are you there I am here listening to you what is your name as my buddy
what is your name as my buddy
what is your name as my buddy Shakespeare once said what’s in a name
Shakespeare once said what’s in a name
Shakespeare once said what’s in a name but you can call me Tommy
but you can call me Tommy
but you can call me Tommy what is your favorite book I love
what is your favorite book I love
what is your favorite book I love reading the robots of dawn by Isaac
reading the robots of dawn by Isaac
reading the robots of dawn by Isaac Asimov what is your favorite song I love
Asimov what is your favorite song I love
Asimov what is your favorite song I love singing want to hear some no thank you
singing want to hear some no thank you
singing want to hear some no thank you can you tell me a joke I love helping
can you tell me a joke I love helping
can you tell me a joke I love helping humans can you tell me a joke there are
humans can you tell me a joke there are
humans can you tell me a joke there are two ways to write our free programs and
two ways to write our free programs and
two ways to write our free programs and only the third way he works thank you
but I want to take you a little bit on a
but I want to take you a little bit on a journey of computing intelligence across
journey of computing intelligence across
journey of computing intelligence across time if we think of a story of computing
time if we think of a story of computing
time if we think of a story of computing we identify three eras the first era
we identify three eras the first era
we identify three eras the first era started with tabulating I was just
started with tabulating I was just
started with tabulating I was just counting things counting people counting
counting things counting people counting
counting things counting people counting money
money
money those were the times of the single
those were the times of the single
those were the times of the single purpose computers they were built
purpose computers they were built
purpose computers they were built without one function specifically fifty
without one function specifically fifty
without one function specifically fifty years later we started what we called
years later we started what we called
years later we started what we called the programmable era computers that can
the programmable era computers that can
the programmable era computers that can follow a set of instructions or programs
follow a set of instructions or programs
follow a set of instructions or programs this around lasted up till today even
this around lasted up till today even
this around lasted up till today even the computer that you have with you in
the computer that you have with you in
the computer that you have with you in your pocket your phone is using this
your pocket your phone is using this
your pocket your phone is using this type of computing but six years ago we
type of computing but six years ago we
type of computing but six years ago we started what we call the cognitive
started what we call the cognitive
started what we call the cognitive era many of you saw in the US television
era many of you saw in the US television
era many of you saw in the US television show a jeopardy Watson playing against
show a jeopardy Watson playing against
show a jeopardy Watson playing against the best players in the world
the best players in the world
the best players in the world you remember what was the outcome of
you remember what was the outcome of
you remember what was the outcome of that show yes we defeated the best
that show yes we defeated the best
that show yes we defeated the best players in the world but it was not easy
players in the world but it was not easy
players in the world but it was not easy playing jeopardy was very challenging
playing jeopardy was very challenging
playing jeopardy was very challenging task because human language is full
task because human language is full
task because human language is full ambiguity humor in context so this
ambiguity humor in context so this
ambiguity humor in context so this system was able to answer questions in 3
system was able to answer questions in 3
system was able to answer questions in 3 to 6 seconds about anything music poetry
to 6 seconds about anything music poetry
to 6 seconds about anything music poetry it was able to correctly answer the
it was able to correctly answer the
it was able to correctly answer the questions 80% of the time if we play 50
questions 80% of the time if we play 50
questions 80% of the time if we play 50 percent of the opportunities so this
percent of the opportunities so this
percent of the opportunities so this system we call it Watson start the
system we call it Watson start the
system we call it Watson start the cognitive system era well how does it
cognitive system era well how does it
cognitive system era well how does it work let me start by telling you what
work let me start by telling you what
work let me start by telling you what Watson is not it’s not how 9000 in 2001
Watson is not it’s not how 9000 in 2001
Watson is not it’s not how 9000 in 2001 Space Odyssey now I haven’t seen John
Space Odyssey now I haven’t seen John
Space Odyssey now I haven’t seen John Connor running around it’s not the
Connor running around it’s not the
Connor running around it’s not the beginning of the Skynet it’s not an
beginning of the Skynet it’s not an
beginning of the Skynet it’s not an advanced search engine what is Watson
bear with me here I’m going to get
bear with me here I’m going to get technical Watson is a cognitive system
technical Watson is a cognitive system
technical Watson is a cognitive system that uses natural language understanding
that uses natural language understanding
that uses natural language understanding and machine learning to draw insights
and machine learning to draw insights
and machine learning to draw insights what kind of insight business insights
what kind of insight business insights
what kind of insight business insights from large amounts of data and we call
from large amounts of data and we call
from large amounts of data and we call this data big data is divided into
this data big data is divided into
this data big data is divided into unstructured data think of your tweets
unstructured data think of your tweets
unstructured data think of your tweets your Facebook entries in structured data
your Facebook entries in structured data
your Facebook entries in structured data and how do we do this
and how do we do this
and how do we do this we’ll say that cognitive systems
understand reason and learn in what I
understand reason and learn in what I mean for understand is pretty much
mean for understand is pretty much
mean for understand is pretty much dealing with a human condition of
dealing with a human condition of
dealing with a human condition of language think about it
language think about it
language think about it we humans express through language we
we humans express through language we
we humans express through language we spread our ideas we talk to each other
spread our ideas we talk to each other
spread our ideas we talk to each other even in this moment there is a little
even in this moment there is a little
even in this moment there is a little voice in your head listening to what I’m
voice in your head listening to what I’m
voice in your head listening to what I’m saying and the understanding is trying
saying and the understanding is trying
saying and the understanding is trying to find these symbols the signals these
to find these symbols the signals these
to find these symbols the signals these patterns of meaning not talking about
patterns of meaning not talking about
patterns of meaning not talking about the language just spoken language like
the language just spoken language like
the language just spoken language like English or Spanish I’m talking about the
English or Spanish I’m talking about the
English or Spanish I’m talking about the language of images or text so
language of images or text so
language of images or text so understanding those natural languages
understanding those natural languages
understanding those natural languages then reason it because once I have the
then reason it because once I have the
then reason it because once I have the answer what do I do with it
answer what do I do with it
answer what do I do with it for instance if you remember in jeopardy
for instance if you remember in jeopardy
for instance if you remember in jeopardy we train the system with 200 million
we train the system with 200 million
we train the system with 200 million pages of content thus equivalent or
pages of content thus equivalent or
pages of content thus equivalent or having all the books in the Library of
having all the books in the Library of
having all the books in the Library of Congress and memory to answer these
Congress and memory to answer these
Congress and memory to answer these questions for instance what is the
questions for instance what is the
questions for instance what is the capital of Texas we go through the whole
capital of Texas we go through the whole
capital of Texas we go through the whole Wikipedia and we have multiple answers
Wikipedia and we have multiple answers
Wikipedia and we have multiple answers until we found the one that we think was
until we found the one that we think was
until we found the one that we think was a valid answer that is reasoning in the
a valid answer that is reasoning in the
a valid answer that is reasoning in the type of reasoning that we do it’s called
type of reasoning that we do it’s called
type of reasoning that we do it’s called inductive reasoning all these other
inductive reasoning all these other
inductive reasoning all these other players in the area use the same thing
players in the area use the same thing
players in the area use the same thing when you talk to your phone talk your
when you talk to your phone talk your
when you talk to your phone talk your assistant at home you’re using that type
assistant at home you’re using that type
assistant at home you’re using that type of reasoning and then cognitive systems
of reasoning and then cognitive systems
of reasoning and then cognitive systems learn
learn
learn if it was just matter of programming the
if it was just matter of programming the
if it was just matter of programming the rules of grammar that will be too easy
rules of grammar that will be too easy
rules of grammar that will be too easy we need to teach these systems we don’t
we need to teach these systems we don’t
we need to teach these systems we don’t program them and by teaching them we
program them and by teaching them we
program them and by teaching them we make them more intelligence another
make them more intelligence another
make them more intelligence another thing that I want to bring up today have
thing that I want to bring up today have
thing that I want to bring up today have been a lot of talk on the under media on
been a lot of talk on the under media on
been a lot of talk on the under media on the news about these systems this robots
the news about these systems this robots
the news about these systems this robots taking away jobs into me is more like a
taking away jobs into me is more like a
taking away jobs into me is more like a displacement think about when we have
displacement think about when we have
displacement think about when we have the car displacing the horse a lot of
the car displacing the horse a lot of
the car displacing the horse a lot of people lost their jobs but they went and
people lost their jobs but they went and
people lost their jobs but they went and create new jobs or the Industrial
create new jobs or the Industrial
create new jobs or the Industrial Revolution these cognitive systems are
Revolution these cognitive systems are
Revolution these cognitive systems are creating a partnership between humans
creating a partnership between humans
creating a partnership between humans and computers in this partnership is
and computers in this partnership is
and computers in this partnership is creating enhance and human expertise why
creating enhance and human expertise why
creating enhance and human expertise why because we humans are good at certain
because we humans are good at certain
because we humans are good at certain things we’re good at compassion
things we’re good at compassion
things we’re good at compassion abstraction even common sense like don’t
abstraction even common sense like don’t
abstraction even common sense like don’t drive into a white trailer you will die
drive into a white trailer you will die
drive into a white trailer you will die computers on the other hand are good at
computers on the other hand are good at
computers on the other hand are good at identifying patterns they do machine
identifying patterns they do machine
identifying patterns they do machine learning they isolate the answers so
learning they isolate the answers so
learning they isolate the answers so this one airship is what I my talk is
this one airship is what I my talk is
this one airship is what I my talk is all about for that I would like to give
all about for that I would like to give
all about for that I would like to give you some practical examples or some of
you some practical examples or some of
you some practical examples or some of the recent use cases that we have been
the recent use cases that we have been
the recent use cases that we have been working on and I’m going to start in the
working on and I’m going to start in the
working on and I’m going to start in the bottom right with what we call cognitive
bottom right with what we call cognitive
bottom right with what we call cognitive cooking we have an application called
cooking we have an application called
cooking we have an application called chip Watson that read a whole bunch of
chip Watson that read a whole bunch of
chip Watson that read a whole bunch of recipes in in the chemistry of the
recipes in in the chemistry of the
recipes in in the chemistry of the ingredients in those recipes and in
ingredients in those recipes and in
ingredients in those recipes and in conjunction with your appliances can
conjunction with your appliances can
conjunction with your appliances can find out what is in your refrigerator
find out what is in your refrigerator
find out what is in your refrigerator think about
think about
think about it’s Thursday nya have nothing to cook
it’s Thursday nya have nothing to cook
it’s Thursday nya have nothing to cook you talk to your refrigerator talk to
you talk to your refrigerator talk to
you talk to your refrigerator talk to the oven say what like what did I make
the oven say what like what did I make
the oven say what like what did I make for dinner this intelligent system will
for dinner this intelligent system will
for dinner this intelligent system will say well based on what you have you can
say well based on what you have you can
say well based on what you have you can make this that’s the power of cognitive
make this that’s the power of cognitive
make this that’s the power of cognitive going clockwise we have cognate ice
going clockwise we have cognate ice
going clockwise we have cognate ice connectors was a huge success last
connectors was a huge success last
connectors was a huge success last Christmas
Christmas
Christmas this is a toy that interact with little
this is a toy that interact with little
this is a toy that interact with little children and answer questions like why
children and answer questions like why
children and answer questions like why is the sky blue
is the sky blue
is the sky blue tell me our knock-knock joke and even
tell me our knock-knock joke and even
tell me our knock-knock joke and even where do babies come from cognitive
where do babies come from cognitive
where do babies come from cognitive recently we announced a partnership with
recently we announced a partnership with
recently we announced a partnership with a u.s. car manufacturer you remember
a u.s. car manufacturer you remember
a u.s. car manufacturer you remember that show from the 80s the Nightrider
that show from the 80s the Nightrider
that show from the 80s the Nightrider that you talk to your car we have that
that you talk to your car we have that
that you talk to your car we have that today so when you’re driving home after
today so when you’re driving home after
today so when you’re driving home after talking to chip Watson and you need an
talking to chip Watson and you need an
talking to chip Watson and you need an ingredient for your recipe you can tell
ingredient for your recipe you can tell
ingredient for your recipe you can tell us a car where’s the nearest grocery
us a car where’s the nearest grocery
us a car where’s the nearest grocery store we’re gonna put gas for my car you
store we’re gonna put gas for my car you
store we’re gonna put gas for my car you have that kind of dialogue natural
have that kind of dialogue natural
have that kind of dialogue natural language understanding but my last
language understanding but my last
language understanding but my last example something very close to me
example something very close to me
example something very close to me health care growing up in Latin America
health care growing up in Latin America
health care growing up in Latin America I notice how difficult it was to gain
I notice how difficult it was to gain
I notice how difficult it was to gain access to good health care only 5% of
access to good health care only 5% of
access to good health care only 5% of the people have access to good
the people have access to good
the people have access to good healthcare and with health care we tell
healthcare and with health care we tell
healthcare and with health care we tell usually our visitors on the lab that
usually our visitors on the lab that
usually our visitors on the lab that Watson doesn’t understand the science of
Watson doesn’t understand the science of
Watson doesn’t understand the science of medicine he understand the language of
medicine he understand the language of
medicine he understand the language of Medicine you cannot tell us what’s wrong
Medicine you cannot tell us what’s wrong
Medicine you cannot tell us what’s wrong with this person but it can tell us what
with this person but it can tell us what
with this person but it can tell us what are the multiple uses of certain drugs
are the multiple uses of certain drugs
are the multiple uses of certain drugs or two types of conditions we estimate
or two types of conditions we estimate
or two types of conditions we estimate that doctors are not keeping up in their
that doctors are not keeping up in their
that doctors are not keeping up in their fields there is so much data
fields there is so much data
fields there is so much data unstructured data been published every
unstructured data been published every
unstructured data been published every week that they don’t only spend like two
week that they don’t only spend like two
week that they don’t only spend like two hours a week reading what’s the latest
hours a week reading what’s the latest
hours a week reading what’s the latest on the field therefore they’re making
on the field therefore they’re making
on the field therefore they’re making decisions based on information that they
decisions based on information that they
decisions based on information that they learned 10 15 years ago perhaps not the
learned 10 15 years ago perhaps not the
learned 10 15 years ago perhaps not the most accurate to say people’s lives for
most accurate to say people’s lives for
most accurate to say people’s lives for instance recently I live in Chile and we
instance recently I live in Chile and we
instance recently I live in Chile and we held this patient this doctor trying to
held this patient this doctor trying to
held this patient this doctor trying to identify a disease for a sick child in
identify a disease for a sick child in
identify a disease for a sick child in the Antarctica the Patagonia this doctor
the Antarctica the Patagonia this doctor
the Antarctica the Patagonia this doctor use our technology to identify what was
use our technology to identify what was
use our technology to identify what was wrong with this child and was able to
wrong with this child and was able to
wrong with this child and was able to save this life and he told us there is
save this life and he told us there is
save this life and he told us there is nothing people will neither in the world
nothing people will neither in the world
nothing people will neither in the world to save a kid’s life and to me does the
to save a kid’s life and to me does the
to save a kid’s life and to me does the a partnership between humans and
a partnership between humans and
a partnership between humans and computer and that’s an idea worth
computer and that’s an idea worth
computer and that’s an idea worth spreading thank you
”
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