count because
see together the video count because after we’ll ask you if you find the
after we’ll ask you if you find the
after we’ll ask you if you find the right number so it’s very old experiment
right number so it’s very old experiment
right number so it’s very old experiment but still I think is very interesting to
but still I think is very interesting to
but still I think is very interesting to see so the basketball is is a okay
see so the basketball is is a okay
see so the basketball is is a okay maybe the video is also the color not so
maybe the video is also the color not so
maybe the video is also the color not so vivid but so how many times guess a
vivid but so how many times guess a
vivid but so how many times guess a number 16 is the right is 15 so very
number 16 is the right is 15 so very
number 16 is the right is 15 so very close but the point did you see
close but the point did you see
close but the point did you see gorilla everybody so together yeah many
gorilla everybody so together yeah many
gorilla everybody so together yeah many of you especially if you watch this
of you especially if you watch this
of you especially if you watch this video for the first time so I’m so still
video for the first time so I’m so still
video for the first time so I’m so still impressed about these experiments
impressed about these experiments
impressed about these experiments because the first time they saw this
because the first time they saw this
because the first time they saw this video I was completely unable to see the
video I was completely unable to see the
video I was completely unable to see the gorilla was two times I said oh my god
gorilla was two times I said oh my god
gorilla was two times I said oh my god there is a gorilla there but if we use a
there is a gorilla there but if we use a
there is a gorilla there but if we use a machine to look in this video there is
machine to look in this video there is
machine to look in this video there is no problem because we can activate some
no problem because we can activate some
no problem because we can activate some simple system that identify is there a
simple system that identify is there a
simple system that identify is there a woman these are men in the video and
woman these are men in the video and
woman these are men in the video and when the usability analysis to identify
when the usability analysis to identify
when the usability analysis to identify the gorilla
the gorilla
the gorilla it doesn’t care it is not focus in the
it doesn’t care it is not focus in the
it doesn’t care it is not focus in the goal so the machine is just a huge
goal so the machine is just a huge
goal so the machine is just a huge collection of algorithm so and when the
collection of algorithm so and when the
collection of algorithm so and when the gorillas live that’s it the gorillas
gorillas live that’s it the gorillas
gorillas live that’s it the gorillas live so the point is okay maybe they go
live so the point is okay maybe they go
live so the point is okay maybe they go realize very easy task but let’s see
realize very easy task but let’s see
realize very easy task but let’s see something more complicated like a few
something more complicated like a few
something more complicated like a few weeks ago I was in San Pittsburgh and
weeks ago I was in San Pittsburgh and
weeks ago I was in San Pittsburgh and his it’s just that few minute walk on
his it’s just that few minute walk on
his it’s just that few minute walk on the street and you can see how many
the street and you can see how many
the street and you can see how many detail them and the computer is able to
detail them and the computer is able to
detail them and the computer is able to identify in this case the algorithm to
identify in this case the algorithm to
identify in this case the algorithm to identify people so but I have a same
identify people so but I have a same
identify people so but I have a same question for you many people are in the
question for you many people are in the
question for you many people are in the street and you can’t of course not
street and you can’t of course not
street and you can’t of course not it’s boring we don’t want to do and many
it’s boring we don’t want to do and many
it’s boring we don’t want to do and many people are addressing a blue t-shirt I
people are addressing a blue t-shirt I
people are addressing a blue t-shirt I don’t know
don’t know
don’t know so there are so many inform information
so there are so many inform information
so there are so many inform information they tell the demerger around o our
they tell the demerger around o our
they tell the demerger around o our world every day every second that we
world every day every second that we
world every day every second that we don’t care about because you know we are
don’t care about because you know we are
don’t care about because you know we are able to resolve a task we are able to
able to resolve a task we are able to
able to resolve a task we are able to talk about a person but we cannot count
talk about a person but we cannot count
talk about a person but we cannot count on this information especially we don’t
on this information especially we don’t
on this information especially we don’t really care but maybe so many
really care but maybe so many
really care but maybe so many interesting things emerge from this
interesting things emerge from this
interesting things emerge from this translation of this information in a
translation of this information in a
translation of this information in a data so this instructor information
data so this instructor information
data so this instructor information there video at our text from our daily
there video at our text from our daily
there video at our text from our daily work no we produce all this amount of
work no we produce all this amount of
work no we produce all this amount of information and we love this information
information and we love this information
information and we love this information we don’t really use it and maybe
we don’t really use it and maybe
we don’t really use it and maybe something can emerge from use this
something can emerge from use this
something can emerge from use this information in my daily work I’m
information in my daily work I’m
information in my daily work I’m interested in a health care problem so
interested in a health care problem so
interested in a health care problem so at the moment of what I am working what
at the moment of what I am working what
at the moment of what I am working what Sun health so one of my problem is to
Sun health so one of my problem is to
Sun health so one of my problem is to try to identify from a
try to identify from a
try to identify from a collection of a scientific paper is
collection of a scientific paper is
collection of a scientific paper is there some interesting correlation
there some interesting correlation
there some interesting correlation between some gene tp53 and some disease
between some gene tp53 and some disease
between some gene tp53 and some disease diabetes or gt350 3 and this is in your
diabetes or gt350 3 and this is in your
diabetes or gt350 3 and this is in your plasma so in what way by using so I want
plasma so in what way by using so I want
plasma so in what way by using so I want to give you a very pragmatic example and
to give you a very pragmatic example and
to give you a very pragmatic example and what we are using all this amount of
what we are using all this amount of
what we are using all this amount of data that I can extract by using these
data that I can extract by using these
data that I can extract by using these technology so let’s see let’s see an
technology so let’s see let’s see an
technology so let’s see let’s see an example of my daily work so I build in
example of my daily work so I build in
example of my daily work so I build in this interface so I’m able to say that
this interface so I’m able to say that
this interface so I’m able to say that these are disease autoimmune disease is
these are disease autoimmune disease is
these are disease autoimmune disease is a related to this effort gene and if I
a related to this effort gene and if I
a related to this effort gene and if I look inside discover this gene this is
look inside discover this gene this is
look inside discover this gene this is related with these three gene that is so
related with these three gene that is so
related with these three gene that is so before so it’s very interesting starting
before so it’s very interesting starting
before so it’s very interesting starting point so if I look in this gene and I
point so if I look in this gene and I
point so if I look in this gene and I try to understand the relation with is
try to understand the relation with is
try to understand the relation with is this gene and the protein they are
this gene and the protein they are
this gene and the protein they are related with this gene maybe I can start
related with this gene maybe I can start
related with this gene maybe I can start to find a drug that is able to in some
to find a drug that is able to in some
to find a drug that is able to in some way interact with this gene so let’s try
way interact with this gene so let’s try
way interact with this gene so let’s try diesel interface where you can try
diesel interface where you can try
diesel interface where you can try different type of drug available in the
different type of drug available in the
different type of drug available in the market chi splitting is a type of drug
market chi splitting is a type of drug
market chi splitting is a type of drug that really is related with this type
that really is related with this type
that really is related with this type with some protein disconnect with this
with some protein disconnect with this
with some protein disconnect with this gene and what is a result the result is
gene and what is a result the result is
gene and what is a result the result is I can find in a direct way a connection
I can find in a direct way a connection
I can find in a direct way a connection between a drug and a way to interact
between a drug and a way to interact
between a drug and a way to interact with this gene and maybe this will be
with this gene and maybe this will be
with this gene and maybe this will be the starting point to resolve this type
the starting point to resolve this type
the starting point to resolve this type of disease
of disease
of disease okay it’s very complicated I won’t talk
okay it’s very complicated I won’t talk
okay it’s very complicated I won’t talk too much about this type of problem with
too much about this type of problem with
too much about this type of problem with you but let’s find another sample they
you but let’s find another sample they
you but let’s find another sample they may be more enjoyable something related
may be more enjoyable something related
may be more enjoyable something related with with us what about explore and TED
with with us what about explore and TED
with with us what about explore and TED Talks
Talks
Talks no it’s like I’ll talk in a TED speech
no it’s like I’ll talk in a TED speech
no it’s like I’ll talk in a TED speech talk about TED speech I like this type
talk about TED speech I like this type
talk about TED speech I like this type of joke so let’s use it at talk like a
of joke so let’s use it at talk like a
of joke so let’s use it at talk like a database to Splore together so
database to Splore together so
database to Splore together so essentially if we sprawl this TED talk
essentially if we sprawl this TED talk
essentially if we sprawl this TED talk we can see I probably if you’re here you
we can see I probably if you’re here you
we can see I probably if you’re here you are a passionated about TED Talks so you
are a passionated about TED Talks so you
are a passionated about TED Talks so you know the many talks are in some way
know the many talks are in some way
know the many talks are in some way linked each other they talk about this
linked each other they talk about this
linked each other they talk about this in the same topics or the outer is come
in the same topics or the outer is come
in the same topics or the outer is come from the same field so this is interface
from the same field so this is interface
from the same field so this is interface that we build where you can see a big
that we build where you can see a big
that we build where you can see a big knowledge map all the information that
knowledge map all the information that
knowledge map all the information that come from that the TED collection so
come from that the TED collection so
come from that the TED collection so you can navigate a little you can see
you can navigate a little you can see
you can navigate a little you can see there is some clusters and talk across
there is some clusters and talk across
there is some clusters and talk across each other because they talk about the
each other because they talk about the
each other because they talk about the same topics and here is a big list of
same topics and here is a big list of
same topics and here is a big list of the most important topics to emerge
the most important topics to emerge
the most important topics to emerge ranking in function to the the frequency
ranking in function to the the frequency
ranking in function to the the frequency of this topic you know this collection
of this topic you know this collection
of this topic you know this collection so every time you touch a topic you can
so every time you touch a topic you can
so every time you touch a topic you can see the cluster emerge in the map but
see the cluster emerge in the map but
see the cluster emerge in the map but this is a more friendly way with to
this is a more friendly way with to
this is a more friendly way with to interact with this data like just ask
interact with this data like just ask
interact with this data like just ask something very natural let’s make this
something very natural let’s make this
something very natural let’s make this question a question like what is the
question a question like what is the
question a question like what is the relation between money and happiness I
relation between money and happiness I
relation between money and happiness I think is interesting topics and there is
think is interesting topics and there is
think is interesting topics and there is some result so there is a collection of
some result so there is a collection of
some result so there is a collection of for video let’s see just the first two
for video let’s see just the first two
for video let’s see just the first two you spend that money on consumer goods
you spend that money on consumer goods
you spend that money on consumer goods which you hope you’ll enjoy using but
which you hope you’ll enjoy using but
which you hope you’ll enjoy using but then the money’s gone you have to work
then the money’s gone you have to work
then the money’s gone you have to work hard to get more spend more and to
hard to get more spend more and to
hard to get more spend more and to maintain the same level of happiness
maintain the same level of happiness
maintain the same level of happiness it’s kind of a hedonic treadmill you
it’s kind of a hedonic treadmill you
it’s kind of a hedonic treadmill you never get off and you we see it in
never get off and you we see it in
never get off and you we see it in religions and self-help books that money
religions and self-help books that money
religions and self-help books that money can’t buy happiness and I want to
can’t buy happiness and I want to
can’t buy happiness and I want to suggest today that in fact that’s wrong
suggest today that in fact that’s wrong
suggest today that in fact that’s wrong and that so in this interface we are
and that so in this interface we are
and that so in this interface we are different component like we can avert
different component like we can avert
different component like we can avert overview of the all the top of the
overview of the all the top of the
overview of the all the top of the content of the speech but the center is
content of the speech but the center is
content of the speech but the center is very cool we have a timeline where we
very cool we have a timeline where we
very cool we have a timeline where we can explore other entity and top is that
can explore other entity and top is that
can explore other entity and top is that this author was talking about during
this author was talking about during
this author was talking about during whole speech so we can activate a new
whole speech so we can activate a new
whole speech so we can activate a new way to jump from one talk to another by
way to jump from one talk to another by
way to jump from one talk to another by using this dynamic topic trended
using this dynamic topic trended
using this dynamic topic trended timeline and you can understand the
timeline and you can understand the
timeline and you can understand the power of this type of technology in many
power of this type of technology in many
power of this type of technology in many other field not just using this type of
other field not just using this type of
other field not just using this type of information so in some way the dream a
information so in some way the dream a
information so in some way the dream a few years ago from the 50 to build this
few years ago from the 50 to build this
few years ago from the 50 to build this machine able to talk with us to answer
machine able to talk with us to answer
machine able to talk with us to answer to our question is close to be done
to our question is close to be done
to our question is close to be done probably we will never go to the point
probably we will never go to the point
probably we will never go to the point where the machine will directional test
where the machine will directional test
where the machine will directional test ran on so soon but we’re there and okay
ran on so soon but we’re there and okay
ran on so soon but we’re there and okay we cannot be too optimistic honestly
we cannot be too optimistic honestly
we cannot be too optimistic honestly there’s still so many technology to
there’s still so many technology to
there’s still so many technology to build but the question answer is in the
build but the question answer is in the
build but the question answer is in the right direction and I want to close my
right direction and I want to close my
right direction and I want to close my speech by
speech by
speech by deeper inside in this technology the way
deeper inside in this technology the way
deeper inside in this technology the way to if you image a good way to really
to if you image a good way to really
to if you image a good way to really create a connection between us and
create a connection between us and
create a connection between us and machine is probably this type of a
machine is probably this type of a
machine is probably this type of a question and answering a SKU something a
question and answering a SKU something a
question and answering a SKU something a natural language you tell me something a
natural language you tell me something a
natural language you tell me something a natural language so IBM is a pioneer in
natural language so IBM is a pioneer in
natural language so IBM is a pioneer in this field so you remember probably a
this field so you remember probably a
this field so you remember probably a few years ago or the job party game is a
few years ago or the job party game is a
few years ago or the job party game is a very famous game in u.s. do you know
very famous game in u.s. do you know
very famous game in u.s. do you know this game someone who you know this game
this game someone who you know this game
this game someone who you know this game okay
okay
okay few of you essentially is like a twist
few of you essentially is like a twist
few of you essentially is like a twist as that user the traditional type of
as that user the traditional type of
as that user the traditional type of games there is a answer you have to find
games there is a answer you have to find
games there is a answer you have to find the question you can see Watson was the
the question you can see Watson was the
the question you can see Watson was the winner obviously otherwise I was not
winner obviously otherwise I was not
winner obviously otherwise I was not here and using this example so was a
here and using this example so was a
here and using this example so was a winner and but the problem is if you
winner and but the problem is if you
winner and but the problem is if you have this question so in 1898 the
have this question so in 1898 the
have this question so in 1898 the Portugal celebrated the 14th anniversary
Portugal celebrated the 14th anniversary
Portugal celebrated the 14th anniversary of these explorers our arrival in India
of these explorers our arrival in India
of these explorers our arrival in India so the answer can be this so one
so the answer can be this so one
so the answer can be this so one supporting evidence can be this because
supporting evidence can be this because
supporting evidence can be this because we find inside the word the Portugal
we find inside the word the Portugal
we find inside the word the Portugal that Portugal Portugal the India India
that Portugal Portugal the India India
that Portugal Portugal the India India and in May that is May so the machine
and in May that is May so the machine
and in May that is May so the machine working this way imagine possible answer
working this way imagine possible answer
working this way imagine possible answer with a possible with a with a new
with a possible with a with a new
with a possible with a with a new question but the point is this is wrong
question but the point is this is wrong
question but the point is this is wrong answer is no Gary the right answer is a
answer is no Gary the right answer is a
answer is no Gary the right answer is a Vasco de Gama why because you have to
Vasco de Gama why because you have to
Vasco de Gama why because you have to build something more
build something more
build something more you cannot just match this keyword you
you cannot just match this keyword you
you cannot just match this keyword you have to use a system to match the data
have to use a system to match the data
have to use a system to match the data the timing so that a match technology
the timing so that a match technology
the timing so that a match technology you have to create these Jo technology
you have to create these Jo technology
you have to create these Jo technology so now we know the India is kept at
so now we know the India is kept at
so now we know the India is kept at beach now we know that this timing is
beach now we know that this timing is
beach now we know that this timing is this timing and the Machine now is able
this timing and the Machine now is able
this timing and the Machine now is able to give you the right answer so it’s
to give you the right answer so it’s
to give you the right answer so it’s only mad there is no spirituality there
only mad there is no spirituality there
only mad there is no spirituality there is no relief nothing more than just mad
is no relief nothing more than just mad
is no relief nothing more than just mad so this is the end of my speech I won’t
so this is the end of my speech I won’t
so this is the end of my speech I won’t just tell to you that to go now we are
just tell to you that to go now we are
just tell to you that to go now we are in the Holi of semantic so we are able
in the Holi of semantic so we are able
in the Holi of semantic so we are able to identify topics but we can we are so
to identify topics but we can we are so
to identify topics but we can we are so far away to be an area of narrative with
far away to be an area of narrative with
far away to be an area of narrative with the machines really able to understand
the machines really able to understand
the machines really able to understand what we are writing our way to
what we are writing our way to
what we are writing our way to communicate
communicate
communicate but let’s forget that is a nightmare to
but let’s forget that is a nightmare to
but let’s forget that is a nightmare to have a machine like that what is the
have a machine like that what is the
have a machine like that what is the reality today there is a machine able to
reality today there is a machine able to
reality today there is a machine able to work with us because understand our
work with us because understand our
work with us because understand our semantics is able to support us in all
semantics is able to support us in all
semantics is able to support us in all our daily work activity or hobby and
our daily work activity or hobby and
our daily work activity or hobby and let’s use this technology because it is
let’s use this technology because it is
let’s use this technology because it is the best way to really understand all
the best way to really understand all
the best way to really understand all the book that I buy every six month and
the book that I buy every six month and
the book that I buy every six month and all the book and paper and content that
all the book and paper and content that
all the book and paper and content that you read every day thank you so much
you read every day thank you so much
you read every day thank you so much [Applause]
”
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