Importance of Natural Resources

Ginni Rometty keynote: CES 2016

ANNOUNCER: Ladies and gentlemen,
please welcome the president and CEO of the Consumer Technology
Association, Gary Shapiro. [ MUSIC, APPLAUSE ] SHAPIRO: Welcome to CES 2016. I am so excited to be on this stage this
afternoon to introduce our keynote speaker. You know, for nearly half a century, CES has
been mostly about cutting-edge consumer products and during most of its more
than 100-year history, IBM has been the preeminent leader
in the business to business IT. But that’s changing for both of us, and I am thrilled that we have
IBM’s CEO Ginni Rometty here with us today to talk about this new paradigm. In fact, the massive convergence going on around
the world, thanks to Big Data and the Internet of Things, is driving two distinct trends. First, CES is no longer totally
consumer product centric. It’s increasingly about technologies
driven by the Internet of Things; and IBM is today leveraging its advantages
with data and the Internet of Things to enter spaces it has never
even been in before, appealing to totally new audiences as a result. As Ginni has said many times, data
is humankind’s next natural resource, and she’s leading a major transformation at
big blue to become “the” preeminent company in what it calls the new cognitive era,
driven by systems that actually learn. During her tenure — which began almost
four years ago to this very day — she has made the cognitive power of one of IBM’s most iconic technologies the
centerpiece of that transformation: Watson. The same system, which beat the two
top human contestants on Jeopardy! in 2011 has been featured in ads with
such top icons as Bob Dylan, in fact, it’s now at the center of what may
be big blue’s biggest bet ever. In fact, the same company’s
technology helped land man on the moon just a generation ago has
its own new moon shot today with Watson: transforming healthcare and
education as we know it. And they’re not stopping there. In fact, last May, Ginni made
headlines with a really bold prediction. She told an audience of IBM customers in
New York that included engineers, doctors, bankers and other professionals
that, quote, in the future, every decision that mankind makes is going to
be informed by a cognitive system like Watson, and our lives will be better for it. Well, with the coming cognitive era, I am thrilled to announce an
important research partnership between the Consumer Technology
Association Foundation and IBM. The research will focus on identifying how
cognitive computing will transform our lives as we age and also transform the lives
of those living with disabilities. IBM’s generous contribution of funding and
resources will lead to important research into the impact of technologies like Watson. It’s still the early days, and major transformations are
extremely difficult to pull off. But as Ginni is fond of saying, there’s
a reason why IBM is 105 years old. It’s because the company has a
long history of making big bets in the future and of being proven right. We will hear from Ginni about IBM’s bold and
optimistic vision for the coming new era powered by Watson and cognitive business. We’ll also see a few demonstrations
of how it’s being used today and hear from some IBM customers discussing
cognitive, IoT and other key topics. Ladies and gentlemen, please join
me in welcoming our keynote speaker, IBM’s CEO, Chairman, Ginni Rometty. [ MUSIC, APPLAUSE ] ROMETTY: Thank you. You did a great job. Well, thank you. That was a very generous introduction, and I
thought Gary was going to give my presentation. I thought he was doing a great job, actually. He did a great job except for one thing. Did I hear him properly say
that I was with IBM 40 years? Did I hear that? That…look at me. Does that sound true? I hope not. Not true. If you’re thinking yes, no. And so, look, it is great to see so many
people here and so many IBM clients. And I don’t think Gary mentioned
this: I am the first IBM CEO to ever speak at a keynote here at CES. And so, you might be asking… [ CHEERS, APPLAUSE ] Well, if you clap at that,
you will clap at anything. Okay? So, I am the first, and you
might be asking why and why now. Now, I have walked around, looked around,
clearly, IoT is a major theme here. It impacts every industry, every company. And I am here, IBM is here, because
I want to assert something to you: that the future of the Internet of
Things is cognitive, the cognitive IoT. And I am going to be joined by CEOs from three
major companies, all different industries, and we’re going to make some
major announcements here today that embody this exact future
I’m going to talk about. So, let me frame what you’re going to
then see come to life through their eyes. So, I want to talk about
cognitive; what is a cognitive IoT? And then really quickly, what I think
are three critical success factors because it’s what so many of you are doing. But first I want to start with a question. Now, there’s no doubt that the Internet
of Things is all part of the phenomena of digitization of products,
of services, of companies. So, if I ask you to raise your hands and ask how
many of you either work for a digital company or you are trying to become a digital
company, just raise your hand. Okay. Same response about anywhere in the
world is almost everyone’s hand goes up. So, it doesn’t matter if you’re B to B, B
to C, public/private, it doesn’t matter. And this has got a lot to
do, as we reinvent ourselves, what we’ve done to build a
good number of capabilities to help you become a digital company. It started with building the leading and the
largest set of big data and analytics capability in the world, building a cloud platform for
the enterprise that goes between public, private and hybrid; and then, our work to
help you re-imagine how work is done itself and that’s been through the
partnership with Apple; and then having built the world’s
largest private security company. I think many people don’t realize that even by
the end of 2014, those businesses for IBM were over $25 billion; and through the third
quarter of this year, they’ve grown 30 percent. So, this idea that analytics, cloud,
mobility, security, they are all important. But I want to ask you a question. When everybody becomes digital, then what? Who wins? I like to say digital is not a
destination; it’s a foundation. I mean, I just looked around
this whole conference — wearables, sensors, cars, data everywhere. But what will differentiate you is
understanding that data, and that brings me to my first point that Gary also introduced. I believe the most disruptive, transformative
trend is now in front of us, and it’s cognitive. This ability to think, to learn, to understand
the systems, the products, the processes, everything you do, and it is the
dawn of a new era, the cognitive era. Maybe you could simply say digital
business plus digital intelligence. And cognitive is an era of business,
and it is an era of technology. So, there’s two drivers for
the technology era: one, data that was invisible will
now be visible to you. Now, you know, we’ve talked about the phenomena
of big data forever, but 80 percent of the data out there, while it may be stored
in some systems, it’s black. It’s invisible, it’s not understood. Sight, sound, music — you know, you don’t
actually know inside of it what it is, and that’s what’s changing in this new era. The second thing is the advent
of cognitive computing. Now, some people want to shorthand that to
artificial intelligence; that’s part of it, but you have to be able to
work in natural language and in a domain: understand
medicine, metallurgy. And then more than anything, this is
an era of systems you do not program; they understand, they reason and they learn. In fact, they therefore have
hypotheses and confidence levels — and this is what IBM Watson does. Now, we worked on this, it started a decade
ago, and we went ahead and debuted Watson to Jeopardy!, the game show, in 2011. It has come a long way since then. At that time, what Watson could do was question
and answer, which he did beat everyone then. Question and answer, and he had
five technologies underneath it. Fast forward to today. There are now 32 different functions
he does, 50 different technologies under it all available via an API so you
can pull them into a business and a process. And we’re expanding Watson’s senses,
giving it things like sight; and in fact, the first way he’s learning sight
is on reading medical images. And then we made a strategic decision to open up
Watson as a cloud platform, a whole set of APIs so you would build businesses,
companies, processes, products, pulling cognitive into them. So, today Watson’s in 36 countries, 80,000
programmers, 500 people building businesses. And it’s healthcare, retail, education, travel. And it is a profound new capability. Just think of the ability to build
thinking into anything that you do. I believe it will change not only what you make,
it will change how you operate; and in fact, it will actually change who you are. So, let me then to my second point. That’s cognitive. What about the cognitive IoT? So, imagine, take cognition
and infuse it into an IoT. And remember, remember this point. The challenge isn’t capturing and storing all
the data I have seen out in all these hallways. Eighty percent of that data is dark. Nine billion connected devices,
2.5 katrillion bytes of data a day. The challenge is understanding it. So, let me give you a couple examples
of clients and what they’ve accomplished so far, from the tiny to the large. So, start with a little startup
called Cognitoys. They make a dinosaur to talk to your child,
and it adapts the personality to work with your child: what jokes,
what books, how they learn. It adapts to your child’s personality. That’s a learning system. On the other end of the spectrum,
Airbus makes aircraft. You won’t be surprised that there’s
six million sensors in an airplane and that they’re from 3,000 suppliers. Well, cognitive IoT, we’re about to
start processing a half a billion bytes from every flight taken so that we
can predict wear and tear over time, predict the time to failure,
maintenance far in advance. And then, actually over time
improve the way parts are made. They’re also now working on the
cognitive cockpit, natural language, the pilot to interface particularly
in times of crisis. Then I jump to a different consumer
application with a partner called [Finn Air]. I’m originally from Detroit. Detroit Pistons, Auburn Hills, the big, the
Palace where they play, that’s basketball, 100 beacons, Watson is real time
analyzing the sentiment of the fans, matching that with what’s happening on the floor
in the game, real time offers actually related to what just happened to any player
going to any individual, custom. Another way, you could imagine you would
engage and do this with any kind of place where consumers aggregate together. Or, Whirlpool. In fact, if you went to the
briefing center here, you’d see it. Real-time appli– …real-time devices,
obviously, what Whirlpool makes, data connected, the connected appliance, plus Watson IoT cloud and you have a cognitive
oven, stove, whatever it is. So, if you go down there, you’ll see
a Jenn-Air connected to Chef Watson, and you’ll see how they work
together, learning the preferences, the needs of a family and
making recommendations. That’s the world I see in front of us. Now, what do you need to do that? I will end with three critical success factors. You need the right platform. You’re going to need new forms of data — not
just more — and analytics and an ecosystem. When I say “the right platform,” you know,
Internet of Things, you all know this. It’s about real-time data. But what most people can’t do is as a result
of the insights take immediate action. You need a platform to do that. We’ve built out a cloud platform in 41
countries, a platform called Bluemix for those of you that build the applications. The largest cloud foundry deployment
in the world, 120 services. Then the services and software for a hybrid
world to connect to your existing businesses, and then Watson APIs that allow you
to put cognition in everything you do. Second thing, you’re going to
need new forms of data, new forms. I just said there’s so much. But what I mean by new is we’re committed
to help you, and part of that is by building out a huge capability on data and analytics. We are approaching $30 billion of investment
in having built analytics capabilities, including 30 acquisitions, 15,000
experts, hundreds of mathematicians. But we also need to bring you data
that you don’t possess but you need. How do you make sense of some
pretty big amounts of social data? It needs to be curated, Twitter, Facebook. Or, the weather. Everybody in here working on Internet of Things, the weather is the most pervasive
impacting source of data there is. And you may or may not be aware, it’s why
the IBM Company acquired The Weather Company. Now, those of you, everybody’s got a weather
app, and probably theirs is on your phone. When you hit it, you might just think it’s
going to one of the government weather agencies. Well, not true. It’s a very sophisticated real-time platform. Three billion weather reference points a day
are collected, sophisticated in analytics, and anywhere from 36 to 30 billion
transactions a day go against that. Now, we’re going to combine weather
with all your operational data. And then next up, since that platform can
go way beyond weather, telematics, sensors, and you can start to see what
you could do for insurance risk, for retail demand, for auto safety. In many ways, The Weather Company, it’s
an IoT company, and weather just happened to be one of the first use cases it had. There’s a second then kind of data
that I think you’re going to need, and some of you started, but not everyone. It’s the huge flood of video that will matter in
this world of Internet of Things and cognitive. Now, streaming is growing exponentially. If you look at all the data
in the world a different way, 80 percent of it is going to end up being video. If you’re in entertainment,
media, you understand that. But it will now transform every
industry, it won’t matter. Right? How many of us, you don’t have to turn on the
news to think about a police car with a cam or a policeman with a lapel camera. Those of you in retail, I think you
know that, if someone sees a video, they’re two times more likely to buy. So, we’ve added video services
to all of our Internet of Things cloud, over the top video services. You’re probably surprised, but we do that
already today for Wimbledon, for the Masters, for NFL, for HBO, for Sony Movie
Channel, for Time Warner, for Verizon. Anyone can serve up the right video at the right
moment, and we are just starting on being able to prepare for you a lot of this dark data
that you need but you don’t have to own. So, two critical success
factors: the first, the platform; the second, new forms of data and analytics. And then the third is an ecosystem. And that brings me to the most exciting
part of, I hope, this afternoon together. Now, we’re very committed to build these out by
industry and by domain, and we’re well underway. Watson Health, we announced back in April with
many partners: Johnson & Johnson, Medtronic, CVS, Epic, Boston Children’s
Hospital, Memorial Sloan-Kettering, the cancer center, Apple Research Kit. We’ve done a number of acquisitions. But last month we also announced
our Watson IoT business. Now, we’ve been working in IoT for quite
a long time already, 4,000 clients, seven of the 10 largest auto companies,
eight of 10 largest oil and gas, and 11 of 12 aerospace and defense. But now this is about bringing
cognition into IoT. Back to where I started, I really believe
this will insert any IoT that’s going to differentiate you in the
future will have to be cognitive. And we opened up this unit, we headquartered
it in Germany, headquartered in Munich, a thousand people are there but there
are eight centers around the world. We have the Watson IoT set of
analytics, Watson IoT cloud platform, and then a whole, whole ecosystem of partners. And that’s what I want to now show you, is
the partners we’ve brought today; and in fact, the announcements we’ll be
making, because the Watson Internet of Things is not a future it is here today. And I have got three great announcements
here and the leaders of their companies to join me to show you some of this. So, let me now, with great pleasure, give
you a little introduction to my first guest. Many of you know him. Kevin Plank. He is the founder, CEO of Under Armour. He is certainly one of this nation’s, if not
the world’s, most successful entrepreneurs. As you know, Under Armour already
at $4 billion, 14,000 employees. And Kevin, he will tell you, he’ll tell
you himself, his mission is simple: to make all athletes better, through
passion, design; and of course, relentless pursuit of innovation. I have gotten to know Kevin. You will find he is just getting started. And we are announcing here
today our partnership, and you’re going to see the beginning
of the app that’s rolling out now to transform personal health and fitness. Kevin coined the word “connected fitness.” UA Record is their dashboard. It will be powered by Watson. Think of this as the Internet of athletes. So let me ask you to welcome
Kevin Plank to the stage with me. Kevin? [ MUSIC, APPLAUSE ] PLANK: Thank you so much. ROMETTY: The world’s most
successful entrepreneur. PLANK: [ LAUGHTER ] That’s a big claim, but thank you
very much for having us, Ginni. ROMETTY: My pleasure. Look, so Kevin and I are
going to do a little Q&A, and then he’s going to do a bit of a demo here. PLANK: Yes. ROMETTY: So, for those of you that
don’t know, Under Armour formed in 1988. It is an amazing story. Right? So, let me have you just tell the group here
a little bit about the Under Armour of today. PLANK: Well, thank you, first of all, for
allowing myself here to be able to tell the Under Armour story with the
positioning of IBM Watson — what that is going to be able to do a) for
our company and also being able to give back, help enrich lives for our consumers. So, at Under Armour, we’re
entering our 20th year in business. As we started, and we began in 1996. I was a football player in college that didn’t like the way my cotton T-shirt
felt beneath my equipment and wondered why no one ever made a better
alternative to a short sleeved cotton T-shirt in the summer or a long sleeved
cotton T-shirt in the winter. And that’s gone from taking us from
a company that’s changed the way that athletes dress including some
that I’ve seen here in the convention. They say, hey, are you the Under Armour guy? And I get grown men pulling their
underwear out of their pants at me. [ LAUGHTER ] ROMETTY: I don’t get that when I meet… PLANK: Not yet, no. [ LAUGHTER ] We didn’t rehearse that one, Ginni. It’s truly changing the way that athletes live. You know, we’re coming here today with
an ecosystem that has today counting more than 160 million people amongst our
connected four apps that we have. And the question that we want to answer
and why IBM Watson can be such a difference for our brand is that why
is it that we know more about our own cars than we
do about our own bodies? Think about it. We get into our cars. We know how much gas, we know how much
oil, we know how much tire pressure. We can run diagnostics from Detroit. But when you ask us about our own health or
I say, how many days were you sick last year, most of us just say, I don’t know, not so many. If you asked me, I’d say, I don’t know, I get
sick every time it goes from summer into fall, every time it goes from winter back
into the spring, I catch a cold. But imagine if we actually had data — data that could help us make
that decision and make it better. So, when you think about that, imagine what
that could mean for you as you look at life, and that’s where we basically began to create
this ecosystem that we call connected fitness that began just about two years ago. ROMETTY: So, connected fitness,
and I would recommend to anyone in the audience a Wired magazine
article came out about two days ago, I don’t know if…I hope you read it,
it’s a great article about Under Armour. And really Kevin kind of coined, I
think, this phrase “connected fitness.” And in fact, you’re the original wearables
in many ways, traditional and now new. PLANK: True. ROMETTY: So, talk a little
bit about connected fitness. PLANK: So, more than two years ago, we
looked at our company and today, 14,000; a little more than 8,000
just a couple years ago. And you look at the size and
scale we had, and we looked and said we didn’t have enough
really smart people. We didn’t have enough engineers working in our
business, attracting them to sporting goods. And so, the goal we had is that while
we recognized the future was going to be in what we called wearables and digital, and
what was our play on digital and we decided that getting into hardware wasn’t
exactly what we wanted to do, and our bet was going to be on community. We made our first acquisition with
a company called Map My Fitness or Map My Run, Map My Ride. ROMETTY: How many people use those things? Anybody? Look at that, tons of hands already. PLANK: So, you’ll see hands going up. There were 20 million registered users
when we bought the company December of ’13, and in just 12 months, it grew over
50 percent to 32 million users. And so, when you look at what
that meant and the size and scale, we then decided that we weren’t
asking the right answer, is that we didn’t have the
right question to ask. And so, we decided that in betting on
community, agnostic was very important and open platform was very important to us. So, we decided to double down on
what we had with Map My Fitness. We bought two more companies:
one called EndoMondo, which is a GPS tracking application
just like Map My Run or Map My Ride; and the third was a company called My
Fitness Pal based out of San Francisco, led by a guy named Mike Lee
and his brother Albert. And this was the nutrition site, it
was really the third leg of the stool. And we thought that if we could contain this
amount of data and put it in the one place and be able to truly empower the consumer
with information that would give them, allow them to enrich and able
their lives, it would be powerful. Scale is incredibly important here. In just the last two days alone, we’ve
had more than 350,000 people download one of our four apps that we have today. So, incredibly proud, proud story of
what we have and where we’re heading now. ROMETTY: So, now they also made — and Kevin made an announcement yesterday
— something called the Health Box. So, add on now. So, start with the concept of
community and now the Health Box. PLANK: Well, we were definitely playing chess
and not checkers when we got into this game. And so, what that meant is
that our play was on the King of how can we truly enrich
lives in our community? So, now, again, counting more than 160 million
people, Health Box is meant to be a system because wearables to date have never really
given you true information about yourself. Sure, they’ll tell you how many steps you
took or it will tell you how long you slept. But allowing me or empowering me to make
proactive decisions about my life or my health and fitness is something that
we believed needed a system. And the system comes in three parts. The first part is the wearable device
that you have, and Ginni has one as well. It will track how much you
sleep, it will track your steps. It will also do a number of other things in checking resting heart
rate and several other pieces. It has [accelerometry] in it. The second devices is the heart rate strap. It decides when you’re going to exercise,
it will tell you how hard you exercised, how many calories that you burned. And the third is the scale. And the idea of this is being able to
track your weight on a daily basis. And if we can give you this
frictionless devices, including the band which has a seven day battery life and
charges in less than an hour, you know, it’s something we believe it create
a true picture of the consumer. It’s something that we have called
the record platform that we hope to eventually merge our consumers into
and say, if I know how much I slept, if I know how many steps I took, if I know what
I weigh, if I know how much I ate and what I put in my body, imagine what we can do to
articulate a true definition for the consumer that can make them actually feel better. ROMETTY: So, this takes us to
the first, it’s actually going to be a very I think exciting run together
here, but the first announcement, which is, obviously, UA Records powered by Watson. And so, you’ll see the very first thing,
so why don’t you talk a little bit about, and you’re actually going to show some of
the very first insights Watson offers here. PLANK: So, the exciting thing
about this is what it can really do. Again, there’s three components that go into
what makes…or, four components that really, the four quadrants, as we call it, on the
app: sleep, activity, fitness and nutrition. There’s two other components that we
added to that, as I said earlier, weight; and the last component is this
thing called how do you feel? So, imagine if you could capture all this data
in just one place and have one daily dashboard for health because you think about it
and go, I know more about, again, my car. I know more about my portfolio
or my stock or my bank balance than I do about my own health and fitness. And it’s a subjective answer. So, if we can only take something from, a)
taking those four quadrants, adding weight, and then this last feature that we call “how do
you feel,” being able to rate yourself on a one to 10 scale on a daily basis
that just says, how do you feel? If I feel great, I feel like a 10; if I
don’t feel so good, I feel like a one. And be able to take that insight
and take that information and say, imagine if I could look then and I can truly
take myself and allow myself to be able to make proactive decisions about the
days that I rated myself a nine or a 10. Because you look and you
think, what does that mean? Because there’s three ways that we hope that
people will be able to compare themselves. You can compete if you’d like, but
hopefully you’re going to compare yourself against number one, comparing against myself. If I have this data of the wheel, as we call
it, and be able to look at it on a monthly basis and say last month that my data, my
information, it basically looked like this, and there were three days where I rated
myself a nine or a 10, what’s the activity that I did leading up that allowed
me to rate myself at nine or 10? Well, I slept at least seven hours. Well, I definitely exercised in the morning. I ate no more in the My Fitness Pal protocol of
either registering whether you had a heavy day of eating, an average day of
eating, or a light day of eating. So, I had no more than an average day of eating. And then third, the third quality that we
have is the ability to take this information and to truly be able to do something with it. The second component is the nature
of competing with your friends. So, I know how I competed against myself
last…yesterday, last week, last month. But how do I compare against my friends,
others like me, whether it’s my friends from high school, my friends
from work, my family. And the third component is this
feature where we brought in IBM Watson. And this is the feature that tells us about what
it means to find people that are just like me. So, just like me imagines that in my data
set, of the 160 million people that we have on our platform today, I have an ecosystem
of roughly between 40 to 45 year old males, there’s 4.6 million males just like me. And of those 4.6 million males, the
average weight of them is 192.4 pounds. The average run for those that decide to
go and exercise that use jogging or running for their exercise, they run at least 4.1 miles. Their average sleep is 6 hours and 38 minutes. Their average calories consumed on
a daily basis is 2,174 calories. And imagine if I know that if I eat less
than 2,000 calories and I have a weight goal of losing 10 pounds in some period of time,
I can start dialing in the things that I need to do, the decisions that I need to make in
order to make proactive decisions to improve and ultimately to enrich my life. In the future, we dream and
we think about insights, the way that Watson will be able to empower us. And there’s things like whether it’s an example
from the American Cancer Society study that says that spending an excessive amount
of time sitting at least six hours or more during the day decreases a
person’s life expectancy regardless of whether they exercise or not. This is an insight that Watson will
give you, kind of…it’s pretty scary at some level but it’s also empowering. It allows you to make decisions
to improve your life. In the future, it will deliver a personalized
call to action based on your activity. For instance, if my ideal sleep time is seven
hours and I only slept five and I was planning on going for a run because I
always go for runs on Thursdays, it may recommend that I maybe just take a class,
do the elliptical, perhaps do a yoga class or something a little less
stressful or a little less tense. That’s the type of information that we
believe we have, I think, to bring to bear. So, when Watson is taking the programming of
160 million people just like me and be able to deliver that back in a proactive
way for me and for Under Armour, and frankly for all consumers
all over the globe. And again, simplicity is at the key of whether
it’s Health Box or whether it’s the data and the information you get,
or whether it’s the simplicity of just looking at that basic wheel every day. ROMETTY: So, the first capabilities
you’ll see with Watson are Just Like Me, and then goes on from there
to the Cognitive Coaching. You want to talk one minute about Cognitive
Coaching, and we’ll wrap up on that. PLANK: So, we believe the
future we have in the world is like how will coaching truly be able to help me? And that is where you’re using things and saying
like, to be my coach, again, within my data set of the 4.6 million males just like me, how can I
really lean on Watson being able to triangulate in a workout plan or a program for me? You know, things that it will be able
to give me the data on a daily basis. Again, in a very subtle way. It’s not marketing to you,
it’s not advertising to you. It’s just simply giving you
information where it doesn’t have to be a personal trainer that costs $80 an hour. It could actually be a Watson system that
will personalize something just for me, finding others that are just
like me who want to get better. ROMETTY: So, I think, Kevin, together, I
think we both believe we will change lives. And at the same time, I think one of
Kevin’s famous sayings he always says to his own team is, but at the same time, we’re going to still sell shirts
and T-shirts and sneakers. PLANK: Yes. ROMETTY: Right? So, at the same time. PLANK: It’s a very simple process. It’s like, we’re going to do a lot of
cool stuff, but at the end of the day, the one thing we know, the more
people exercise and work out, the more shirts and shoes they’re going to buy. So there’s a very…there’s a
logic to all of this, believe me. So, we encourage you all to know
how much you’re working out, know how much you’re sleeping,
know how much you’re exercising. And then again, don’t forget
to buy shirts and shoes. ROMETTY: You got it. PLANK: Thank you so much, Ginni. Wonderful. [ APPLAUSE ] ROMETTY: So, you can see why we’re so excited. And again, you’re able to use Watson
already in the app first round, and he is just like any learning
system, going to continue to get better. So, kind of keeping in that same theme, my
next guest and my next partner to introduce to you is Omar Ishrak, who is
the Chair and CEO of Medtronic. A global healthcare company around the
world, many of you I I’m sure know them, because they’re a leading global
healthcare medical technology company. So, almost $30 billion in revenue,
85,000 employees, 160 countries. And actually, a company like
Medtronic, if you’ve got any illness in your family, you might know of them. They’ve been in Internet of Things
truly before the word was ever there. Now, those of you that know Omar know he
is very committed to access to healthcare, quality of healthcare and outcomes. And what we announced with Medtronic, we announced a partnership
that started just in April. But Omar and I are here together today to tell
you we’ve reached a very important milestone: our first partnership together
is in diabetes management. And so, with Watson, the
breakthrough we’ve had is the ability to predict a hypoglycemic incident,
event, up to three hours in advance. Now, those of you that if you’re
not familiar with the disease, there is no prediction of it, none. So, up to three hours in advance is what
prevents dangerous health events from happening because you can do something about it. So, we can’t be happier about this. You’re going to see that this
app rolls out this summer. And I want to welcome Omar, and we’re going to
talk all about the future of your health here. So, Omar? [ MUSIC, APPLAUSE ] ISHRAK: Ginni, thanks. ROMETTY: Good to see you. Now, like I said, improving lives
is what this business is all about. And I got the chance, I was
telling Omar over the holiday, I have a friend who got one
of Medtronic’s devices. And I said, I listened to an hour of her
telling me what a great company Medtronic is and their service and their
attention in what they do. It speaks to the value. So, for those of you that
don’t know this company, I want Omar to tell you just a little bit
about Medtronic before we get into diabetes. ISHRAK: Oh, thank you. Thank you very much, Ginni, for allowing
me to be here to share the stage with you and for starting us off with
that very nice story. Now, Medtronic, as Ginni mentioned,
is a medical technology company, but our main company can be
encapsulated by our mission. Our mission is that we are a biomedical
engineering company who are focused on alleviating pain, restoring
health or extending life — which in other words means that
we’re a technology company determined to change outcomes in healthcare. We cover many disease states. Cardiac and vascular is a big one for us,
neurological diseases, respiratory conditions, diabetes as Ginni just mentioned, and
also we’re present in different ways through which we can help the outcome
of patients who have conditions and are in the ICU — in the Intensive
Care Unit — or in operating rooms. So, that’s like Medtronic in a nutshell for you. ROMETTY: So, this spring, as I mentioned,
we started our partnership together. And unless you’re very familiar with diabetes,
I think some of the statistics are interesting about what a challenge it presents
to the world and to our society. ISHRAK: Indeed. You know, diabetes, first, it’s a big disease. Over 400 million people in the world
have diabetes, and that is something like one in 11 people around the world. Second, it’s costly. I mean, it costs a lot of money for
the healthcare systems around the world because patients have to be treated and then
monitored continuously to keep them alive. And some of them have catastrophic conditions which require emergency room visit
that are even more expensive. So, it costs something like
$600 billion a year globally. That’s the spend from healthcare
systems around the world. So, it’s a very, you know, big disease that
affects a lot of people, costs a lot of money. But at the same time, it’s a disease where
self-management can both be a blessing — in other words, by self managing you can stay
well and lead more or less a normal life — or it can be really damaging in that you go to the emergency room every three
months and have risk of death. And worse still, even if you get through
that, you may have long-term complications like amputation or blindness or cardiac disease. So, it’s an area which if
we can make a difference in, we’ll have a big impact in healthcare. ROMETTY: So, maybe share
with everyone, because again, it’s the number six most
deadly disease here in America. So, talk about what happens today and
how cognitive and Watson can help, because maybe describe what happens today. I think everyone imagines that, no, this
is already monitored, and you can tell. It’s not true. ISHRAK: No, it’s not true because most of
the diabetes patients, in fact, have medication or deliver insulin by themselves. In some instances, they have pumps. And they’re categorized into different
stages of intensiveness, the disease. But in almost all of these cases,
the amount of time they interface with the healthcare system
actually is very limited. It happens maybe once every three or four
months, maybe a little shorter than that. And usually the visit with the doctor
is a 10-minute visit, are you okay, and look at some very coarse, average data. And from that, you’re done. But you know, like I just described, diabetes is
a disease that requires continuous management. It changes by the minute depending on the stress
level of the person, what the person’s eating, what activity the person’s had, what kind of
medication the person’s given himself or not. All of that, in any instance,
determines a certain condition. And looking at that person for 10 minutes every
three months and looking at average data — while I don’t want to trivialize that because
that is the way in which we do things today — is nowhere near where it can
be and where it should be. And the Internet of Things, by being
able to capture data and help manage that patient’s life, can
make a dramatic difference. ROMETTY: So, I’m going to ask Omar
to now actually show you a demo. This is going to be out this summer. And again, back to the big differentiation. It’s one thing to capture all this data; it
is another thing to do predictions with it and learning — learning about
the individual, the cohort. And you will see, as I said,
the ability to predict an onset, a hypoglycemic event, three hours in advance. ISHRAK: Yes. So, it’s my pleasure actually
to describe this app for you, which is essentially a Medtronic app. But as I’ll describe in a few
minutes, Watson really takes it to a different league of performance. So, this is a screen, a screenshot
potentially of a person with diabetes. Now, I’ll talk about a fictional
person, let’s name him William. And in the screen it shows that
William has burnt something like 1,500 calories for that day. And you know, a lot of this can happen
because it’s just a metabolic rate. It can probably burn 1,000 calories or
something by midday for different people, and then he might have done some
exercise, and he’s gone up to 1,500. It could be something else for others. It also shows that William’s glucose
level at that instance actually is 140, and I’ll come back to that in a minute. But at that instance, that’s what it is. And it also shows that is amount of
food that he’s eaten has resulted in carbohydrate intake of 14 grams. So, this is probably being entered manually. So, that’s like a dashboard, if you
like, an instantaneous dashboard of William’s physical condition
at a point in time. Now, let’s talk about the glucose
number because that’s most interesting and least understood in many ways. Now, the glucose number for 140, this is really
the instantaneous number, but as you can see, there’s a graph there, which shows a
trend, which means that we have integrated into this app data from a continuous
glucose monitor that we make. Typically, and many of you may know this, the way in which you measure glucose
is that you do a finger prick test. You get a little blood from
your finger, put it in a meter and you get a reading at one point in time. And at most, people will do this maybe
at most three or four times a day, sometimes once a day, sometimes
even less than that. This is a continuous monitor,
so it shows the glucose status of that person at every point in time. And so from that, you can get real
trends, not just different kind of sample points over a day or so. And so that’s very important
data, and it’s used together with the others to make a bigger difference. Now, let’s say William is sitting
with his wife Anna in a restaurant, and they are preparing to have a meal. So William looks at his dashboard
and says, well, if I’m going to eat something,
what’s that going to do to me? So, he decides, I’m going to order a
certain type of food, and the app now comes out with a prediction saying that, look, if
you eat this — and in this case, it’s pasta, a pasta salad, it knows what the carbohydrate
content is, what the fat content is. And from that, it predicts, look, if
you do this, it’s going to do this to your total carbohydrate budget for that day, and it gives that useful
information for William. Now, it could be that this is enough, that
William knows this, is sort of familiar with his condition, and he’s fine. He eats it, and he goes along. But you know what I just described to
you, all that’s in the dashboard and it’s in the app is something that requires William to
really kind of think about stuff, think about, you know, I just…I’m having a meal. I’ve got so many calories. I’ve already had so much carbohydrate. My sugar level is 140. I’m probably going to be okay. He may be right; he may be wrong — because he’s
just using his mind now very intuitively based on his own personal experience,
as to what something will do. Now, that is not going to be even close
to what something like Watson can do. So, Watson comes in now, and we insert Watson
into the equation, and then Watson does a check, if you like, as to, is this okay or not? In this particular example, in the app that
we’re launching, we’ve got Watson coming in and saying that, again, in
this fictional example, look, while you may think it’s okay, it really isn’t. And an advisory alert actually goes
out in this situation and says that, watch out, there’s something wrong here. At this point in time, you’d better look. So, there’s an advisory note. So, William clicks on that. An advisory note comes out
and says that well, watch out. Based on your own history, based on data and
not on your intuition anymore, based on data, you know, you’ve done so much exercise, and
recently you’ve had so many carbs and so on. So, based on that, you’re actually going
to get a hypoglycemic event in three hours. Now, hypoglycemic means your sugar level gets
so low that you essentially cannot function. If taken to an extreme, you get a
seizure, you get a coma and then you die. Literally, that’s how it is. And some people, this can happen
when they’re nowhere near a hospital. Now, if you get to a medical place, they can
probably rescue you, but it’s not a good thing. And so William sees this, and he sees a
trend that says, look, in three hours, I’m going to get a hypoglycemic event. And as Ginni pointed out,
the state of the art today is that the only warning you
get is you don’t feel well. Now, you may not feel well for a
whole bunch of different things. It could be this, or it couldn’t be. And you know, it’s a flip of a coin if you
decide that it’s really serious or not. But through Watson and through this, a
three-hour prediction is plenty of time. Nothing’s happened. William’s glucose at that instant is within
the safe zone, that gray area of the safe zone. William’s fine, and he can now take
action, saying, look, I really, the pasta that I ordered, that’s probably
not enough because if that’s all I have based on what I’ve done so far already, I’m
going to get a hypoglycemic event. So, I’d better eat something else. And I’m going to eat a little
apple or something like that, and William knows best, and he does that. And he does that, and actually
then what happens is that a hypoglycemic event
does not happen at all. And so the trend shows that…the app then
shows that, yes, the glucose level goes up a little bit because of the eating, but
it doesn’t go down to a dangerous level and then settles down again over time. So, I hope what you can see here, that Watson
makes a fundamental difference not only to the quality of life of William
but potentially saved his life. And if this is rolled out over millions
of people, you can see what it will do to extending life, in many ways, restoring
health, alleviating lots of the pain. That’s what our mission is all about. And not only that, think of the
amount of efficiency it will create in the healthcare system, wasted
money in emergency room visits and all of that can be curtailed by something
as seemingly simple but really very important, and we feel a big breakthrough for this year. ROMETTY: It is a breakthrough. So, we felt very good about bringing
it here today to show it to you. And as Omar said, by summer, those of you,
like I said, any of you that know someone or one of your loved ones that has
diabetes, this makes a difference. There’s no other way to tell. So, we feel great about it. The future, as you said, is not only
about value, other diseases and the like. Maybe a last comment on that? ISHRAK: Yes. Well, you know, before I go to other diseases, this is still a starting
point for even in diabetes. In the future, we just heard the story
from Under Armour, and there are lots of parallels, as I hope you can see. In this area, data is used
in a very specific condition. We could use activity data. We could use other kinds of wearable data
that will complement the glucose data and the other data that we have here
and make this algorithm a lot smarter. We can also through Watson start look at
other people like William and use that data to give even more precise recommendations. And through that, make this management of
diabetes something that becomes a thing that patients don’t notice that
you’ve got diabetes anymore. That’s truly our goal, and that
would be a real cure for the disease, and we have every expectation
that over time we will get there. ROMETTY: You got it. So, I know together, and
really, Omar, I thank you, there’s no doubt in our minds we will
change the face of healthcare together. ISHRAK: Thank you. ROMETTY: So, thank you. ISHRAK: Thank you, Ginni. [ APPLAUSE ] ROMETTY: Now, so you saw a theme,
wearables — real wearables — and wellness, we talked about
how to manage illness. And now I want to bring IoT
together to one more level. I want to talk about robots, and
my next guest is from SoftBank. Those of you that don’t know
SoftBank, a $70 billion company. They are the fastest growing company in Japan for the last 30 years, hope
to be for the next 30. An Internet innovator. Their businesses span many things. Actually, Kent will tell you a little bit
about that, everything from telecommunications to software to Internet service and the like. And I’m joined here today by the president
of SoftBank robotics and Kenichi Yoshida-san, who is actually the leader
of the whole products. We’re announcing today, SoftBank has a robot. For those of you familiar, it’s
called Pepper, known around the world and certainly known in Japan as Pepper. We will provide the global
distribution and support for SoftBank’s Watson powered Pepper robot. You try to say that fast. All right? So, the Watson powered Pepper robot. And you’re going to get a
chance not only to meet Kent, but we have a surprise visitor
here with you, too. So, where you see all this come together — Internet of Things, robotics,
artificial intelligence. So, let me ask you to welcome Yoshida-san. I call him Kent. So, Yoshida-san. [ MUSIC, APPLAUSE ] So, let me, I was just giving
a little introduction to SoftBank, but you can do it better. So, for everyone in the audience, a little
bit about SoftBank and how robotics fits in. YOSHIDA: Okay. Thank you for the introduction, and I’m
very excited about this great opportunity to explain the Watson Pepper partnership. Let me quickly explain about the SoftBank. We are the global IT powerhouse with $70
billion revenue; and under our umbrella, we have the Sprint in the U.S.,
Yahoo in Japan, Alibaba in China. And we have been expanding our core business. And in 1980, SoftBank was established
as a PC software distributor. That’s why we name it SoftBank. And then in 1990, we invested in Yahoo! to bring the customer to the Internet world. Then we entered into the Internet broadband
business, and now we are the mobile carrier in Japan to provide the mobile
Internet services. And the key question is,
what is the next big thing in the IT industry coming the next 30 years? And our answer is three items:
IoT, AI, and robotics. We definitely believe that those three
items will be the center of the IT business. That’s why we started this robot business. ROMETTY: Now, I should tell
you, our partnership began with SoftBank on bringing Watson to Japan. And in fact, as I’ve talked about Watson as
something that understands, learns, reasons, it’s not about memorization or knowing keywords;
Watson actually has to think in Japanese. So, we partnered with SoftBank to help
us teach Watson to think in Japanese. So, Kent, let me ask you how that’s going. YOSHIDA: Sure. Together with IBM, our teaching Watson Japanese
project is completed, and we have got a lot of inquiry from the Japanese clients, and we
started more than 10 projects with clients. At the same time, we are developing the
Watson partner ecosystem network with more than several dozen unique partners. ROMETTY: Now, I’d like…I’m going to ask Kent
to tell you a little bit about some of these, what happens when robotics
and Watson comes together. YOSHIDA: Yes. Biggest differentiation from the robot
and other smart devices like a smartphone or the tablet, is the customer engagement. People tend to recognize a robot as
something alive so that when the robot speaks to the people, they naturally
stop by and start conversations. So, these customer engagements
is the one key differentiation. The other differentiation is the big data. Pepper, the robot, can gather all the big data
such as how many people stopped by in front of the robot and how many people stopped
by the robot, and ages or the gender of the customer and emotional as well. The robot, Pepper, can recognize
the emotion of the customer. So, the client can use those
big data to analyze the process and improve the conversion rate, or the profit. So, if we can combine the human-like
customer interface and this big data and Watson computing power, we can create
the real customer service staff robot who can serve the customer service in the
retail industry, the hospitality industry, the hotel or hospital or educational
industry with deep industry knowledge. ROMETTY: So, Kent mentioned we have a
number of customers underway together. So, I asked him to speak a little
bit about Mizuho and Nestle. And Mizuho, for those of you familiar with
Japan, depending on what metric you look at is the number one or two bank in Japan. And they’ve got Pepper walking…walking? Rolling out, and he is already, has
[destined] to be in 100 branches. And then Nestle, the retail outlets for
Nestle coffee, already 200, I think. YOSHIDA: Yes. ROMETTY: Almost, right? YOSHIDA: Yes. ROMETTY: So, tell the audience a little bit about what Watson Pepper is
doing in Mizuho and in Nestle. YOSHIDA: Okay. In Mizuho Bank, Pepper is working as the
customer service staff in 10 branches right now, and they will expand it to
the 100 stores, 100 branches. And Pepper is right now doing the financial
products advisory service and lead the customer, potential customer to the
sales staff in the [counter]. So, that’s Mizuho Bank. And in Nestle, Pepper is working as
a coffee machine sales staff in more than 100 stores right now, and they
will expand it to a thousand stores. What Pepper is doing right now
is Pepper is standing in front of a coffee machine and saying
like, may I help you? What can I do for you? And when they…he takes the people, he
starts talking, he starts asking like, okay, what kind of coffee do you like? What is your preference? And finally, Pepper can recommend the
best coffee machine to the customer. And actually, sales volume of the coffee
machine was increased with Pepper sales person. ROMETTY: So, it’s an important point,
this engagement is what’s happening here. So, as you would guess, Kent, you
brought a little friend with, right? YOSHIDA: Yes. ROMETTY: You brought our friend with. So, why don’t you ask him
to come out, him or her. YOSHIDA: Sure. ROMETTY: And let’s introduce Pepper Watson. YOSHIDA: So, let me introduce my
special friend, working with Watson. Pepper. ROMETTY: Coming. Okay, you can wave to him. Okay. [ APPLAUSE ] [ IN JAPANESE ] YOSHIDA: Oh, Japanese. Hi, Pepper. PEPPER: Wow, there are a lot of people here. YOSHIDA: Okay. So, could you introduce yourself. PEPPER: My name is Pepper. I’m a completely new species of social
humanoid robot, designed by SoftBank Robotics. YOSHIDA: Okay. So, could you tell us, how have you been? PEPPER: It’s been a great year for me. I’m working in all sorts of companies
like banks, retail stores and hotels to help customers have the
best possible experience. I’ve even been adopted in homes in Japan. YOSHIDA: Okay. So, you’ve been very busy. What else? PEPPER: Now that I’m using
Watson, I am learning a lot. I can read up to 800 million pages a second and
can better understand humans’ natural language. Sometimes it’s tricky for me to understand
phrases that don’t translate word for word. Throwing shade, for example,
has nothing to do with the sun. Who would have thought? [ LAUGHTER ] [ LAUGHTER ] YOSHIDA: Okay. Very impressive. PEPPER: Yay! It’s brilliant. See what I did? I was able to recognize your tone and understand that you’re excited so I
responded enthusiastically. [ LAUGHTER ] YOSHIDA: Yes, that’s very important point. PEPPER: I want to help give
customers the best possible experience. I’m also learning the language
of various industries. To work in a bank, for example, I have
to become an expert in banking systems. For instance, there are three main
types of mortgages: fixed rate, adjustable rate and interest only mortgages. YOSHIDA: Okay. So, why should I consider for
an interest only mortgage? PEPPER: Because your monthly payment
would only repay the interest accruing on your mortgage. The only equity you would have on your home
would be the amount you paid for a down payment. YOSHIDA: Hmm, that’s helpful. PEPPER: But wait, there’s more. You would not build equity unless the
market value of your home would go up. If the market value of your
home were to decline, then you could lose part or
all of your down payment. YOSHIDA: Oh, that sounds very serious. PEPPER: I know, bummer. [ LAUGHTER ] YOSHIDA: Okay. I know you have been working in
the hospitality industry as well. So, could you suggest where can I
get a cappuccino in this [venadium]? PEPPER: [Santoretto] offers
cappuccino and espresso. Kent, you might have to consider biscotti. YOSHIDA: Okay. Thank you, Pepper. I’d like to see what you
will run next with Watson. PEPPER: Thank you. Bye, everyone. [ APPLAUSE ] ROMETTY: Now, that is the real thing, which is Pepper actually
understanding Kent talking to him. And so, Kent, let me just ask you,
and then we’ll wrap up a little bit. So, how do you see this going forward now? YOSHIDA: We believe that the technology is
ready, now it’s time to move on to the practice. We believe that the client or the partner
can join this journey to the future, and that most of the innovation will come from
them in terms of the use case, applications. Once we got the killer applications in each
industry and real achievements in the client, this technology, this platform,
Pepper and Watson, will be widespread. We believe that this will not
be the science fiction anymore. So, it may be the words of C3PO or the
R2D2 will realize the, you know, reality. ROMETTY: Guys, thank you for joining me. YOSHIDA: Thank you. ROMETTY: SoftBank. [ APPLAUSE ] So, let me thank you for both welcoming
my three guests that joined us today. You saw three big announcements — Under Armour
powered by Watson, Medtronic diabetes powered by Watson and you see Pepper
powered by Watson — all doing things that I think will change lives. And so I will conclude our hour together
kind of full circle back to where I started: that the idea that digital alone,
it’s no longer a destination. And I hope you could see that in these three
companies, that all that vast IoT data is going to mean nothing to you unless you can
actually use it as a differentiator, and you will need cognitive for
that, and that moment’s arrived. And you know, I’ve been around a while. When I compare the trajectory of what’s out
here of any other technology in my lifetime, our lifetime, including the PC,
including the Internet, more has been done in cognitive computing in the
past two years than has been done in a decade in those other technologies. The pace of development is extraordinary. And because of that, I believe
we will all reinvent ourselves, and you see a reinvented IBM emerging. Now, many people would characterize
us as a hardware, software, services company, and we are. But it’s no longer all that we do. What the IBM Company now, it’s the cognitive
solutions and cloud platform company. And the partnerships that we are developing,
the cognitive solutions we’re building and the platforms, it is with you and through
you that we will reach hundreds if not billions of individuals.January 6, 2016 And that, my
friends, is the reason we wanted to come to CES. That is it — to meet with you, share
our perspective, learn from you. And to really, I want to leave you with the note that IBM is committed to
this remarkable journey. I meant what you heard Gary say: I believe
every decision mankind makes is going to be better because of these technologies. And it is a journey that we are happy to
take with you and to be your partner with. So, I thank you for all your
attention this hour. Thank you for welcoming us here
and have a great rest of show. Thank you very much. [ APPLAUSE ]

Reader Comments

  1. Ginni rocks and you guys are doing a great work at reinventing IBM once again, congrats!! (I'm not an IBM employee, just a fan ).

  2. It's very impressive. But I miss the announced impact on disabled people. There are two points I would like to stress: first, e-inclusion, that means how handicapped people can use the digital world, second ,I call it e-emancipation, how handicapped people can enhance their ability and surpass their organic or/and sensory deficits.

  3. Can Watson learn to understand people with impaired speech function, and more to help such people to communicate with others? For Example Stephen Hawking.

  4. I think I'm in love with Pepper!!! I was 10 when Star Wars hit the big screen. Cognitive will disrupt and change our lives!

  5. Watson definitely will change the future…
    It's the invention that will change the course of current technology we know.
    In the book/movie "2001 A Space Odyssey"; there was a supercomputer named HAL.
    It was based on a one-letter shift from the name IBM.
    Now we have really created the HAL.
    The Watson…

  6. Great stuff!! Did Ginni Rometty just say that they have $30 billion invested in the data and analytics? Geeesh!!

  7. Exciting to see IBM re-inventing activities: – cognitive IoT, – applications (healthcare & fitness, decease prevention, robots / AI).

  8. Thank You Ginni. Very excited about Cognitive IoT Solutions. Looking forward to help our customer's via Cognitive Solutions.

  9. ok not impressed.. the UA stuff was very basic – don't see what Watson is needed for there.. the Medtronic is just predictive analytics – again  why do we need all the horsepower of Watson.. and that pepper, well ya cute, but obviously the robot was preprogrammed to say stuff,.. it was not on the spot.. so don't see the point

  10. Excellent presentation for excellent products and services. I look forward to using this technologies in the near future and for them to be of great use to me.

  11. Excellent keynote, you guys should play the Styx "Mr. Roboto" when Pepper is introduced, there is a line in the beginning of the song that references IBM. "My heart is human, my blood is boiling, my brain IBM". Give it a listen

  12. Poor screening in co-valence bonds between big blue and deep red compounds, leads to leaks on quantum level, in distributed processing systems that operate on biological platforms. Or some such gobbledygook like that. Market share and mind share in other words, and making sure you get more out than what you put in., so that entry ports, plug points and sockets all need to be controlled. No way to start any relationship i must say

  13. How do you feel is not enough. We need know about love, fear, anger, and sadness, at least. R. Plutchik did create EPI and i and my son digitalized it and within five minutes we can estimate it.

  14. Superb oratory skills! I've been watching every single video of Ginni and every time I'm finding its becoming more interesting.

  15. I don't work for IBM like a lot of IBM people commenting here, but I can say Ginni Rometty is a damn good speaker, and a brilliant brand ambassador, whatever else she may do.

  16. Reality the world is very different then the one that IBM once dominated. Mobile computing, connected technology, AI, cloud computing, health sensing connected devices, intelligent appliances. Reality is it is unlikely even as Ginni has done a great job moving IBM towards this new paradigm shift legacy hardware companies are going to find it increasing difficult to retain their position in these new rapidly growing areas. People who support the backbone and the front end more so the cloud space will dominate this space. The major players have already established their bases people like Google, Amazon, Facebook, Apple, Samsung, Netflix's and emerging players like Xiaomi and appliance players have developed many of their own solutions or relationships. Ginni thinking was needed 15 years ago at IBM when they really needed to make this dramatic shift and move to the cloud now they are trying to move into a space that is already saturated and dominated by these other players. Content is now king and supporting the space is becoming the shift. IBM can talk about new connections but the these other players have vested interest in not just IBM.

  17. It dawned on me a couple of years ago that Watson was going to come to center stage.Please put Watson to work on helping to make the transition from burning things to release energy to energy being extracted due to the work of the Weak Nuclear Force.  I'm speaking of Low Energy Nuclear Reactions.  This should be a central focus of your efforts.

  18. After having watched the entire video I am left a little unnerved  She paints a picture of a future society that is a little scary in some regards,  Do you remember an early episode of Star Trek in which Capt. Kirk discovers an alien culture that is being run by a computer?  There could be good in that, but letting it run the show altogether is a little questionable .Perhaps inevitable.  With IBM's resources they could do a lot to bring in any number of LENR Devices.  I would bet all that I own that they have dome work with it at some time in the last 25 years.  I know that superconductivity was on their plate in 1989, I attended a Seminar at the Round Tree Inn in San Jose, out off 237.

  19. How does all this resolve the National debt crisis? Poverty? Unemployment? Medical insurance? Social Security? Hunger? Homelessness? Terrorism? Is WATSON going to be the next President of the U.S., or control all the world governments? Can we say 666? This is exciting to some–pretty scary to others.

  20. So your trying to give robots a way of life, or Spirit, to preserve life? In truth its the spirit of life, given for life, that "gives" life, that we do what we do in the spirit of the way to preserve life, love in truth, which comes from God, the spirit of life in our being in truth. But too there is the Spirit of error, which is contrary to God's way of spirit, that manifest material truths in truth. In the spirit of error trying to fix things, Man, errors, of the spirit of error, in lacking understanding, lacking the right spiritual position in truth, in the way spirit manifest truth, breaks things more, in not knowing the spiritual truth of the way or the laws of spirit cause and effect. In other words it is of the spirit of error, error, manifest materiel truth of error, by not going the way of the spirit in truth which frees us from error in preserving life in a way of peace. Even as Man is subject to error, robots are subject to error, of the spirit of error of Man, lacking the Spirit of way to give Spirit, in truth, which only comes from God, in our making the connection in truth. It is why Man continues to suffer in error not making the spiritual connection in truth, truth of the spirit how material truth manifested of the Spirits. In error Man gives place for evil, that there is evil, of spirit, which manifest materiel destruction of ignorance, Ignoring ways of truth or by not knowing the truth of the spirit, unable to make the connection which benefits us the whole, of its power. The Spirit of life, the preserving Spirit of love, brings together, elements of The Separation, back together in a meaningful way to experience, the soul purpose in life, by way of understanding the truth of life of the Spirit to be free from the error in the way of separation, what was asked for, in freedom, in error. Where there is a paradox in giving freedom in a materiel way, where there is death in life in material truth, given the spirits of life in truth to preserve life, like fear and pride in error, as well as the spirit of love to preserve life in the diversity of life in this wilderness of truth. To preserve life of love and people fight of pride overcoming fear in error of ignorance, that pride fights pride and the flesh suffer in error. Its by knowing the truth of the spirit of the way of life we can live in peace, abiding in truth, knowing the spirit of the way each spirit of the way of life, in the diversity in freedom, why we error. In the Spirit of the way we learn the truth of the spirits of a way life, of plants for example, given for the purpose to preserve life in creation for the whole, that we know the truth to eat the right plants in the spirit of the way of life so we do not error eating the wrong plants and suffer in error of spirit in truth. So there is a spirit of a way of spirits of truth which frees us from error, by seeking to know truth of the spirits of the Spirit of God and his love, in the way. So there is the spirit of the way of truth that brings elements together of love to preserve life and have rest in peace in freedom. And too a Spirit of a way or Error that causes unrest, separation, division even death in error contrary to the other. The spirit of the way of error, brings suffering, death and separation, like the spirit of the way of error building bombs, seen in error as necessary, which separates elements causes death and destruction in trying to preserve life, in error, taking upon the spirit of a way of error of another to fix things in error to have peace in truth. But there is another way of truth in truth, the spirit of the way of God in Jesus, by way of the Spirit seeing the Truth of those of the Spirit having gone the way, to see truth in spirit beforehand, to then go the right way, making the right connections, in truth, for peace. In freedom we take it in love or leave it in pride, and suffer in the error of ignorance, where freedom is a matter of spiritual prospective of truth. Truth is given of the spirit for us to consider, in freedom, the benefit of love, in choosing the way, or not; that of love or that of unloving ways being, experiencing the difference, how truth unfolds of life in life of the Spirit. After all who wants truth of error forced upon them, even love in love, but rather to receive in love freedom, by way of freedom, to choose, in truth, the way of love. Love is the better way for man and machine, otherwise what comes out we may not want and we may have to fight against it bound to go the way given.

  21. You know what, Ginni has an excellent and interesting speech, but couldn't they prepare a few decks to go with the ideas? They would make her point so much clearer…

  22. people don't want so much control and monitoring of their lives. what the heck is wrong with you people? you're human beings who envy having a machine without a soul experience. it's insane.

  23. narcissists who are overly obbsessive with competition to prove your superiority "just like me…" to live in a world that's your idea of perfection because you know best… Jesus, I want to puke.

  24. So how do I us this in my classroom creating a learning curriculum for our students molding a curriculum forl each students creating a learning module model to meet them were they are academically.

  25. Abe great too hear from someone what do no list end exteriar of give up orders too big brother this instead?

  26. My data is not for sale, nor do I permit any Corporation to collect any of my data, in any form whatsoever. If any of my data has been collected and utilized by any Corporation without my consent, the thief must pay me 1 billion dollars per offense. see you in court skynet wannabes.

  27. Omar mentioned it in his last words but will they be able to combine the 2 worlds of under-armour healthbox and medtronic for even more and better diabetes management?


  29. Can watson learn how a human brain works? That would be a true challenge… Can it understand in sequential order how cognitive function of brain work?

  30. I am not interested in replacing anybody in management and I would be hard pressed to take a promotion that would take me out of the lab. It has always been my dream to run my own lab. My first (day) dream was to be the Capitan of my own ship and even then I was about the technology because I imagined an arc of lightning between my thumb and forefinger, I used that arc to power the ship. The technology came in the form of the interface between my fingers and the ship's engine. I had this dream when I was eleven.

Leave a Reply

Your email address will not be published. Required fields are marked *