We talked about their Communications Project and looked at some information on Artificial Intelligence. They are headquartered in new jersey. The communicators is on location at Nokia Bell Labs in new jersey. We are talking to the Staff Members about what theyre working on. Joining us now, michael eggleston. What you do here . I am a researcher. I work on. [inaudible] and technology. What is your back ground. Semiconductor devices. My degree is from berkeley. My phd was at berkeley and my undergrad was that i was state university. Are you from iowa . Im from minnesota, originally. Your here at bell labs working on. Optical senses. There anything that detect light. What you are mostly with is a camera. The only see twodimensional images so im working on a 3d imaging technique. Its very similar to radar by using light. Are those in practical use already. Yes, there are, one of them is in the medical field it is noninvasive. That is pretty common, today. Yes, these are becoming more common. They take up a large table and can cost tens or hundreds of thousands of dollars. Im working on taking an entire system and shrinking it down to the size of a chip. We monitor ourselves and the environment around us. How far away are we from that type of technology. There are a lot of challenges that we have to overcome but right now we have all of the building blocks. We kind of have developed with the optimal indication technology. In your work is a completely healthrelated . Is that where your relat headed . Thats where i am headed, healthrelated, sensing the biochemistry of the human being and monitoring our health on a daytoday basis. This was one of the Biggest Challenges we face for humanity which is how we feel and its really something that we dont monitor. Theres a lot of opportunities and challenges that come. We want to make continuous help monitoring a reality. Other sensors and then them math that goes into the optic. Yes, theres a whole section of work that needs to be done both making the components that can be small and integrated, putting it in the system and developing the algorithms to use these new tools, to actually diagnose things so, im not a doctor, i dont have a medical background so what i do they really make tools, new tools that can help those professions do their job. So, you talk about the 3d i image, where else can or is this being used today . Its really seeing a lot of use, the second most common is in skincare so for example if i have an abnormal growth on my hand i can actually do a full 3d scan and tell of its cancerous or benign or something i need to look at. Its completely noninvasive. You have to cut anything off or take a blood sample. There are many other fields people are using, dentistry, you can actually look at the enamel of the teeth and see micro factors before they develop into cavitie cavities. Even inside the body there using this to do internal surgery so they can see what theyre doing on the inside of the body. So really the range of possibilities is in less. Anything youd want to see you could use this technique. A lot of us are familiar with mri. How old is that technology and how is this related to what youre doing. Mri is a pretty old technique, it was pioneered. [inaudible] its a great technique. It lets you scan the entire body, but the resolution is millimeters to centimeters and the entire system is massive and something thats very challenging to scale down. They are very expensive and people dont have access to them. Now with these optical techniques, they can be very small and very cheap and can actually allow us to do a lot of the same thing that were doing with mris and do them at a much lower cost. Whats more important in your work, the scale or the technology . To me i think they kind of go handinhand, but at the end of the day when you can scale something down to a small size, you can make it cheap and even enable it for a mass audience. If we all had access to mri in our daily life it would significantly enhance our health. So to me helping everyone is one of my main goals. Thats what is driving the size down with the technology we have. On your door is assigned that i want to ask you about. Danger, invisible laser radiation happening. A lot of the sensing that we do is in the infrared so its longer wavelengths of light than what you can see and we tend to use rather highpowered systems when we are demoing them in the lab. This is just a warning that depending on what experiments we are running, you might have to wear safety goggles. Now as you can see my doors open, thats how it usually works, usually we dont use these lasers because were really looking at something that is used to scan the eye. Where is a laser . You have an inherent . Were actually surrounded by lasers. I can bring over here and show you some examples. In these date back to einstein, dont they. So yes, lasers date back to the late 50s, early 60s. Based on einsteins work. Yes, stimulated emission. Usually, the factor this. So that the laser. This is a laser. Its a pretty nice laser that is used for optical and the actual laser is much much smaller. The lasers can actually be actually, even for example if you have the air pods, those have three lasers in them. You can actually make those very, very small which is part of the reason theyre so attractive because now we can actually embed them in everyday devices and have an incredible amount of added functionality. This is a laser, we actually have several lasers on this table here and there in all different shapes, sizes and its all about packaging. Lasers are tiny but we put them in large boxes because they are easier to handle. Before we enter in that your daytoday, what were you working on . I am working on a new method to actually implement these systems. A lot of it is actually about when you come to System Integration is writing codes and algorithms actually do what you want to do. Whenever things tiny can actually physically change it so everything has to be automated. If i was actually writing code to do this. Where did your interest in this topic come from . So ive always been fascinated with light. To me my vision is my number one thing. So i went to school i learned more about light and light is amazing because everything it touches, it actually picks up the signature of that material. For every beam of light that bounces up and hits you and me actually carries up information. If i look at it the right way i can gain an incredible amount of information. That kind of curiosity has led me too this path. Michael with gnocchi labs. Thank you. The communicators continues its visit to gnocchi a bell labs in new jersey. Joining us now is a gentleman named sean kennedy. Mr. Kennedy, what is your position here. Im a Department Head and i lead the network team and we are interested in a lot of things but Artificial Intelligence, augmented intelligence, and a whole host of other Network Algorithms that were trying to develop. Before we get into those, what do you mean imap of networks . Well, networks are just a structure that you can look at so we study the structure and the properties and then generally we build algorithms to solve problems so whether its voting problems like how you get information from one part of the network to another part of the network or facebook which is just a Large Network so lots of network type problems come from studying the structures of these networks and you can decide things like who you should be friends with next and other questions that we experience on a daytoday basis. You mentioned Artificial Intelligence. How do you define that question. Thats a good one. Im not exactly sure how i define it. In general i think people think about replacing human intelligence and thinking machines, self driving cars and things like that, i tend to think of it a little bit more like a mathematician so Artificial Intelligence is just a giant optimization problem where we put in a whole bunch of input that is labeled and we build machines for mathematical models that do a good job so we might have a lot of data that is cat images and data thats not cat images and we build a model that can decide which are which are. The way i view it is just a large optimization problem. Is siri artificial intelligenand google . Yes, i think so, whether or not there thinking machines i would say no, but in the states of an optimization problem they would deftly fall into that round. Whats the difference between a thinking machines and a learning machine . Are we there yet. Definitely not. We dont have intuition built into these machines. We do a really good job of conserving the obvious spread by show you a cap picture 95 or 96 would probably get it right, but the machines do an excellent job as well as identifying cap pictures but they are not really, sometimes their surprising us, but you probably drive a car really well so i think theyre not yet thinking machines, theres no, they dont really show a lot of intuition behind what theyre doing. Doctor kennedy, what kind of research or what is the back and of that machine recognizing the face of a cat. What type of technology is that. Generally a big network, its a narrow network, i dont have a picture but the Large Networks were you input the image just by the pixel value, and images nothing until you have these spots on the screen and they show up with different intensity so you can turn it into some digital thing and until you see that digital feed into this network, theres a whole bunch of nodes, in the middle of this with edges that use this to compute different values as it pushes itself through the network. Lets go to the ones in the zeros before we look at whats on the board. Why is everything in ones and zeros in your world . Well because we digitize them. What do they stand for . What they mean. They can mean anything. They could represent your heart rate in your watch as youre going for a run or the pixel images on screen so we can produce the pixel, its a way that a Computer Stores information in ones and zeros so thats normally the way that we deal with information. We are what is in the anomaly room. What are you going to show us . What we are talking about or what we have here is what we call augmentative intelligence. Rather than trying to replace the human thinker, what we are trying to do is build tools that help humans understand information were not doing this in a way that is just for data scientist. We want to make it simple for children, from taking pokemon that children love to play with and explaining to me how it works but also we have stuff for internal tickets, et cetera. We want to ingest data of all types across all spaces. What we want to do is build an interface that allows people to explore this information so they can see this information in a way that theyve never seen it before, allow them to compare things inside this data set so we start to understand why things are showing up on the screen and then ultimately we want to use this information to create knowledge what we mean is we want to be able to make decisions about this information. As you can imagine youre giving some huge spreadsheet or website that you want to ingest and ultimately whats useful for you is to take that data, the ones and zeros in the dots and turn it into information but ultimately knowledge that you can used to answer questions. Maybe your boss is asking you for some information and what we have here is what we call augmented intelligence and what we speak of as assisted thinking. Their tools that allow us to speak better to answer questions better. Lets go to with the pokemon and walk us through what this can do. Youve got to be a mathematician to be able to do that. Perhaps. Im in a stanback, you walk us through the. So this is just a nest of information from pokemon. We ingested different creatures and then you have a whole bunch of extra features that theyre focused on so the screen shows a global ranking of what the smart machines thought were the most important thing so if theres something on here that you find interesting, another feature we feel if youre going to play with data and use data, you want to interact with data so perhaps you find this guy interesting so you simply touch and, now by pet touching him what youve done is youve indicated this is the piece of information youre interested in. Its not showing here but we also have the ability to tell a machine youre not interested in certain pieces of information so once i did that, what you see is immediately the screen was reorganized around the pieces of information are interesting so you can see these are Different Properties of these pokemon, whether its the way they breathe or their name or general category overall. So this is a bit of a toy example, and we did this mostly for kids to think about information, but you know just to play with information or just to get contacts, but when youre thinking about information, what you want to do is take that information and you want to quickly streamline it so the pieces of information you are interested in. I guess you could think about doing an interview and youd quickly like to go through these documents and extract information, something that caught your eye in a document and you select that and you hope that youre able to reorganize the screen to help you filter these pieces of information. Of course when youre thinking about things, when youre thinking about a problem sometimes we dont want to think about the things that are just immediately related to the subject we will look further out and thats what im able to do with this machine. Im able to zoom in and zoom out on the data to look for things that are related. So well see if i can pull up a slightly different example. You have questions . Keep going. Lets see if this one works. I never get to play with us. I honestly dont have this in my office. Lets go with this one. So one of the curious things about Artificial Intelligence, which i guess maybe comes to why these machines are not intelligent in the sense, if you were to train a Neural Network, if you did a good job of sticking images in and you put in a cat image, one 100 of the time it says cap or not cat so your set. See you have this, the question is whats it going to do . Did you learn anything question did you learn anything about that cat or what about similar things like whats going happen if i stick in an image of a fire truck . Is going to solve my problem . Have i learned something about the structure of cats that will help me recognize fire trucks. Its curious that it could return either thing. It doesnt really contain any intuition thats helping you get closer to recognizing different types of images. Youve done a really good job training on cats, for example. So here in this space, what we should be able to do is train a big Neural Network and use this network to help us understand what things are. Lets see what happens. I would hope so. You could possibly, these are all images. Its not based on keywords but more importantly this is on the deep learning features that underpin each of these images. You can see why theyre similar on the screen. Its not because dashiell can tell is a human when you look at all of these images in the middle, they seem very similar. Perhaps you could describe it. Augmented intelligence is being used now. Yes, in a practical sense. It think so. As we build tools very naturally so the idea of augmenting, for example, google can be thought of as augmented membe memory. You dont have to remember anything, you can just go to google and will likely put up for you. So the tools that try to augment, we believe this is a different spin on the actual way we are using this tool. Artificial intelligence. Are we using it today . Like not in this room but on a practical level. Our people in the world using Artificial Intelligence. For sure. Google and facebook and self driving cars, these things exist. These are real examples of machines that are able to do things that humans cant. How far along are we in our research and knowledge of ai . I think we have done it a very good job, so we are where we are right now in the Artificial Intelligence space because of the massive amount of data that are available to us in the massive amounts of Computing Power that exist now for potentially free and for our ability to transport our ubiquitous, the fact that we can collect this data from almost anywhere. The idea behind this reinforcement learning technique in Neural Network is 30, 40yearold. [inaudible] we have more computational power and data to make these techniques actually work well so, as for leading to smart machines or intuition, its hard to say. I think will continue along this path and be surprised at what machines can do yearoveryear, but whether or not this builds intuition, thats it good question. Shawn kennedy, you are also working on virtualreality. I am not working on virtualreality. No. And ive watched a lot of demos but i dont think i should be giving you one. Artificial intelligence, augmented intelligence are the two things youre working on here. Its my main focus, yes. Thank you for your time. You are welcome. And now on the community is on our tour of bell labs in new jersey, we want to introduce you too. [inaudible] what is your title here at bell labs. I am in the Research Department where we work on the next generation of telecommunication. These are integrated circuits but they are highly sophisticated for specific applications. These could be for wireless or optical communication designed only for that specific purpose. Anything that you have worked on is it in the public . Are people using linear products . There are some of the things, i havent been around for that long, only eight years but certainly things that the lab have both have been in the industry we recently released some products. So some of your traffic of your cell phone and internet will go through. So what are you working on now . A lot of things and at the forefront, probably the most exciting is the 5g. Which is. The 5g is an interesting thing because its been a hundred years. [inaudible] this has changed, this is what we do, its what all wire wireless medication is. We wanted to do is create a new era of medication and that is direct communication as a pose to broadcasting everywhere, we want to target it at individuals. We been wanting to do this because our search for data is never ending. We always want more and more and we have saturated our spectrum. We have to go to higher frequencies and they have many other challenges. One of the challenges that the single transmission through the air is just too much. I will talk to you have to directed directly at you and get data from you and then move to the next person. This is a completely change in paradigm and with that a huge set of challenges. Its looking at being rolled out in the next couple of years, isnt it. It is an ambitious goal. Different vendors want to be out there, want to provide this and give users the ability to do this. It is going to be difficult for everybody. I think its a great bell labs problem because theres so many things we need to solve, mostly in terms of cost and management and this itself means that you need more disciplinary environments. Thats why bell labs is so good because we have so much expertise in 70 different areas and it all comes together to produce a result that could be quite revolutionary. My guest said the labs is not the only Research Facility working on it. Not at all. Is the competition. Everything is a competition. In a sense the fact that everyones working on it is exciting and it means its a worthwhile problem and a lot of smart people in the industry are working on it and eventually everyones innovations will come together to create the next revolution and i think were all excited about it. We want to give you more data so with that we can change the way you use your smart devices, years computers and smart phones. You want virtualreality, this is, by their nature a lot of data and that data is not very well supported in our existing wireless network. If you want to enable technology on a mobile basis we can use them freely and we have to think about it, that doesnt include all the other highresolution series that you want to watch. Thats the only way to do it. If you want to get to a point where we can do this freely. You can develop this or work on 5g in a vacuum, cracked. Correct. You have to work with other people were working on similar or related products. Yes i work on integrated circuit design. Im working on that basic thing you earlier so we would be making the communication, but of course that medication would then have to have. [inaudible] a modem and visualizing application, it also needs manufacturing material engineering, civil engineering, all of these have to come together and we have to Work Together. Its not like the 18th century where you can walk out of the door. Almost everything is hugely collaborative. That is the nature of research nowadays. We are standing on the shoulders of giants. I think its quite exciting. To have access to all those different expertise here at bell labs. Yes, definitely. Bell labs is probably one of the most. [inaudible] we have a wide range of expertise ranging from Software Materials and more. Its definitely going to make it easier to have all of this together we also of course collaborate with the universities and even former competitors, we always Work Together to make this happen and i think its going to happen, its just a matter of time. What is your background . I have it degree in engineering. Im canadian and so this is what i worked on similar circuits during my degree and thats the thing about having a phd, its not necessarily about this thing that they teach you, its more of a thinking message what its all about and obviously a lot of people, almost everyone here, Everyone Wants to learn more, invented innovate and its quite amazing. s electrical engineering, is that a misnomer in a sense . In a way im more of an Electronics Engineer than an electrical engineer. [inaudible] it really is for the same reason, we understand more, we need innovations in the same way. Is spectrum unlimited . In the laws of the universe yes, but in the laws of the government no. You have to be very careful and there are rules and ways to make sure that you dont step on someone elses spectrum and this is obviously so people can actually Work Together so whatever you make something and you want to commercialize, you have to make sure you know the regulations. These carriers purchase these for hundreds of millions of dollars or more sometimes to be able to own that spectrum so when you make a device you occupy their spectrum. Its even true. [inaudible] used to have to define yourself to a particular wavelength or sequence but thats just the way it is. It allows them to Work Together and set the standards. Have we gotten more economical, more efficient in our use of spectrum. Certainly. Especially at lower frequencies and this is why we are moving to higher frequencies because weve done everything under the sun to cover the spectrum and put as much data through as we can. These innovations will continue, a lot of it has come. [inaudible] this is a good example, a wireless medication technique where you have multiple channels and receivers talking to each other and even though at any time all these signals are mixed together with Digital Forces you can separate them again. This increases the capacity of whatever medium you are using. You can take these to a higher frequency like 5g that makes it even more challenging. Its very ambitious but thats what you need to do. You mentioned youre from canada. How do you get the standards the same in the u. S. And canada. Yes of course, there are som some, europe is a different entity but youre right, in the sense that there is some collaboration between government agencies, especially at the National Corporations that tend to make sure every product they make would work. Sometimes we have to modify what we make so its suitable. They might be spectrum thats not available in the united states. Has that evened out with the international standard. Not necessarily my expertise but yes, people want to make less versions because theres 20 different rules. Certainly there is some uniformity to make things simple. We are standing in an actual lab. You build things here, dont you. What am i looking at are here. This is a prototype for an array that we bought a couple years ago and we demonstrated this and it was quite exciting. What is unique about this system is that the operational frequency is very high. It operates. [inaudible] as you can see here theres an antenna on the surface thats very, very small. Theres about 20 of them in each little section and the reason they are so small, and the interesting thing about in tennis as they get smaller as the frequency becomes higher. Its just the laws of physics. So a 90 gigahertz, your traditional antenna that would be very large becomes very small. It mixes integration and its very exciting but at the same time. [inaudible] so its a challenge of making appeared this thing is actually capable of sending ten gigahertz of data. Second. Thats many, many. Second. [inaudible] you can target different people. Will this be, is as part of your 5g research. This is deadly part of 5g but the frequency that this particular prototype is working on for Research Purposes isnt necessarily a 5g frequency that will be in the first appointment group. The first appointment is looking to be. [inaudible] this is much much higher frequency. Therthe philosophy is that if you can solve problems you can deftly sell them in 28 years. Thank you for your time toda today. If you would like to see more of cspans indicators program go to cspan. Org. The topic of the book is to start a conversation about patriotism and what it is in this town and to make sure that people do understand that by dictionary definition, there is a difference between patriotism and nationalism. Patriotism is of course a deep love of country, but one key of patriotism and being a patriot is humility. If you are to patriot, you dont take the view that you go around beating on your chest saying we are better than everybody else, where the best, were the strongest but your humble enough to know that when in search of the more perfect union, in the very beginning of our constitution, in order to seek a more perfect union, so thats patriotism. This carries and in certain amount of arrogance and deceit and the danger with nationalism in extremes, you can have extreme economic nationalism. I want to remind people of the extreme nationalism in the 1920s that led to the great depression. It had racial nationalism. Now im not suggesting we are at this point. It can lead to nativism and tribalism. In our great historical. [inaudible] then we are through as the land of the free and home of the brave. You can watch this and other programs on booktv. Org. You are watching booktv on cspan too. Television for serious readers. Here is our primetime lineup. Tonight at 840, gerald horne, history professor at the university of houston talks about two new books on the history of the africanamerican struggle for civil rights. 945 eastern, university of michigan professor examines the role that slavery played in the early history of detroit. And, we wrap up our primetime programming at 11 with her room. [inaudible] former Senior Advisor to rex tillerson. He discusses how religious extremists in the muslim world use social media to advance their agendas. That all happens tonight on cspan to booktv. 72 hours of nonfiction authors and books this weekend. Television for serious readers. [inaudible conversations] we do have a few chairs. You can talk right into the microphone. Let me get right over to the microphone and talk. I want to welcome you all back to a wonderful saturday afternoon here. We want to let you know that this is our First Signing of the month of october, the first of about ten or 15 of