>> you're watching booktv on c-span2 with top nonfiction books and or authors every weekend. booktv, television for serious readers. >> now on c-span2, "the communicators" is next with a visit to the annual consumer electronics show in las vegas. then live at nine, we'll take you to the university of louisville in kentucky where senate minority leader charles schumer is speaking. and later, the senate gavels in at 3:00 to begin work on immigration legislation. >> c-span, where history unfolds daily. in 1979, c-span was created as a public service by america's cable television companies, and today we continue to bring you unfiltered coverage of congress, the white house, the supreme court and public policy events in washington, d.c. and around

the country. c-span is brought to you by your cable or satellite provider. >> host: and this week on "the communicators," more of our visit to las vegas and the consumer electronics show which is one of the largest trade shows in the world, about 200,000 people come every year to see it. about 47 million people visit vegas on a regular basis. so here's more from ces. [inaudible conversations]

[inaudible conversations] [inaudible conversations] >> host: so, adelyn zhou is, what do you do for a living?

>> guest: i am the chief operating officer of topbots focused on artificial intelligence and machine learning. we help executives, one, figure out what this artificial intelligence is, this technology, and two, how to actually use it and apply it within their businesses. >> host: and i've been asking everybody this, how do you define artificial intelligence? >> guest: it's a great question. i think we define it as using computers or technology to reach human or even beyond human levels of ability whether it's automating different processes or different or parts of our lives. >> host: give an example. >> guest: oh, there's so many. i mean, you can have artificial intelligence in something as simple as your music playlist or your netflix queue, those are all technologies using machine learning to figure out what movies you like to watch and what music you like to listen to. it can be in your e-mail

internet system and filtering out spam. it's not a person there marking things spam or not, but a computer algorithm using technologies like deep learning within a.i. to do that. and then on the other end, you can have artificial intelligence powering self-driving cars, right? autonomous driving uses vision and machine learning to help a car navigate city streets. or my favorites and one of the areas most people are excited about is health care and using artificial intelligence to help doctors better diagnose different skin diseases or people's potential chance of getting heart disease. >> host: so, adelyn zhou, can that artificial intelligence teach itself, can it go beyond what humans are capable of? >> guest: not yet. so in our book, "applied artificial intelligence," we actually spend two chapters helping people understand what a. i. is. it's one of the most commonly misunderstood things, and in the media right now there's so much actually fake news around what

artificial intelligence is doing and do. so when you think about a.i., it's a spectrum of automation. so as a really basic area, you have really simple what we call rule-based systems. they're like if you are -- [inaudible] say, peter, you say is, a, and, you know, i will respond with b. it's just automation, it's not really a.i., on the other spectrum is what we call artificial general intelligence. so that's where you hear about robots being smarter than humans, having super-level intelligence capabilities. we're not there yet. we are kind of somewhere in the middle where artificial intelligence is being able to create, create music, create pictures, things like that on its own as well as a.i. that's being able to learn. so starting to learn things, but it's definitely not there and can't have a conversation with, like, you or i can have and jump

from, say, talking about source one minute and then talking about the news and talking about process my the next. philosophy the next. >> host: saw one of the robotics companies here with a big sign that said, sorry, but we can't take over for you. [laughter] was that -- do people feel uncomfortable with a.i.? >> guest: i think there's a large, a mix of unknown. a lot of people are not -- first, a lot of people don't even know what a.i. is, and we work with a lot of the leading, like, c-level executives, the major companies, and this is kind of this nebulous thing. what is a.i., it's a catch-all. what exactly people don't know. and when people don't know what it is, it becomes really hard for them, right? and you start or getting scared. hollywood, the movie industry doesn't do us any, like, help by turning out movies like terminator and the world's going to come to an end. we're definitely not there, and we have many years to go. the exact number of years

varies. if you ask any expert, it's anywhere from 30 to 50 or more years to reach that kind of terminator level. if at all. >> host: who founded topbots? >> guest: we founded topbots with two of my colleagues, maria and marlene. >> host: and how did you fund yourself? >> guest: we decided to actually be a real business, and so we fund ourselves with clients. and so we invested initially our own capital, but from then we decided that the best proof of a girl business is getting repeat clients and client work. so we're using that. >> host: the best of what kind of business? >> guest: the best kind of business for us. we'd been in venture businesses, but we wanted to be in real business -- >> host: and it's three women. >> guest: three women. it's kind of unusual. >> host: what's the reception out in silicon valleysome we've heard a lot in the news about silicon valley.

>> guest: yeah. well, the three of us have been in technology for most of us in our careers. i think for us, we're used to it. even at ces, jumping on the plane coming here, it was 80% men, right? things like that. you kind of just get used to it. you form partnerships with other women and men who are very supportive of women, and you try to do the best work and be recognized for your work. >> host: now, adelyn zhou, you mentioned the book you co-authored, it's called "applied artificial intelligence." what's the theme? >> guest: it's how do you actually use a.i. today in your business. so what we found is there's so much misconception, people don't actually know how do i use this technology and make my business grow. and so what we've found is you have really technical books that are so technical that you and i, most people would not be able to comprehend. and then you have books that are thinking, hey, what will happen

when the robots take over or what happens, you know, with super intelligence. but for a business leader, there's no real handbook on how do apply a.i. to my business today, framework and how to i as a business executive focus on something maybe other than quarterly returns and focus on investing in technologies that will revolutionize and change our company? >> host: okay. we're going to put you on the spot here. we come to you, c-span is a media company, help us use a.i.. >> guest: yes. >> host: what do you tell us in. >> guest: there's so many opportunities for you guys. so first of all, we look at where do you have -- like, one, what are your core streakics, right? -- strategics, right? what are you trying to achieve with a.i.? there's no point in just using technology for technology if you don't have a problem that you're trying to solve or purpose that

you're trying to reach. and so if you're trying to, for example, say reach more customers and you want to understand how do i do that, that would be a marketing and sales question. and so there's a lot of opportunities in that space. so first you would look at -- you can use a.i. to better find the type of customers, or in your case the viewers that would be really receptive to your programming. it could be looking -- finding correlations among different audience bases and finding out, oh, even though this person isn't a diehard political junkie yet, he has these potentials based on these other interests that he he might like it or she might like it. and use a.i., that's one way to find the audience. another way is you can create, for example, ann alexa skill or a facebook chatbot. you might use it to deliver news to your constituents so they can chat with a virtual assistant be like, hey, you know, what was

the latest bill that's being put out to vote. and this automatic, you know, intelligent agent can say, oh, this bill has this type of probability of being vote on, these are the other things that you should keep in mind. so think of like as a companion or advice or help viewers understand what's happening in the government right now. >> host: so how much does that advice not cost me? [laughter] >> guest: it can be super simple. there are, like, products you can use outside like plug and play, and if you have the technology behind sometimes it can even be free. it's your time, right? your technology time cost. or you can spend a lot of money doing a high integrated system, but i don't think cost -- it depends on your skills. it's just like any other technology. it can be anywhere from a couple thousand dollars to, like, millions. really depends on what you're trying to do. >> host: ad lin saw what's your

biggest concern or what's the biggest drawback, in your view, of a.i.? >> guest: i think my biggest concern actually right now, and you talked about it, is the lack of diversity and the inputs into creating these intelligent systems. so fundamentally, machine learning is based on using a lot of data. so they look at day and find -- data and find correlations and, you know, find -- to help figure out and create kind of their output. but if you're underlying data is faulty or if you collect the data in the wrong way, then you can have biased outcomes. another -- and then also if the algorithms that you use are not robust and are, you know, skewed or biased in certain ways, then your outcomes can also be incorrect. so an example would be in the judicial system is, right? they are now starting to use artificial intelligence to determine whether someone should

have a five-year or ten-year sentencing. and they're using that and giving it to the judge, and the judge is looking at it to help make a criminal sentence. but if the data powering the likeliness of that candidate or that person to -- [inaudible] the recidivism rate is based on faulty information of saying a person's ethnicity or gender or age is more likely to repeat the crime, then the output of that would be an incorrect or faulty or biased number. and so is a person who maybe shouldn't have been given a ten-year sentence, you know, should only have been a five-year sentence got a ten-year sentence instead. so it really depends on the people who are creating the algorithms and the data that's there, that's collected is not biased so you take into account all the different nuances of our, you know, everyday lyes. >> host: what about privacy? >> guest: privacy. i think it's interesting because it changes the cost

internationally. in europe, right, they have very different privacy rules, and in china it's like everything goes. i think for us we as individuals do need to take it into consideration how much private information we are putting out there. i think a lot -- all our data is being captured and collected, and these days data is considered the new currency within mainstream learning. and so is i think we should be careful and guard it, we should also be cognizant and circumspect of different companies that are using our data and asking for the day and seeing that they're using it in a right, moral, potentially justified way. >> host: do you feel that the data protections that were offered today are in the regulatory framework should be stronger, weaker? do you have an opinion on that? >> guest: i think it's hard to say. as a -- i think it really depends on the american public and what we want.

i think the thing is even if you have prior stronger regulations, people never read the fine print. and people are willing to give up their information for convenience. and so even with higher regulation, i think it is very difficult if the public doesn't really care and they're, like, i want convenience in exchange for my data. but i definitely think there should be rules and regulations in place to make sure that the data is protected, that it's not -- it's being safeguarded, it's not, you know, being hacked, not being used because our data is becoming our fingerprint, and it's our individual identities, and is so we do need to protect that. >> host: do you find especially in the c suite where maybe an older generation, do you find different attitudes towards technology than you to with the younger generation? >> guest: i think with the c suite they don't necessarily understand a.i., but i think most people we talk to might be a self-selected bias too,

they're all really, really interested, and they do want to figure out how their business can use these technologies. i think they realize that with google and amazon and all these different companies the that their company in order to stay afloat, it needs to embody these technologies. the problem they have is that they have quarterly financial goals that they need to hit and yet at the same time they're trying to invest. and so they constantly have this, i guess, dilemma because some of these investments in a.i. might not happen and might not drive through your quarterly returns for another quarter or couple equators and, therefore -- couple quarters, and therefore it's hard for them to make those decisions. >> host: you're a harvard mba, a harvard undergrad. is this a veer off more you? talking about artificial intelligence? >> guest: i've always been interested in how technology impacts our lives.

i've been start of start-ups and tech firms my entire career, so for me, this is just the next phase. what i love and what gets me up is helping people understand how these fundamental technologies can be used and applied in our lives today. and so for me, i'm trying to translate between the soup iser technical work -- super technical work that's happening by great academics and try to make it accessible to the everyday business leaders so that we can use the technology and improve our businesses. >> host: as someone in this business, what kind of technology do you use regularly, and how do you safeguard your own privacy? >> guest: well, first, i have a sticker on my camera on my computer, i highly recommend people -- >> host: something that simple and low tech. >> guest: yes. a lot of times you see very easily hackers can access your camera remotely. the light might not turn on. even mark zucker wurg and even -- zuckerberg and even the

pope on his ipad have a sticker -- >> host: the one facing you. >> guest: the one facing you, yes. so on the privacy side there. but in terms of just making our everyday lives easier, one thing that a lot of people are starting to use is actually -- [inaudible] so if you love texting your friends and family, it's actually so much easier to use speech to text, and the technology, the a.i. to do natural language transcription, translation has gotten so good that sometimes, you know, you can use that to text people instead. so that can be something simple that you can try and use a.i. in a way to do that. on the work front, i mean, we use different processes to automate our system, you know, when we work with clients, things like that. so we use different technologies within that. >> host: do you find when you work with non-technology companies that the understanding level is a little lower?

>> guest: absolutely. i think that it is a gradual prodepression, and people -- profession, and people are getting smarter about these technologies. if you're not interacting with out every day, you're like where do i even start. and that was kind of the fundamental goal with writing this book, to help give people an access point, a way to start to really understand people who are not necessarily swimming in technology every day to understand what is a. i. and what are the ways that it can impact their lives and their businesses. >> host: so applied artificial intelligence can be read by the general reader? >> guest: yes, definitely. >> host: go ahead? >> guest: oh, no, definitely for the general reader and hopefully it'll have tangible frameworks and strategies that they can actually use it. >> host: adelyn zhou, thank you for your time. >> guest: thank you very much. >> host: and this is consumer electronics show in las vegas. more from our visit coming up.

[inaudible conversations] [inaudible conversations]

[inaudible conversations] [background sounds] >> host: where were you raised? >> guest: i was raised in oregon. [inaudible conversations] >> host: now on "the communicators," we want to introduce you to deepu talla who works for a company called

nvidia. mr. talla, what is n vid ya? >> guest: you know, we are called the a.i. computing company. we started 25 years ago in 1993, started as a graphics and gaming company. so if you're a gamer, a pc gamer, there's over 200 million that are on the nvidia platform now. and ten years ago gaming technology, what's called a gpu. gpu is graphics processing unit. the difference between a gpu and a cpu which is what powers all of our computers, central processing unit, is that a cpu is a -- [inaudible] a gpu is a -- [inaudible] so basically many things in -- [inaudible] cpu's typically have one processer, gpu you typically have thousands of processers, so it's running many, many, many processes at the same time. so we use that gpu, and basically, you know, ten years

ago we started expanding beyond traditional pc gaming into many high performance computing models. for example, i don't know if you know, almost all of the top 500 green work -- [inaudible] and the in the last two years we've gone into many different markets, self-driving cars -- [inaudible] and you've probably seen a lot of the modern a.i. revolution that's happening. we are, you know, right smack in the middle of that a.i. revolution. >> host: so what's the generic definition of artificial intelligence, and what's your definition? >> guest: yeah. i think artificial intelligence, there's many ways to look at it. the way i look attar official intelligence is -- at artificial intelligence, it's just like electricity. a hundred years ago when electricity came about, it was new. but every industry uses electricity. there's no industry that doesn't use electricity, right? so artificial intelligence is going to be the same way.

it's the tool that every industry is going to use. if you look at the last three years or so, almost every industry that we know is being transformed by artificial intelligence. is i'll give you some examples. i think as a consumer, you know, all of us use the iphone or android phone, okay google or hi siri or alexa. all of those are using artificial intelligence. so when you ask -- [inaudible] from your phone or your mobile device to the cloud and then artificial intelligence is running the -- and then the virtual assistant is sending you back an answer. most of it started with enjoying or -- [inaudible] since then it's being applied to, applied in every industry like self-driving cars are a big example here at ces. smart homes, smart cities, robot

you ics. medical imaging with a.i. can help detect images, process images faster than the a radiologist can. and so basically augmenting a radiologist to basically get an idea of, okay, look at the -- [inaudible] tell if there's a problem there. >> host: so in your title, you are vice president and general manager of autonomous machines. >> guest: a autonomous machines. >> host: what's an autonomous -- >> guest: any device that essentially moves you can think of like an autonomous machine. so a robot, a robot for manufacturing, a drone that's going to be used for inspecting bridges in rural areas, you know? video analytics security camera that is going to be on a police car, for example, looking out for suspects or looking out for, you know, amber alerts. so anything that potentially,

you know, a machine that is moving and if you think about it, all of them will be infused with a.i.. >> host: so today so far have i used an n vid ya -- nvidia product? >> guest: you most likely have indirectly. if you're using a siri or a netflix recommendation engine or using any of those facebook pictures, all of that, most likely, you know, you wouldn't know it, but, you know, when you're trying to target a video or look at something, it's going into the cloud. and the gp us are now in every cloud service provider when it's microsoft, amazon, chinese, baidu, alibaba. pretty much every cloud center is -- [inaudible] >> host: you say, say, and l ra, what does that mean? >> guest: gpu is already spaced up with a cpu.

but traditionally for the past 30, 40 years, a cpu, you think of it like -- [inaudible] and that is kind of what comes to the people's mind, right? every computer -- [inaudible] so all of those have been, all of your software runs. now, what's happened for the past 30 years, this phenomenon called more -- [inaudible] every year the performance of the cpu used to get better 50%. so every two years it's a little over two times faster. now you compound that over 0 years -- 30 years. you've had this explosion of a thousand times faster. clearly from the early '80 to where we are now, it's obvious. now, that cannot last forever. so what used to be 50% every year in the last five years or so, it's like barely 10%. and you think that 10 and 50 is

not that much, but when you compound interest over many, many years, over 10, 15 years, it's going to be a factor of finish. [inaudible] so gpu ez essentially took that role of accelerating applications. gpu always is -- that's what i mean by accelerating your applications. >> host: how close are we to a quantum community? >> guest: a lot of people are working, it's being researched, so it remains to be seen, but right now we think gpu computing is the new form of computing. the cp, uz were the form of dcpus -- cpus were the last form for 30 plus years. >> host: so as vice president and general manager of nvidia, what do you spend your day doing? managing peopling -- people? >> guest: having fun. first of all, we have an amazing family at nvidia, a family of 1 is 1,000 ec nears -- 1,000

engineers -- 11,000 engineers, and everybody working towards the common goal. definitely i work with products, building products, define products, working with engineers, and then my responsibility as gm also is to take the products to market. so working with customers all over the world. i travel quite a bit, going all over the world, and essentially make the product successful and then work on the road map for the next one. >> host: so deepu talla, for the consumer how transformational has been cloud computing, and how transformational will be 5g? >> guest: i think cloud computing has been amazing, right? to think about the late '90s and early 2000s, it was all about pcs. and then in the mid 2000s we saw smartphones come to bear starting with android and iphone in the 2007-2008 time frame. and a lot of these smartphones are so successful because of cloud computing.

without cloud computing, you could not have all the apps and all the, you know, all the programs that are running. more so of the creating that we do here, mapping, digital assistant and all the things are going to the cloud, and the cloud is able to process at such a big scale that you don't have the device to be a supercomputer all the time because you have a finite amount of energy if you cannot do everything here. and so the cloud is able to see access to all these devices and do a much better process of centralizedded computing. so because of the cloud modeled together, they form an unbeatable pair. and then the obvious is the next evolution of 4g today, 5g would mean higher bandwidth, lower latency, right, and better quality of service operating. and that's par for the course, isn't it? i mean, mankind innovation, things have to get faster and better because more data's going

to come by, right? .. . >> guest: there's so much coming in. and it's no surprise that you need to have-- >> and you've mentioned this, that so much data coming in, does it get lost? >> well, i look at it today. in almost all case a lot of data is lost. give you an example. think about the security and camerasment you look at the airports, you look like things in office spaces and traffic intersections, you know, you have all of these cameras in

museums and government buildings, right? and 24/7, they go into the-- 30 days and depending on the policies, unless something happens. something that happens humans go and look at the video which means almost always after the fact. so you can't really prevent, because you're adding more and more cameras, artificial intelligence you can augment the human being. nobody wants to watch hundreds of millions and billions of cameras 24/7, the most boring thing anyway, so, artificial intelligence to come in in the form of technology called deep learning, and it can come in, and it can analyze video, analyze video, the anomaly. is there a moment, a purpose

not supposed to be in there. and the traffic, is somebody breaking the law? you can do analysis and then, the human can finish up, but it's augmented. and i think more data today is lost, but the hope and goal is that using the power of the eye, you don't have to lose the data, you can make sense out of the data. if it doesn't make sense, don't use the data, but that level of data, you can actually make sense out of it and then use it for some value creation. >> what's the down side to this connectivity? >> i think with mankind, with any good technology there's always a downside. you go when fire was invented and used for good, bad things. and electricity is used for good things and bad things. as long as there's new

technology, what's the political thing, a lot of people ask, what about the jobs, what does it take away? i think in general, people with artificial intelligence, it's different than all of those, ai is still you. a lot of people don't understand. people don't understand it, obviously there's a little more fear, fear of the unknown, if you will, but what they're finding in all of these markets that ai is coming into, and like self-driving cars. over a million fatalities every year. if we can reduce that significantly with the self-driving car and that's a benefit to mankind. not only that, i mean, if the self-driving car is, you know, doing it, and spending time, one hours, two hours a day in the car driving, i'm sure like to drive one in one week or whatever, but sometimes just want to maybe be more

productive. and working life is given back to me and then if you have self-driving cars, parking spots and the resources in the whole city is going to get better. so there's benefits to this. and so the policy-- so the question is what's the down side? i think it's up to all of us to figure out, policy makers, citizens to figure out what are the potential down sides and figure out what's the best way to a handle it. some would say policies and in general, i'm an optimist. and we can find benefits, and find a way to come around to it. >> we spoke with governor rick snyder of michigan while we were here and he was talking about a lot of tech companies setting up offices in detroit because of the cars and nvidia

set up an office? >> yes, we have an office there and we work closely with detroit, of course, and a drive platform for self-driving, from car makers to trucking companies, to transportation service companies, the business like ubers of the world, the lyft companies of the world and mapping, think of the scale. mapping the whole world. we can pretty much tell not just using gps, but using cameras to map the whole world. you can figure out at any given time just by where you are, so using that, you can actually do that very well. working with all sorts. and we have offices in michigan, detroit area. >> are you finding that the american work force is ready for your company to be employed by you? >> i think so. i think, you know, obviously,

as i mentioned, it's evolving. i actually believe the area that we have has just begun. three years ago, nobody knew. people talked about ai and a form of learning. and the average person did not much about ai. because it was not apply, why would you worry about it. the first deployment just started. i don't know if you're using google three years ago, you're using it now and you use it now, and better than before. and that's just the beginning. because doesn't know the context that you're asking, it could be, are you based on your calendar or something you have to do tomorrow. as a human, you can think there's that level of-- next level of thinking that ai can have. so, i think that the employment cycle, the work force, in the early stages of ai deployment

and ai gets deployed more than more. in almost all cases that i'm seeing now, everything that i worked on robotics, or whether it's the deployment or self-driving cars and in almost all cases it's linking to the human being. and it's not quite-- that's why i think the work force is ready for it. is the work force ready for the platform? yes, we could really become more productive. the self-driving car as it comes in, it's going to get more productive and the same thing about manufacturing, and you know, things in the warehouse management. you know, the warehouses are getting so big, so tall, and you don't want humans climbing those things, those things are a fantastic example where they can come and augment the hume being. i give you the example of video, if you want-- something bad happens, right, and you want to find out the video for the tra of--

traffic. you can spend 24 hours to get to that frame or have ai, all on video and then finally getting the you interesting piece. and i think these are all things that humans alone can't do. i'll give you one more example. you know, three, four, five years ago, how many packages would you get to your home, maybe one a week, two a week and that's what i used to get. now i go home every day there's like a half a dozen packages lying around and my wife loves to order packages. what are the chances that a human being could be able to do all the packaging and food deliveries and it's just not possible. and you don't want all of these cars and people, not enough people to do all of these kind of-- so i look at it, especially in the near term, given ai in very early stages, in almost all cases it's augmenting the human being, making the human being more productive then in the

future it remains to be seenment it becomes more and more inclusion. and it's true with any revolution. and 100 years ago, and how ma many-- now, you know, i think there's going to be tran formation, but i think in the near-term augmenting the human being. >> we've seen some tech executives limited their children's time using tech. bill gates. do you do that? down that's a good practice? >> i wish i can, but they don't listen to me, but obviously, you know, it's just amazing that three-year-old kids, he started playing with phones when he was three, and you know, he can play, you know, he loves playing on that thing, and then we limit it in the sense that obviously as parents we look at one hour a day and two hours a day and get them to

do other things. and in general, there are some concern that not just kids, how much time are they spending on platforms looking at all the things. and i personally, you know, try to, you know, be listen to an extent and sometimes-- ments are you finding that kids when they're given this at an early age are easy adapters. >> oh, for sure, for sure. i mean, give you an example. so for the most common person-- what is it, right? you know, this past summer in my lab, we have high school kids, these are 14-year-olds, 15-year-old, 16-year-old kids in high school, most of them in the area and they came in and did an internship building robots and they were programming. and 10 years ago, 5 years ago,

i wouldn't think of a high school kid, undergrad kid would be programming ai, but it's becoming so easy and common with these kids, they pick up, the robotics, i don't know if you heard of the robotics, high school students building robots as a hobby. and this exists over like 5,000 worldwide and over a couple of thousand just in the united states, all over the united states. you know, different high schools they all have robotics teams. so they have been building robots as a hobby and now ai coming in the last year or two, they're jumping on board using the technology to use ai for more cooler innings. things. the younger kids are able to take the technology and understand the technology as if it's like, you know, a duck takes to water in a way. >> and how do you use the regulatory environment in the

state of california and in washington? >> i'm actually not-- regulator, depends early on on the industry. so, obviously, self-driving car in the case of california we have self-driving cars and they are doing fantastic. and permission for self-driving ca cars. for without permission, it's hard to take it very far. in the case of self-driving cars there's a debate going on. in the case of super computing and in the case of using ai, you know, you work with, you know, the u.s. government and the nations top supercomputers are accelerated by technology. and that trend. >> what's your background? >> my background is i've got a ph.d. in computer engineers. >> at ut? >> university of texas at austin. i feel like it's a thousand

year, it's 2001, and i've got that. since then i've always been working in technology, i like technology, i start off as an engineer, designing architecti architecting for cameras and smart phones. my ten years ago i worked on the platform, and one day ten years ago i decided i would like to be in technology and business, you know? so, i moved into the business side of things. i still am close to technology because without technology it's very hard, so that's basically what i do work on the technologies and have fun and i can afford to have fun because we have a fantastic family of-- >> and where were you raised? >> i was born in india, i spent half of my life in india, i moved here when i was 21 years old. >> do you think your 2001 ph.d. from university of texas is relevant today? >> oh, absolutely. i think that the way i think

about it is, directly what i did, what i worked on was computer engineering and computer architecture, and all the processes i worked on then are now transferred to the next level. even if it didn't the way i looked at it, let's say three years, four years, five years, we're all going to be living to be 100 years old, maybe 200 eventually when cryogenics come in. and the way i look at ph.d. in technology, explaining. just because it's explaining a certain area, it doesn't mean you have to work in that area for the rest of your life, you pick up new technology, but a ph.d. or an undergrad degree or engineering degree, it's just a way of thinking. it's the way i thought about it and how i molded my career. it didn't matter what it was, what i wanted to do, you know, i can always adapt to new industry and that's the beauty

of it, as long as you're learning continuously and you have the skillset. >> so a couple of years ago, we talked about 3-d printers here and we were very excited and we talked about drones in the past on this show and ai, and some of those things, but in three, four years, what are we going to be talking about at this show? >> yeah, i think in my-- it's always, you know, predictions always got into-- with that caveat, i think the area of evolution given that ai is not an application, it's going to be impacting every industry, i think it's an almost certain that ai, you know, influencing an industry is a given, a no-brainer. now, as to what extent it's going to be depends on each industry for several reasons. it's going to be technology dependent.

how fast can you develop the technology. some technology is easier to develop than not. how fast are the policies going to be. because those are important, too, because you can do something technically doesn't mean you should do it. and which industry will go away, it's going to be dvd or-- and i think the self-driving car is going to be a great thing because it's going to impact humanity so much reducing the number of accidents, building efficiencies and transportation as a whole overall, it's going to be a fantastic thing. in the case of robotics, they're going to come in and augment, robots, but autonomous drones are going to go and do oil and natural gas and rig-- and humans are so expensive to go and look at those things. robots, are huge, people come on board in the next 40 years.

we've got to feed them. there's not going to be enough farmers. the robots need to do that. these are the industries that i think that ai infusion is going to be, you know, just a no-brainer. >> deepu talla, nvidia. thank you. [inaudible conversations] [inaudible conversations] [inaudible conversations] [inaudible conversations]

[inaudible conversations] [inaudible conversations] [inaudible conversations] >> now joining us on the communicators is andrew shuman who is vice-president of products for the microsoft corporation. mr. shuman, what are some of the products we could look for microsoft. >> i run the cortana team so

i'm keeply involved in the efforts to think how this natural assistant can come out and change people's lives. i feel it's a nascent step to how people use computers, ai-powered experiences. >> so cortana is ai? >> i would say cortana is ai. >> is she learning as she goes? >> cortana, if step back and think what ai is, on one it's big data and patterns in big data, but ai, how software can be easier and easier to use. and software learns more about natural language, human speech, gestures, the physical world around us and in that way can be much more easy to use and really meets the user where they are. they don't have to learn about the software, the software learns how to work with them. in that way, i think that cortana actually embodies this idea something that you can naturally communicate with and knows you well. it knows the world well because

of the work we've done over the world in bing and boston is a place and a band and that's an important distinction for certain people. so, that being able to have the full knowledge of the world alongside the natural language that's really the capability. >> how does she compare to alexa or siri or hey, google? >> i think we all compare in one interesting way, in that it's very early. these devices and systems are pretty simple to use in simple cases and awesome. when my hands are full in the kitchen it's awesome to set the timer that way or get music playing that way, but what i believe, and i believe is a unique thing about cortana, we can think about how we're better connected to things that we know about you, so if you're using office at work, for example, you can use cortana at home to do scheduling and to manage your busy day, get up in the morning and ask cortana, what time do i have to be at work this morning and how long is the commute. or quickly dial into a meeting

instead and leverage cortana to do that more easily. cortana knows what you're working on and connect you to things you're working on at work on your desk top. one small feature, we allow you to do reminders, and the reminders can be contextual and i'm at home, when i get to the others, update the stock i'm working on and i don't want to forget one thing. remind me when i get to work the update. i'm at work with the power of microsoft word and office and the reminder pops up, in context and flow and helps me connect that. being that ubiquitous having your back, it's an interesting role to play to that strength. >> even though microsoft is what, less than 30 years old or about 30 years old, we think of it as an old line company anymore. how do you think of microsoft and what's microsoft's vision?

>> well, i think microsoft certainly has been around a while, but also continually transformed itself into different areas. myself personally, i worked for a while in the post office group and now i'm working on natural language in the bing group alongside cortana and we think about the sea changes and how we want to think how they impact everyone's ability to get more done and kind of aware of what's going on around them. so, i think that that constant reinvention is fantastic and it's brought a change in the culture how we can go after emerging growing areas of interest, such as ai, and i think that those are areas that continually get me up in the morning and cortana has a lot of young people on the team, it's always a good mix, old hands and young hands. >> and what's going to be the impa impact on microsoft products? >> great question.

i mean, i think that it's so interesting to me, i think we can have all of those devices be connected without any setup, without any work so the idea that all of my devices can be connected to the internet and thus available for us to do interesting cloud services on them is fascinating. on the industrial side, it's a stream of data to help enterprises run their companies better and know what's going on in their systems and on the home level, manage your busy day, where i my kids, when are they getting home tonight. and that's sensors always updating. i think that aspect is really, really interest. >> we talk about these devices as if, oh, yeah, i'll just design cortana. but what is the technology. >> say that again? >> when we talk about these devices casually and kind of expect them to respond to us, but how much technology is put

into them? >> well, i mean, it's an enormous amount of work. to get natural language processing going has been a long, long journey. microsoft first in natural language and transition in the '90 as we're building on that knowledge and information. one of the facts that we built the bing, and that's natural language and processing becomes the key engine, if you will, that's really taken billions to build and make awesome and that's the cooler part of the technology is to understand human language and be able to use that in a very natural way. >> with all the data that is being collected by microsoft, what happens to it? where does it go? >> well, microsoft, as one would expect, microsoft has a

lot of very important enterprise customers and we're built in an era where we have to really treat all that data as our customers' data. and so first and foremost, it starts with having very good systems which people can control and manage their data. if you're an enterprise customers or an end data user. and it's one of the most trusted cloud providers, we adhere to local laws and data centers in different countries so we can adhere to those pieces and we actually have a lot of places where the data couldn't be looked at by microsoft employees only people who worked on the data so we really work hard, i think, on keeping that data as an incredibly important asset for people to have all the right protections that they expect. >> how long have you been with microsoft? >> 25 years. >> how did you get there? >> how did i get to microsoft? . i really enjoyed programming when i was a kid. i had an apple tv.

i wrote basic simple games and i got hired to work on microsoft projects called ren & stimpy an old cartoon character and i worked on outlook for a number of years, wrote the calendar on outlook and years later working on artificial intelligence. >> andrew shuman, vice-president for products from the microsoft corporation and he's been our guest on the communicators. communicators. [inaudible conversations] [inaudible conversations] [inaudible conversations]

[inaudible conversations] [inaudible conversations] >> and this has been the communicators on c-span from las vegas and the consumer electronic show. anything that you've seen today or any of our coverage from ces you can watch at c-span.org.

c-span, where history unfolds daily. in 1979 c-span was created as a public service by america's cable television companies. and today, we continue to bring you unfiltered coverage of congress, the white house, the supreme court, and public policy events in washington d.c. and around the country. c-span is brought to you by your cable or satellite provider. provider. >> c-span history series landmark cases returns with a look at 12 new supreme court cases. each week historians and experts join us to discuss the constitutional issues and personal stories behind these significant supreme court decisions. beginning monday, february 26th, live at 9 p.m. eastern and to help you follow all 12 cases, we have a companion guide written by veteran supreme court journalist tony

marro. and landmark cases, 8.95 plus shipping and handling. to get yours go to c-span.o c-span.org/landmark cases. >> c-span is live at university of louisville for remarks by senate minority leader chuck schumer speaking here at the mcconnell leader named for senate majority leader mitch mcconnell. you're watching c-span2. [inaudible conversations] [inaudible conversations] [inaudible conversations]

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[inaudible conversations] [inaudible conversations] >> live here at louisville. this is the mcconnell center named for majority leader mitch mcconnell. we'll be hearing from the minor leader chuck schumer.

we did get word from our crew, that he did just land at the airport, so we are expecting this event to begin a little later than scheduled. maybe in about ten minutes or so. let you know though in the meantime, that this week in congress will be working on immigration issues, one. things that chuck schumer will be working on with mitch mcconnell as well, as there are plans for a rare open-ended debate on the issue. they'll expect a plan from trump, no chance of passing. the president might be the most influential in this according to the associated press. and a proposed white house budget proposal and a new infrastructure plan. again here at university of louisville just waiting for remarks by senate minority leader chuck schumer.

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