coming up tuesday, governance study senior fellow from the brookings institution and author elaine kaymark on her book about why presidents succeed and fail. then indianapolis star reporter tony cook and tim alberta of the national review about the role president-elect mike pence will play in the trump administration, and a look back on the indiana governor's work in his home state and his years as a member of congress. be sure to watch c-span's "washington journal," beginning live at 7:00 a.m. eastern tuesday morning. join the discussion. tuesday, the american bar association holds an all-day event on the future of health care and legislative policy developments. we'll hear from lawyers, administrators, and blue cross/blue shield representatives. it starts live at 8:30 a.m. eastern on c-span3. also tuesday, a discussion on the world oil outlook with

remarks from opec's secretary general. we'll hear about the outlook for medium and long-term oil supply and demand, as well as the current challenges and opportunities for the oil industry. the events hosted by the center for strategic and international studies and it's live at 9:30 a.m. eastern on c-span2. and then former house speaker newt gingrich talks about the ongoing trump transition and future administration. he'll look at some of mr. trump's principle, and look back to his time of working with him on the campaign trail. mr. gingrich speaks at the heritage foundation, and it begins live at 11:00 a.m. eastern on c-span. follow the transition of government on c-span as president-elect trump selects his cabinet, and the republicans and democrats prepare for the next congress, we'll take you to key events as they happen, without interruption. watch live on c-span.

watch on demand at c-span.org. or listen on our free c-span radio app. the u.s. council of competitiveness held a day-long forum assessing the impact of new innovations on the economy and workforce. this portion includes a series of discussions on artificial intelligence, partnerships among universities, and technology companies, and encouraging future innovations. this is about two and a half hours. >> thank you very much. it's a great privilege and honor to be here. we have in our panel, some esteemed panelists who are coming from the world of research, collaborative sciences as well as venture capital and businesses. so it is a great pleasure to do this topic of artificial intelligence at a national level. i think this is the perfect time to conduct this as a national level and i want to thank council, i want to thank debra and all the council leaders for

giving us a chance to present artificial intelligence. what i would like to do is for the panelists that are sitting here, roy, and cynthia and daniela, i'd like the mention several facts why this is a tipping point where artificial intelligence is today. the tipping point is you see a lot of people are talking about artificial intelligence as the next internet revolution. it is absolutely the next internet revolution. it's very pervasive. not only that, we're now seeing, according to some of the economists and people from china, for example, they are saying this is the next electricity. this is the next energy. why this is all happening. the level of investments in artificial intelligence has been really very high. and we're now seeing a huge potential of all of the ai hardware and software reaching

approximately $47 billion by 2020. that's a huge step up. we see enormous, enormous opportunities in the area of startups, especially in silicon valley, but in many ecosystems as the panelists can vouch around the world. so far there are over 1500 startups across the world that are leveraging artificial intelligence. that's not a small number. you look at the information, for example, ibm watson back in 2011 was simply focused on basic machine learning, not deep learning. now they have 30 components focusing on deep learning today. google had only few deep learning initiatives several years ago. but today they have more than 1,000 components in the space. we're seeing business models being changed, totally transforming the industry, totally transforming the world

of academia and research. this is now entering a stage where i just came back from g-20 in germany. it is a high topic on digitalization task force focusing on artificial intelligence. because as you know, digitalization alone is providing major impetus, major force for growth around the world. additional 20% of growth in artificial intelligence will probably lead to 1% growth worldwide. that's why it's critically important, and that's why we're having this discussion. so with what i'm mentioning regarding all this information, regarding the internet of things right now, they are basically saying it creates a value of over 1.9 trillion by the 2020, 2023. the numbers are enormous. we were just few years ago, again, from venture capital perspective playing with only 200, $300 million invested in

artificial intelligence. but now today, we're going to close the year of probably close to a billion dollars invested in the space. we have with us the managing director of bloomberg data. but you have cost ventures and other groups, intel capital and others who are heavily, heavily investing. in the next several years, we anticipate investments will be at $5 billion in artificial intelligence. so with everything going on, we're on the cusp of major major revolution. the models are going to shift. let me be a maverick here today. i think some companies won't exist because they'll be transformed because of what we're seeing. i will pose a question first to you, daniella, what do you see in terms of the perception and are we reaching the point right now where our economic models are going to shift and change and what do you think the future will bring to the united states?

>> so it's a privilege and a great honor to be here. thank you for this great question about our research area. i would say this is an extraordinarily exciting time for ai. because a lot of the tools that we as a community are developing are maturing. this is due to great advancements on the hardware side. we've heard about moore's law today but similar exponentials are happening in other aspects, in the quality of sensors, the quality of the motors that we have available to us, in how we communicate. practically everything about the digital space is subjected to moore's law, to an exponential. in addition to that, as a community, we have made tremendous progress in how we solve problems.

and the third reason is the event of data. we now have the ability of collecting enormous amounts of data that help us learn how to do things right. when we cannot write from scratch algorithms that will solve those problems. good hardware, excellent algorithmic support, tremendous amounts of data are all coming together. there is a confluence that enables all these things to come together to deliver things that -- to deliver capabilities that we never even imagined even five years ago. so five years ago, nobody was talking about self-driving cars. today it's inevitable that we will have self-driving cars. all major car manufacturers have announced self-driving car efforts and we really expect this technology will come to bear and will bring us safety and will bring us more efficiency and lower impact on the environment. these are all tremendously exciting possibilities for the

future. >> thank you very much. cynthia, just to follow up on that question, what are you seeing? you heard all the facts. we're hearing media tremendous potential, tremendous growth from the investment to revenue potential in artificial intelligence. what are you seeing in the area of robotics in artificial intelligence? specifically i know that you're also involved and you founded a robotics company as well. give us an impression how you think it will change the business models and impact the united states for tomorrow? >> sure. i would definitely say we're at an inflection point of ai. it's really not just about the technologies that daniella had talked about or where you commercialize these systems, but when i first started working the field, it was a case where you had large corporations, advanced technologies speech recognition,

machine vision. you name it, it would take millions of dollars to develop these technologies. and they would hold them close to the chest and productize their products based on these core technologies. what's been happening more recently on artificial intelligence is those tools and abilities have been opened up into sdks. so now third party developers can start to take these ai techniques and put them into their own products and services. so it's this recombinant service happening in ai starting to happen now. you see many types of devices to exhibit artificial intelligence. that's recent. now we talk about google and microsoft services and watson and all the big companies are starting to do that. the way that impacts a company like mine, my company called gebo.

you would have to build all the intelligence into the machine it and it couldn't really change unless it was from its open learning, but now that it's connected to the cloud, you have this ability continue the upgrade the content, the capabilities to continue to have, adapt new abilities and now as a platform, you are able to much like the iphone, a whole developer community of people now able to create applications for robots where they might not necessarily be the person's skill, but through the tools and technologies, they're able to create, so it's absolutely transforming how robotic products are starting to be able to be commercialized and creating new revenue models. this idea of this iphone platform model is quite new, but you're starting to see a lot of companies adapt that. >> cynthia, thank you. i know my own daughter is very much attached to alexa. the new product that came out of amazon and many of you have seen the beezus and his team, you were speaking about the relative democraticization of the tools in the space of artificial intelligence, they just released

a bunch of tools so many developers and many end users and many research facilities and executives would be able to guide their teams to develop ai applications. amazon web services have done this. intel has done this on the hardware side alone. ibm is working as well, so, right now, the structures, even so we don't have the major models in place, or standards, there's a whole serious of democraticization taking place now and it is obvious some of the major players. roy, thank you so much for joining and bringing the venture capital perspective. you're one of the leading players vest investing in artificial intelligence. over several years, we have seen major players from facebook to google to microsoft to ibm, really buying out ideas, buying out startups. people who are is visionaries, people who are leaders in the

space, there has been over 150 acquisitions, 40 alone this year by the corporate venture community, especially of the companies i mentioned. where do you see this going? what's the end game and where do you see the convergence of venture capital and artificial intelligence? >> well, so we invest on behalf of bloomberg, exclusive in companies that influence the future of work. when we started our fund, we did not mention or think about artificial intelligence. this was three and a half years ago. and six months into starting the fund, one of my partners came to me and said we should start looking at this artificial intelligence thing. at first i dismissed her and said fine, if you want to work on it, be my guest, but it's your time. three for our months later, she came back and found 2,000 start up, we prefer the term machine intelligence because it conjures up less of the science fiction nightmare. and cynthia and daniela are

actually inventing. as an investor, my job is to help them plug the injennings into the power at the end of the day and commercialize it. we play a role that is relatively late in the process, which is to say governments, lorge corporations, academic institutions start the chain of invention. and we're just delivering the last mile. so for venture capitalists to be excited, it means it is almost ready. that said, i still think it's early. we are at an inflection point. the way i think about it is the conversations we're having now about machine intelligence are similar to conversations about the internet in 1997. if you remember that moment when everybody started saying well, what is your internet strategy? what will you do? and they hired people with strange titles like web master. that's the level we're at. the tools are starting to democratize. the acquisitions have so far been a blip relative to what will happen. and we look at it well, maybe

this trend of machine intelligence as otherwise people might be able to do, maybe it's as big as a trend of mobile. well, it seems bigger than that. maybe as the internet. actually, i think it might be as big a trend as all of software today. if you look in the productivity numbers, the last 25 years, it's actually unclear whether technology has had that big an effect on u.s. productivity. and i think that's because we've been waiting for the promise of the kinds of inventions that we'll see now through artificial intelligence. >> roy, just to follow up, again, to the earlier statement i made when i was in berlin, the chinese were saying that they creating thematic funds, which are specifically related to artificial intelligence. one alone has put together over $200 million fund. this is right across china. investments are very, very important. for us to make sure our start up committee and to make sure we're reinventing our future and keeping our leadership position which i think we should in the united states, what do we do?

how do we deal with this? >> i think venture capital is a rounding error. despite doing this for a living. at the end of the process, much more important is government investment and large corporate investment in riskier, longer term fundamental basic research. we receive the end of the pipeline. and it's funny. we've now done this study, three of my partners for three years mapping all the artificial intelligence companies. in the first year we got a bunch of calls from academics saying oh, we've been working on this. thank you for finally seeing it. and in the second year oh, last year i saw what you did and i want to put some money in this thing. this year for the first time, the wave of calls is from the fortune 500. we now have big multinational corporations and not the ones who had the wherewithal to invent such as google does, et cetera, but every company is saying wait a minute, i need to do something about this. so, if you are part of the

large corporation, you should be asking what is our intelligence strategy. note like the late '90s with the internet, many companies will blow billions of dollars on foolish ai investments before we figure out what to do. but we'll probably have to go through that phase. but then i think we have 25 years ahead of us of incredible dividends for the economy and for human beings. >> roy, thank you. i agree. i think we need a very cohesive and very solid ecosystem. you can't have venture capital sticking out. you need corporations and well funded research. especially at the government level to make sure that we main maintain our very competitive position. as you know, the u.s. is very competitive in this space. the next competitive are the nordic areas in sweden and norway and other places. >> i don't know how competitive is u.s. is. for what it's worth, this is an area where canada was focused on this issue for decades while the u.s. was basically asleep at the switch. china seems more focused on this issue and i think one of the ibs

issues we have and where a group like this can be very helpful, as an industry right now, we lack strong hypotheses about where employment growth might come from. we have lots of hypotheses about nick growth, but i think this is a warning call to the u.s., which is not the leader on this issue right now. >> thank you. >> i would just like to jump in to add and say i was in china in shenzhen in august at a meeting where the governor of the province announced $500 million in robotics research at local universities for the province alone. >> wow. >> this is for the guangdong province. let's consider our investment, our national robotics initiative is amazing. it's wonderful. it's at $30 million a year for the whole community and our whole country. >> you know the amount the u.s. spends annually on ai research? funding basic a ireport? the president released a report, ai should be important. and the number was a billion dollars. it is nothing. we need at least 10 x.

>> i agreement. and i think it probably should be some sort of a public/private partnership. we need government, families, all of the institutions. just coming back to you, daniel, regarding your home company slovenia and other places, i was just in slovenia alone. they have invested heavily in a lot of the artificial intelligence research and people. but it's not reaching the markets. how do we bring that talent that right now everybody is looking for talent of specific ai, indeed modeling statistics, how do we bring this talent into the united states to develop market-ready solutions and products. >> so that's a great question. i would say that we have a lot of talent at the top universities in the united states, but it's not easy for our students who graduate to remain in our country and give

back after their training because they do not get a visa. it's difficult for them to get a work visa, so i think we need programs that enable our students to continue to stay here. at the moment, many of the students return to their home countries and they help build the local economies there. so we have to do something about that. >> yeah, thank you. cynthia, we are at a point where industries are being created. they're first movers. we've seen what microsoft, what google, what facebook is doing. can you share with us especially in your experience with robots, but the consumer space. what are the first movers and what business molds are they forming as well as enterprises. what are you seeing? what is research doing to align and connect with some of those first movers? >> yeah, so before i answer that, i want to also just raise

the opportunity of artificial in education. so many of these questions around talent and opportunity. again, we hear this theme quite a lot this morning. artificial intelligence offers a whole new innovative approach to bringing potentially high quality education for everyone through mobile devices which are prolific. and i would say we shouldn't only be thinking k through 12 and beyond. well need to start tapping the problem at early childhood. way too much science is showing that critical neural foundation formed in the first five years, even if you start kindergarten behind, it's very hard to catch up. artificial intelligence in these technologies offers an opportunity to bring the experiences to the home so you can learn at home and not just at school, to augment what teachers do. again, i see this as another area of critical innovation that we really need to take seriously as a country. now in terms of kind of the leaders in the areas of robotics, i have to say clearly there are a lot of really profound movers in the space depending on the area of robotics. agricultural.

medical, transportation, cars and so forth, but i have to say, the united states in terms of these first kind of bold companies still is producing a lot of the most innovative products and the motivative models. even in my own sector of personal robots coming into the home, we did a crowd funding campaign to raise venture capital in that stage, you had to put your idea out there. and there have been so many copycats around the world now trying to do what we're doing. because the idea is out there. again, i think often the innovation is being started in the united states. and what i would like to see is the ability for us to continue to lead and own that rather than being taken over because there is so much more investment happening in other parts of the world. >> cynthia, thank you. just because we're a little bit short on time and i have a lot of questions. this is a very interesting topic. i'm sure our audience here as well. there's been a lot of talk regarding autonomous enterprises.

and what makes enterprise autonomous. some people talk about self-service intelligence networks, neural networks. roy, maybe you could talk about some of the examples and what you're seeing in the autonomous enterprise space. >> sure, i'd like to fund a company that runs itself. it sounds like a good thing. it would also be a good thing. we invest this things that are far mature. they tend to be an immediate way to deliver value to a customer. i'll give you a very tangible example. we invest in a company called textio that takes a job description. before you publish that job description to try to get candidates, it analyzes data about past job descriptions to predict the quantity, quality and gender mix of applicants and lets you edit your job description before you put it out there to maximize the potential results in the world. the reality is they're using relatively straight forward well understood learning tech next. we invest in a company that uses

vision to estimate the size of markets. they can approximate how quickly is the chinese construction market growing by counting the shadows on buildings. we have a lot of these data-driven. fsn and health care are right because of the data set. the question this all raise series what happens to the experience of work and jobs. together with new america, bloomberg has been driving a project called the shift commission to study long-term scenarios for work this the united states. and i think the potential range of outcomes we might, it's easy to picture the self-driving truck. uber just did this that made its first bear delivery. we did a meeting with truck drivers in ohio watching that. the self-lending officer, the accountant, the total number of jobs to me is really not the issue. because a balloon doesn't pop because of pressure overall.

it pops because of a pin and we have many, many different professions across the united states where there is some risk of profound change. so whatever industry you're in, i think there is some ai application that is coming for you very quickly. >> roy, just because we're running a low on time, and i want to get into this area of the darker side of artificial intelligence. i'm an optimist, and i believe that artificial intelligence will create lots of jobs in cybersecurity. we're stepping up on value creation in the united states. we're always looking to solve problems. if we are looking to solve problems and stepping up in value creations, we need to have people who are going to be architects, who ares a threat turners. but i understand gardner and forster put out a statement that the press is picking up that there is going to be 7% to close to 14% job loss by 2025 in a lot of areas. i know roy you have done a lot of studies with truck drivers and taxi.

>> yeah, we have looked at all of the research. when we tend to debate these things, we tend to have a point prediction what will happen and therefore this is what he is we should do. the reality is human beings are terrible at prediction. so really the right way to think about it, we believe and the reason we're doing scenario planning for the future of work is to try to prepare for a wide outcome of scenario. >> roy, i apologize. because of the shortness of time. >> sure. and i just want to jump to daniela for some comments regarding the job loss or opportunities in the space. >> so i see ai as a vector for tremendous positivity. i see ai improving the quality of jobs. in other words, consider any job. it's repetitive and predictable aspect can be done by a machine. and that's not just for truck drivers and for other jobs that are really obviously in the line of machines. so, i really see a huge opportunity to bring safety, to

bring customization and to bring more efficiency and joy. because if you have a machine that does all the routine part of the job that you might not be excited about, you might have more time to focus on what you're interested in. >> thank you very much. and cynthia, just as we're coming to the closure of this session, there has been a lot of talk privately and also through the media discussing the ethics issue of artificial intelligence. you know, they're trying to scare us in fact to say that the ai world could be catastrophic to mankind because they'll become smarter. the machines will become smarter han human beings. right? you heard that discussion and the discussion i had several friends from google and other companies that took it further saying that in 20, 30 years, ray kurzwell said we're going attach our brains and we will scan all this information almost like what we're doing with the phones. so they're predicting this scary future. but i'm not sure this is the

future, because we're talking about applied ai. we're not talking about creating a conscious machine. and i want to get your feedback and your perspective on the ethics issue on where we're going with ai. >> yeah. i think the primary ethics issue around ai is making sure the ai we create truly benefits everyone, not just the few. and i think right now if you look at the applications, they tend to be clustered around certain kind of sectors. and it's not being democratized. one of the big reasons i keep coming back to education, to me that's one of the areas where ai could truly, truly benefit everyone on the planet. i think when we talk about the singlarity, it's all speculation. what we know right now is we can within a very specialized domain, we can create an ai that can be -- perform better than a person. but people can do many, many, many things. these ais that do one thing, that's all they ealy do do. the new dialogue that is

happening in commercial is collaborative aspects. it's ai that works in conjunction and partnership with people so that the human ai team is more proficient, more productive, more successful than either the ai alone or the human alone. and that's where a lot of the energy is going. so i don't see the doom and gloom. i really see us being augmented and able to lead successful, fulfilling lives because of that partnership. but we have to get that partnership right. an that's when you get back to the basic research and the application of that research. >> and government support. >> and government support. >> for economic security for individuals. 100 academics yesterday released this economic security project. i'm one of the signatories to call for exploration of the idea of a universal basic income of every individual getting paid in order simply as a citizen, simply because we think we need some compliment to the uneven effects of ai on potential employment. >> thank you. and finally, one quick brief answer from each of you. how does ai impact globalization? there has been a lot of

discussions of this election about outsourcing. but we are now at a stage where we're leaving automation or going to a complete autonomy. and how does it impact developing countries? how does it further growth of our economy? what is your take, starting from you daniela. >> soy like the idea of customization. i like to think about how we do manufacturing today where someone designs all of our products, and they are manufactured overseas mostly. so now imagine that we replace that process with a customized process where we have customized templates for various products that people could customize and with their personal preferences in their own homes that then get produced in a local factory nearby. and this could impact the u.s. and every other country on the planet. >> thank you very much. cynthia? >> yeah so, for me in terms of globalization, i really think in terms of the empowerment of teens, but also the empowerment of the individual. ai offers the opportunity for

deep personalization and empowerment. so services that we have to go to industries and corporations for, increasingly are going to be able to come at a personal level to the home. whether it's finance, planning, education, health care. i think we're going to see the empowerment of ai for the individual in a whole new way. they think will be a global trend in general. shift industries around that. >> roy? >> i'm sorry to end on this, but i'm not sure i have anything useful to add. i consider myself an expert in the u.s. >> america first. >> what do you mean by that? >> less on globalization and less on trade. >> i would say the first mover thing is wily overrated. we need when these things work to benefit the united states. but i actually don't care who benefits first. >> great. i think we as american entrepreneurs, american research, american academia should be investing a lot more. because this is a space which could make a difference for the united states and the world. and we've seen today

perspectives coming from the top academics in research, as well as practitioners in and financial capital. thank you very much for listening and being a part of the future. i think the next time we meet, i think we may have intelligent agents that will guide us to this meeting, will guide us to lunch, will schedule things for us. wouldn't that be a very cool future for us? and i truly hope that it happens very, very soon. thank you, everybody. [ applause ] . next, in a short series of presentations, leaders from industry and national labs will show exciting, potentially game-changing innovations. ladies and gentlemen, plead welcome the director of pacific northwest national laboratory, dr. steve ashby. >> good afternoon and congratulations on your 30th anniversary. very happy to be part of this.

as we clear that so we hopefully don't have a tripping hazard. as we bring up the first slide, please. talking about the grid, talking about machine intelligence and really bringing those together. what i'd like to talk about is energy. it illuminates our night sky. it warms our homes and powers our economy. and thank you. and the united states, we use a tremendous amount of energy. in fact, about 97 quads of energy each and every year. the department of energy's national laboratory, we're working hard in partnership with academia and industry to continue to develop the industries that will ensure we have the clean, affordable and reliable energy that we'll need not only today, but into the future. but another part of what we're doing is looking how we can make greater use and better efficient use of the energy we already

produce. and that's important because when we look at that 97 quads, we waste about two-thirds of it in terms of waste heat and other inefficiencies. let's put that in perspective. what would this wasted energy do for us? well, it would actually power the rest of our hemisphere forean entire year. alternatively, it would power the entire middle east and africa. so that's a lot of energy that we're wasting. if we can find better ways to be efficient with our use of energy, we can save that energy, save money, and reduce capital outlays for new power plants. so i want to talk a little bit what we're doing at pacific northwest national laboratory in collaboration with many others to increase energy efficiency. see if we can get it here. there we go. and particularly, i'd like to focus on our electricity usage.

we use electricity, as we heard earlier, for a variety of things. here you're seeing a montage of things ranging from lighting, h-cav, the equipment we have in our homes and factory, a whole variety of things use the majority of the injury we produce of that 97 quads. and we have made tremendous progress in improving the efficiency of these individual devices and the pieces of equipment that we use when they're running. the next challenge is can we infuse them with some of that intelligence we just heard about, some of the things we're doing here so that not only more efficient when they run, but they know when to run. and perhaps also they communicate with the smart grid to know to avoid peek low times. and that's what we're doing at the laboratory. and the invention that we're coming up with here very simple, but it's something that we're calling voltron. can we get that up here?

there it is. it's a device smaller than a deck of cards. and it's an innovation we've come up with, really combining some of the technologies we already have today for controlling appliances and technologies, being able to do that from building to campus to regional scale and infusing it with intelligence. so what is this device? it is a combination of the algorithms we just heard about, the real smarts running on a very lightweight computing platform such as raspberry pie and made available through open source. so our partners can download it from the voltron.org site and use it in a variety of applications. in fact, one of the things we're eager to do is to partner with different people to explore the different ways voltron can be used. we're also partnering with people to adopt this technology. what can it do for us?

hopefully can move the slide forward. what we have here is we can use that technology to within your building to control appliances or devices. here we're just showing an hvac unit in a refrigerator display case you might see in your supermarket. and you might control that device, a series of devices within a building, the entire building itself, so you now have a smart building connected to the smart grid and tying into the region. more than that, you can also have it talk to the grid. in a two-way fashion which enables concept call tran active energy. this device helps us do that. >> that first example here. and what you can see is that in the case of the refrigerator display case, our colleagues at

oakridge national laboratory in partnership with emerson ran an experiment, and they show that if you use this, you could actually save a tremendous amount of energy. think about those refrigerated display cases. they have a defrost cycle. currently that cycle runs very consistently. it is very efficient but also runs a lot when it doesn't need to. suppose you had environmental sensors that brought in the data stream that told you when you needed to defrost it so you didn't run that defrost cycle when you needed to. that's what voltron allows you to do, and you can control that. 75% reduction in energy usage. and you widely adopt that throughout the united states, it would be enough power for say 200,000 homes. another example that we did, pacific northwest national laboratory with a small company, transformative wave in western washington is looked at retrofitting voltron into an

existing building's product control line they have and using it for rooftop hvac. there demonstrated in a very simple experiment up to 50% energy savings on that device. not buying a bunch of new hvac equipment. a retrofit of that technology into a product they're already offering. this is the promise of this technology, where you're really infusing what we already have in items of energy technology and i.t. to bring together to make these things really smart. now that's what you're doing, for example, just to control a single device or a piece of equipment. you can also do that throughout entire building and make the building smart. or you can look at what you can do in terms of a campus. and that's what we're doing at pacific northwest national laboratory. here we've installed voltron in nine different buildings with a number of devices connected to it. and we actually manage this and look at the whole campus now and what we're doing to control our energy usage, optimize it and

actually make the laboratory itself a test bed for demonstrating the power of transactive control. here is an example of a control room we can use here where we can monitor all the energy and water usage at the laboratory as part of our efforts for sustainable operations. we look at this going on here. that's what we're doing at the laboratory. in addition to that -- whoops -- we also have partnerships going on with the university of washington. and washington state university. they're using voltron in different ways. for example, university of washington is looking at using it in terms of the incorporation of solar technologies into their campus. washington state in terms of the corporation of large scale stationary storage as we heard earlier. they're each doing independent study. what we're now getting funding from, the washington state clean energy fund is to bring that together into a single regional demonstration of the power of

transactive energy where we can collaboratively manage our loads in realtime in response to signals we're getting from the grid. we're doing that in the northwest. we've now been partnering with colleagues in ohio, the university of toledo and at case western university where they're also looking at this with respect to the incorporation of renewables and stationary storage. and they're doing their own demonstration and are plans in the future to link that to the power of transactive control in a larger scale. and right here in washington, d.c., we've already deployed voltron technologies to eight schools and buildings with plans to go up to over 150 within the next year. so here what you're seeing is taking a very simple idea. a lot of smarts in terms of the algorithms, infusing that and bringing it together and working with people to understand the type of applications we could have for this technology, and making it available for our partners so they can integrate into it their existing product lines and new product lines.

we've already demonstrated the ability to save a huge amount of electricity. in doing so, reduce much of that two-thirds wasted energy, and save consumers and building owners a lot of money in the process. and so what we would like to do here is invite you to join us looking for different ways in which we can exploit the voltron platform, how you can develop those applications for it and make use of it. or if you're a company, the product line talked about how you can incorporate voltron into those product lines so we can have an even bigger impact. it's an important to bring together the kind of environmental sensing we'll have in the future throughout our homes and buildings and exploit that to save money, save energy, and make the future a better place. so thank you so much. [ applause ] >> ladies and gentlemen, please welcome dr. sujit chun, senior vice president and chief technology officer rockwell automation. >> well, good afternoon.

let rockwell automation. >> good afternoon. let me also congratulate the counsel on 30 great years. i appreciate the opportunity to speak here this afternoon. in my ten minutes, i'm going to highlight some of the exciting opportunities in manufacturing. we heard that manufacturing is at an inflexion point for realizing unprecedented productivity from a lot of the technology advances that are occurring around us. so if you look at all of the different technology advances, if i can only advance the slide, so when you look at the different technology advances that are impacting us, everything from ubiquitous connectivity, machine learning analytics. we heard a lot about some of these technology, just a few minutes ago. regarding artificial intelligence, machinery. well, the excitement in the manufacturing area is around industrial internet of things.

you've seen projections that by 2020, there will be 50 billion devices connected to the internet. out of these 50 billion devices, roughly half will be in the industrial space. companies like cisco and mckenzie have put out numbers for the new value that this connectivity is going to generate. and that number is around $15 trillion. just a smidgen less than our national debt. so of these $15 trillion of new value 27% is expected to be in manufacturing. that's the largest segment of the benefits industry from industrial internet of things, so that's pretty exciting. if there really is roughly $4.5 trillion of value to be created from industrial internet of things, how do we go about it? what are some of the impediments? i'm going to talk about not just the opportunities, but what are the areas where more innovation

is needed? where more talent is needed and better policies are needed to move forward. let's advance to the next slide. the vision that manufacturing is moving towards, we call it the connected enterprise. basically what the connected enterprise means is bringing together data from your production site, manufacturing sites with your supply chain, from your customer demand inputs, so bringing them together and then optimizing production operations to get the most value from the data integration. so this is the tim idea behind enterprise. we started with the enterprise roughly about six, seven years ago. we started out by rolling out

any rp system, which a lot of companies have done in the past decade. but then it's not just the erp system, but we started transforming the processes. we started working on people, processes and technology and optimize. so a real example, seven or eight years ago, when we promised product to a customer, roughly 82% of the time, we delivered on time. that was not acceptable. 28% of the time we missed the delivery, right. so that was not acceptable. today it is 98% of the time. so when we tell a customer, they're going to have this material, 98% of the time we deliver on time. how do we do that? well, now, we have full visibility into customer demand. we know what the customers are buying. we produce roughly 300,000 products. so knowing what the customers are buying, knowing where the

demand is allows us to produce to demand. it allows us to stock in our distribution center, the products in the highest demand. it also gives the visibility to our sales force to sell products that are immediately available. we call them preferred products. no surprise that we discovered there are 30,000 products we sell 80% of the time. so having the visibility into what's being consumed using that to drive the production processes got us to the 98% number using this concept. as we talk to manufacturing companies and ask them, what do you want from this technology evolution, they come back with four things. they want faster time to market. from a new idea for a product, time to market, they want to optimize that. they want to reduce cost of production. if you look at energy, electrical energy, roughly half is consumed by industrial operations.

a 10% reduction is -- reducing cost is a major driver. the third area that most will tell you is a major issue today is up time. they want to increase their asset up time. you walk into a food and bev type factory, most machines are only up 60 to 70% time, so 30 to 40% of the time, they're under maintenance, may be cleaning place. may be routine updates to the machines that are being made and that impacts productivity in a huge way. the final area that's real important is enterprise risk reduction. building and more safety and security. it's making their environment track and trace. if you have a recall, food or pharma, they want complete traceability throughout the supply chain. these are the four drivers we're focusing on. a lot of innovations coming out

of rock well are helping our customers achieve these four major drivers. so how do we see manufacturing evolving in the future. today, we could say that to some extent manufacturing is modular. and in its own way, it's cure. of course security is never done. we know this is a continuous process. where we're doing in the near future is towards making manufacturing more predictive and optimized. a lot of machine learning, artificial analytics, cloud, mobility, all of these technologies will move manufacturing towards becoming more predictive and optimized. where we want to go towards, the long-term vision is to make manufacturing self-healing and optimized. that's our long-term vision,

probably 10 to 15 years out. but we see a change today. in the past, manufactures were were looking for low cost labor, tax holidays as we heard this morning again from intel. looking for location where is they could put manufacturing where they could benefit from these cost incentives. what are they looking for in the future? they're looking for putting manufacturing where there is technology innovation, technology innovation that will help them solve problems like safety and security, while connecting the manufacturing plant with the i.t. systems. so as you build more connectivity, there's going to be a major security risk. they're looking for good risk for innovating good risk. they're looking for environment where there's a lot of innovation. they're looking for talent. i don't need to repeat what we heard this morning about talent. there's clearly the change in the talent that's needed in plan

plants today. a lot of the jobs where a person would shovel, that's not being done today. we need security experts. we need people who understand how the internet works, that also are living the plant environment, so clearly, there's a change in the skill set needed and we heard enough about education so i'm not going to belabor that point and finally, policies and procedures. we saw a speaker draw this card. if you look at that curve, it's the growth and regulations. we need friendly regulations, we need friendly policies. in the future, that's what manufacturing companies are going to look for. so my final comment, i would love for the council to continue its leadership of manufacturing. we need public/private partnerships. we need help to get manufacturing to its next evolution and it won't happen

without public, private partnership, so thank you for giving me the opportunity to talk this afternoon. [ applause ] >> ladies and gentlemen, please welcome mr. adam conn. founder and ceo of aconn semiconductor. [ applause ] >> thank you very much. before i begin, i'd like to thank the council for having me. congratulate them on 30 years. it's a very important time now in text message and maintaining competitiveness, particularly within our field of advanced materials is crucial. i've been looking for ward to this talk for a number of of months. earlier this year, i spoke at the international forum of the americas in toronto talking about riding the wave of disruptive technologies. it was disconcerting to hear from the u.s.' position in terms

of competitiveness was being questioned and so one month ahead of the consumer electronics show, i am so delighted to be able to engage with you and talk about the work. and how acon semiconductor and our partners are not only advancing the innovation technology, but advancing our competitiveness through clean technology, opening up the possibility, a number of captivating markets. i would like to frame my talk with how it's more -- telecom and automotive market, now, the global semiconductor market is a huge market, $350 billion market worldwide. but specific to the united states, it's actually the third largest contributing to gdp behind automotive. sorry aerospace and pharmaceutical. more importantly, it enables over a trillion dollar global market. within these, three key sub

markets are very limited. power devices. things are overheating, power efficiencies are about 90% inefficient. not good. wearable systems. we have these new technologies. augmented reality, virtual reality, very, very important, not only for fun, but military defense capability and sensing in addition to other industries, it's a $40 billion market with a competitive compounded annual growth rate. additionally, the sensor market is key and these are quite limited by the present materials capability. as the logo infers, we specialize in diamond based semiconductors. diamond has been known to be a efficient material. perhaps the ultimate semiconductor material. diamond can conduct heat five times more efficiently than copper, the current status quo material, but above and beyond

that, there's a highest power in addition to numerous other material attributes which makes it very, very favorable for today's electronic, particularly as we're seeing in the new, different types of cell phones, won't mention names that are being either incinerating on power up or being ship damaged, so we know heat is still a major, major issue. and from diamond, we can see not only superior performance, increased energy efficiency, but thinner profile, the next big thing. for me, i think the next big thing is really going to be fully transparent electronics. because diamond is a transparent semiconductor material. it can be married in with metals and you know have the ability to have fully transparent electronics. and so our earlier work in collaborating with national laboratories as well as other universities like the

fabrication facility has been focusing on molecular engineering. actually going to the atomic level. and engineering them to alter the transparency or mechanical properties, so it's been a quite effective demonstration in terms of showing capability of diamond. when we compared to the state of the art silicon market. we see it's not only 1,000 times thinner, but a million times higher. extremely efficient material. this is perhaps five to seven years out. it takes about ten years to bring a ship to market. if we look at the optical and thermal needs, the systems market.

we can bring numerous solutions to much needed problems. within the aerospace market, more efficient. today, we're develop optical windows, more reliable systems which can better detect ballistic signatures, as well as high reliability and efficiency so they can survive battlefield conditions, flight conditions, et cetera. i think for us, nothing speaks more closely to our individual lives than consumer electronics. we all have cell phones. all enjoy using automobiles which connect and won't leave us alone. with a semiconductor, we've been focusing on building a diamond prairie. this has been a public private partnership. as much as i would like to take credit from that name, it came from a senator, melinda bush,

very instrumental with the village and actually having us relocate and headquarter in gurney, illinois. so not only traditional semiconductor labor, but also engineering the new wave of folks to work on materials in competitive labor and manufacturing. the site is the world's first compatible eight inch diamond semiconductor line. no other line is specifically readily insertable into today's marketplace to be able to address and process other materials and as a part of that signifying this, we actually are the recipients of an incentive package as well as the local county and city. we're proud to announce this sum

summer we brought back key elements of motorola's razor team to help bolster this technology. our chief operating officer chief technology officer as well as in addition to others down on the design level. after bringing on this talent, we had to do something exciting. right? so, we announced the third party test results of our diamond on glass technology, this brought the question of the world is can diamond actually provide what we need in consumer electronics. can we have scratch resistant display. more outlets picked up the story. so around 40 to 50 different outlets around the world reported on our third party testing results for diamond on

glass and the speculation was going wild. when are we going to see a diamond screen for cell phone? so i actually thought today for this audience, i would bring the world's first diamond glass screen and show you that not only is it here, it's been productized. and when we do something like this, we don't make this for one unit, we make it for 300 million units. so this technology is here today and actually, the next question after this, this is great, something for a diamond screen or wearable screen. it has much higher -- when your phone is to your face, it's much more cool and so, from 800 times thinner profiles compared to the leading glass competitor, we see over six times harder material. if you checked the paper this is morning, we announced the

world's first diamond glass lens. so, when we talk about the prospect of a diamond, is this material ready for market, we're not only seeing it being deployed in today's military technology system, we're see ng the broad, broad spectrum and it's very exciting because this was not only originated in the labs for the united states, especially developed here, researched to scale, but now brought to pilot production, so i thought this was a very stellar way we could state that innovative science started here. we'll be developed here and we

have to bring it to mass scale. we are proud to be doing this in the midwest. please track our efforts under the diamond. thank you. >> our next panel will explore next generation opportunities at the intersection talent, technology, investment and infrastructure. ladies and gentlemen, please welcome mr. jim bosilli, co-founder new institute of thinking and research in motion, mr. mike -- dr. carol l. fult, chancellor at university of north carolina at chapel hill, and miss nia malika

henderson, senior political reporter, cnn. >> hi, everybody, thanks for being here. it's great to be here. we want to start the four pillars of course talent, infrastructure, investment and technology. want to start talking about talent first. and i'm going to start with you on this one because this is something you've written about. the idea of learnability, the idea of upscaling. what do you mean by that? and what sort of responsibility do you think employers have in terms of that area? >> well, you know, part of this day has been encouraging from the aspect of talent. ever since we began our morning

with the dr. conn, dr. crow, fred smith, everyone has talked about access to scale talent as being an absolutely necessity for our nation to be competitive. actual fact, it is true not only for the u.s. but true for the developed world because labor markets are being affected by an ageing workforce, and developed countries alike. individuals making different choices based on changes in environments and organizations thinking about organizational agility in a very different way, so, all of this translates into a bifurcation of the workforce. i think it was dr. crow who talked about this this morning. out of the u.s. workforce, there's 60, 70% that is fully employable that has the right skills and 30% of our workforce and population that is not

participating, so, the biggest challenge that is facing us to be competitive is going to make sure that we as a nation have access to a broad pool of skilled workforce and we know today that 30% of the workforce has low or is unskilled or does not have enough skills to participate and be successful in a global competitive environment, so, that will be the defining challenge of our generation to figure this out. because as brand talked about during lunch, if it's a very complex structurally driven global issue, there's not going to be a simple answer. because we've known about this and we've seen indicators of our performance in terms of skills compared to our global peers as nations, you know, for quite some time. this is not new. but we have not really been able to make the turn. i would argue the current

trends, the polarization based on the skills they have to contribute to the growth of organizations and to our economy, is going to accelerate and there's no indication that it's going to you know, mitigate or converge at this point. so, that's what's going to be so important for us to figure out. >> and carol, one of the things that's going on, talks about this bifurcation, in terms of the workforce. one of the things that seems to be going on is decline in investment. federal investment. in terms of science. is that a trend you see reversing? has it stalled? where do you see things now? >> i get to start off with good news because just two days ago, congress did pass legislation that was going to increase nih. by about 4.8 million for some important targeted areas. 4 billion and another 4 billion

on an annual bases and i think for all of us, that is good news and we're excited about it. i think that the needs are greater and the opportunities even greater. and i think that's where we start thinking about how can that investment be understood. can we do a better job making clear that if an investment comes back, people have been arguing that we can make sure that that investment isn't only going to help, it's critical. so i think of it being an investment in the workforce. we can probably talk about that more, but universities are places where in these areas of science, technology, that's where the young people get excited. they get the skill sets. we made a bet in america after world war 2, that if we brought innovators into universities where they were also teaching young people, we would create the entrepreneurial mind set necessary to stay great. when the money starts drying up, those people have a harder time doing what they do.

they tend to retrench and not be as they become more risk adverse. they also tend to become less likely to increase the embrace of lots of different areas, so that talent force changes. the idea force changes. so another piece of good news is that it's related to bad news. last year, nih had 50,000 proposals. i'm a reviewer as are many people many this room. at least 25,000 of them had amazing work in them. if you run a business where you're throwing out 25,000 great ideas every year, you have to start wondering about your business model, but if we start increasing that even a bit, we've got people ready so, if the money comes in, we're not in a position where we have a desert of ideas, so, it has that. it has the capacity to really fuel economies and i know all my

colleagues out there could say they have these study, but a little fuel from the government, for example at chapel hill, we did a big study, for every dollar we get from the federal government, we generate 7 to $9 in additional money that goes to fuel research, back to the economy. we hire 100,000 people in the state. so, i mean, i could go on about that, but i think the good news is that should these investments increase, we're ready, the bad news is that if they don't, these pipelines that are holding on could hit a point where it's going to be a lot harder for them to actually take advantage of what is sitting ready if for us as a nation to use. for competitiveness. >> mike, i want to go to you on this. another pillar. infrastructure. done research in terms of manufacturing sector and a lot of emphasis on that. coming in, you have specifically done research on vulnerability.

in terms of cyber attacks. something i hadn't thought of. can you talk about that? >> sure. my voice, i came down with a cold this morning. >> it's kind of sexy. >> very sexy. >> it's a very interesting dynamic because what we're seeing is we're seeing that right now, innovation is the pillar of growth. i really love what bronze said at lunchtime, around the fact that you must be innovative and carol said about the entrepreneurship, but what we're seeing is what happens clearly is the ability that human error, cybersecurity, becomes an open issue with innovation. and the conundrum that any company has you don't want to stifle through innovation and you have to keep going. and especially in the manufacturing sector. as things get more complex, using ecosystems, so you can't

really secure yourself against human error. it does start number one is tone at the top. i think every organization from the board to the executive needs to have cyber security. supporting innovation, but the word i use is a harmonized way. making sure they're sitting back and looking at cyber security procedures. using ecosystems, television really a balance of how do you push while at the same time watching for cyber threats. things are getting more complex, more globalized, using ecosys m

ecosystems, it is a balance of how do you push for innovation while at the same time watching for cyberrisks. >> i wonder if you could talk about america in relation to where other countries are in terms of investment and infrastructure. we talked about sort of this global economy and this global erase towards innovation. where is this country? >> yeah, thank you, and i think i'm going to build a little bit on what fred smith said this morning. and i think as you try to drive your innovation globally, you have to really assess the ecosystem globally that you're going to participate in because that ecosystem determines the capacity to commercialize your ideas globally. and over the last 30 plus years. the primary underpinning of the system that we've used is called trips. the trade-related property system.

underpinning wto, and what was happening through tpp i'm more interested in tips minus. china says i'm more interested in tips minus. i'm not trying to be pejorative, i'm simplifying a little bit. then you have a administration that's saying i don't like trips plus, is that because it's not trips plus plus, or because trips wasn't right and i wanted to look at something else? so this is an uncertain environment to commercialize in. there are rival risks. it's -- i find it highly unlikely they're going to come together in the near term.

so this is a different situation for commercializing globally in the next decade than we've known in the past 30 years. i study these things a fair bit. one study i engage on i should say, one study this which is very interesting for your chair is in ag tech patents, last year, 92% of all ag tech patents from university research were from china. so they published over a million patents. this is a land grab and stay out of the game until you get enough land and come back in. which is rivalist and mercantilist. so i think i personally -- sorry, i personally believe this is the most pressing issue to globalizing right now because the rules systems are diverging and becoming quite political. ed of what's happening in the

election and the royals to the east and to the west. and all of their turbulence and nativisms. so i think this is going to be central to figuring out how we commercialize ideas in the next decade now. >> and, carol, i wonder if you could talk about -- one of the things that the obama administration has tried to do is put a focus on s.t.e.m. education, bringing more women into the field, encouraging girls to go into the field. has that mattered at all? have you seen a difference in terms of conversations around, around that or in terms of interest? >> everyone that is in higher ed spends a lot of time to think about the disparity gaps, the changing demography or we look at the rooms in higher education at the top. most of us look the same.

and many of it look like me and there's fewer that look like a lot of our students. and so we think a lot about bringing them in. i do think even going back to title nine, that's had a big influence in bringing diversity into our infrastructure and our research. a lot of the best examples of the value of diverse research teams actually come from entrepreneurial areas where they talk about, you put six people in a room that all come from the same background, you get the same idea. you put six people with six different ideas. six different backgrounds and you're going to get something that is really dynamic. i think this goes back to me about investment. one of the great ways investment in research -- and i'm talking mostly university research, but it's all research. one of the things it does is it does give us a chance to also address other societal problems. we use that research to develop a diverse team of young people who start fueling as they move up with ideas like the way

obamas did it where you get more and more people. you're going to see the diversity of the ideas and we have a chance. very much to start also reducing those income disparities that go with people thinking that they're limited to disciplines in certain, you know, that women can't do science or students of color can't become engineers. as we erase those boundaries, we start doing immense good not only for the science, the s.t.e.m. that we're doing, but the goal we have to diversify the work force and make the talent pool so much more energetic. i think they go together. >> do you want to jump in? >> not only neigh much more energetic, i think the business, you know, the clear business case is diversity of thought drives better, better business outcomes. the participation of women, depending on where you are in

the world is either lower or significantly lower than that of men, but in almost all of those cases. the level of education for the very same women is higher than it is for men. so if you think about a demographic that is shrinking in all of the developed world, all countries in europe have a shrinking population with one exception, we're just friends. we are holding our own, but within our own country, roughly the same tendencies are occurring depending upon necessity. so our need to bring in skilled talent into the work force is huge and women is actually the biggest untapped pool of skilled talent that is not fully utilized today to varying degrees in developed countries. that's certainly the case. >> and there also seems to be a turn away from globalism and thinking that america is part of this larger economy in terms of immigration and in terms of bringing talent in. do you -- is that going to affect kind of diversity if

there's this shrinking away, jim, from thinking that america -- yeah, is part of this global economy? >> oh, i think there's -- there's without a doubt a talent war, no question, but i think america does exceptionally well because of the quality institutions and the base of their company. so you have a bit of an embarrassment of riches, but of course it can never be good enough. but, you know, how you manifest that, there was a comment from the gallop gentlemen who said there's more business formation and diamondism is going down, so i do think how you manifest all of this into prosperity and productivity, i believe the gating element is much more infrastructure, personally as dr. folz said, there's a lot of talent out and there not the infrastructure to receive it in her case.

so, you know -- i mean that's more in a research thing than in a business formation, but i think it's a pretty good metric. and infrastructure is a very, very important piece to look at. i think they'll build off of things mike talking about the cyber. people are excited about block chain, it's really great because it allows this stuff, but allows people to do things without being tracked. so a lot of these things raise complex issues all along the way. >> yeah, mike. >> one thing when -- the question about s.t.e.m., what we've realized in the business environment is we've been a huge proponent on s.t.e.m. the majority of businesses need science, technology, mathematicians. but we're down into high schools now. we have to start earlier and earlier. we're talking about programs for freshman in high school. we believe that now, you know, when you're taught internships in sophomore years in college,

it's not good enough. we have to start younger. >> we been investing -- that's a big aha. if you speak to the younger generation. people in their 20s who have joined us in the past five, six years. they look at things totally differently than someone my generation looks and they believe you have to start early. you have to start getting those diverse skills, you know, embedded much, much earlier. so we're putting it in program now, looking at as early as freshman and high school now. totally different than when i started. >> yeah. does anybody have questions in the audience? >> yeah, i have maybe something to add to what mike said. when we talked about skill shortages, you know, we survey employers all over the world and also here in the u.s., around their need for talent and whether they think they can find the talent in labor markets. and what we see today is that 40% of the employers we survey here in the u.s. say they have difficulty finding talent. what's encouraging is that

almost 50% of the same employers are now saying that they are investing in training for their work force. where it's the same answer would have been a 20% of employers saying they had a hard time finding people, but only 20% were investing in the development and training. that i think is going to be key -- and it comes back to the question you asked in the very beginning. organizations will have an responsibility and a self-interest in making sure training and development for the work forces that they have. but longer term, we believe that the best predictor of employability may be something we call learnability. the desire and the ability to learn. because we've talked a lot about the changes that are occurring in markets through changes in globalization and the mechanics and the different forces, and it's going to be very difficult for employers and educational institutions to predict what the skills are going to be 18 years out.

they're going to be specifically on the hard skills needed. of course s.t.e.m. skills are always going to be in demand in a digitized world. so the ability to have a work force that is used to acquiring new skills as they go along, will protect us and will render us and make us even more competitive through the time. and we think that's going to be a key driver of employability. we think it can be one of the biggest drivers of competitive advantage if we crack that, we will have a work force that will stay competitive, not only be, you know, in phases competitive and then having to catch up like is the case right now. >> dr. folz. >> one of the ways we talk, we need to develop a whole generation. i love the idea earlier that competitiveness might be measured at a big metric, but it only builds from a lot of individuals.

those are what we used to do the best anywhere. i think that was the real serge in america. if we dry up those pipelines, we really do dry up that inventiveness. so by fuelling it and doing it in such way that would build those partnerships, we actually start every single student and learner has the capacity to be that innovator. that's part of the good news. the investments it takes is actually small. so what is nih's 30 billion -- the health care is 3 trillion. someone said rounding errors. each has the capacity to build these partnerships in ways that can be amazingly transformational for every single individual. to expand this at the rate and speed we want to.

universities have a lot of real estate. we're sharing that with business partners and bring this in. we havthis capacity to do it. i think we're at this moment where a little bit, especially. giving the willingness to reach across the sector seems to be at a point it really could escalate. you know, but it needs that intention that i think meetings like this give us when we come together and talk about it. >> and jim, in terms of what you would want to see. in terms of emphasis and investment and moving forward from the terms of partnerships, what do you to want see and what do you expect to see? >> well, i think rco, debora said it earlier today, that innovation has had unequal distribution elements to it. and so i think you realize when you don't pay attention to that,

it rears itself in surprising fashions and everybody's grappling with that. so i think everybody sold this stuff as trickle defense attorney and everybody would get a fair shake and in fact, it didn't work out that way within states and between states. and i think that's a lot of reason why people are pulling back right now and i'm not trying to just say oh, let's just spread everything to everybody, but i think the intention to the investments and distribution are not just -- it's not a justice thing, but you could make it that case. i think it's a functioning society thing. and so, i think that's really, really important. there's no -- there's no end of possible innovation things. you've heard them all. all today and they're very, very compelling. each and every one of them. i do believe that how this is going to work in the world. you've seen how europe's pulling back. you've seen -- you've seen the

rattling with china. you've seen ttp go up and down and people saying come on, bring it back up again. i think -- i think that's going to gate a lot of this good talent and good desire to invest. and i think the administration is going to be overwhelmed with the things they have to do. so i would say distilling these things into clear priorities could be the thing i would think would be the most constructive thing to do in 2017 with this administration. and that's going to be drinking water from a fire hose and try to get it to a manageable way that you can move ahead on it. >> and mike, what's your sense? >> i actually agree with what jim said. i would say that though his perspective is a challenge between milking innovation and not tieing it to kind of a short term pnl look at it. innovation is long-term. and i think at our firm, i know,

where the challenge is the ability to -- innovation isn't a yearly thing. it could take something five, six, ten years. and you have to -- if you get behind something, you have to stick with it. there is opportunities at times the market changes, financial changes. to your point, you have to be able to call something, if it is not going to work, it is not going to work. everything that is innovative doesn't mean it is going to work. sometimes we are very shortsighted. >> i would love to say something about that. one of the way the universities have a different model is we have to invest in the discovery-based long term. so big example, zika virus.

we would be nowhere on zika virus had we not had researchers studying all sorts of things that had nothing to do with zika virus. when it comes up, the 10 individuals across the country who had been working on that is were there. another example, this whole movement towards complete rethinking in transform medicine may have started 30 years ago by someone who was actually looking at viruses and bacteria. it didn't look like anything. but it took 30 years, and sudden isly we are on the cusp of the biggest invention. i'm really glad you said that. we need to make sure that research is wonderful. we can do great things with it. but it all dries up if we don't continue the basic research. i really appreciate that too. >> what about you in terms of a new administration, encouraging them to focus on what exactly in terms of innovation. >> as we think about the areas that could drive tremendous

growth in investments and infrastructure, reduction of regulation, and of course making the labor markets competitive and also ease of growth in terms of companies. their ability to track talent. the key issue is going to be reskilling and upskilling those in the workforce so they can continue to evolve. right now our employment is 4.6%. we can argue about the workforce participation rate, which is lower than the recession. give 2%. regardless of which we are following a number of hallmarks of a tight labor market. certainly slack. some are under employed. some left the workforce. but the ones that are under employed and that are outside of the workforce probably at this point don't have the skills to actively and easily participate in a lot of the things that

strong growth could generate. but i think that's going to be a systemic approach both -- and i know the panel after us is going to talk about education and the need for education in the long term. but certainly in the short-term, to deploy a lot of people to infrastructure projects is going to be challenging. speaking to a number of companies that are involved in big infrastructure projects, their biggest problem is finding infrastructure engineers. that is going to be the reality of hitting into this shortage of talent that can realize so many of those things. my hope and optimism would be a structural and systemic approach around really reskilling the american workforce. a skills revolution is what we are hoping for. we think that truly can drive our competitiveness to untold heights not only in the short-term but in the medium and

certainly the long term. >> any questions out there? there we go. >> hi. i'm from the college of engineer at texas a&m university. i have a question for people who come from industry. as we invest resources in programs to educate engineering undergraduates for innovation and what we call the mind-set of entrepreneur, what are the two things you believe are the most important things in knowledge and skills that we should be focusing on? thank you. >> who wants to the take that? >> we are probably all working on that same thing. the skills of learning when you have hit a wall, how do you develop the synthesis.

>> i would say i think you used the term the inquisitive the mind. what we are looking for now as students is even if you come to a firm like ours and think you know what to do, have the ability to say in two years i may use that skill but do something different. the difference is, coming in, when i joined the firm, you kind of had a career path of 10 years. you knew what you wanted to do in 10 years. now we want the students to almost make two-year commitments. innovation is moving so quickly that we don't want to lock them in for something. we want two year commitments. it's almost this multiyear commitment to continue learning.

>> it is the hard skills and soft skills. access to knowledge is ubiquitous. hard knowledge can be acquired. experience can be leapfrogged because you have access to an understanding at a much more rapid pace today. so this notion of transferability of skills between industries and between various aspects with what you do with an organization is going to be increasingly important. >> jim,you want to jump in? >> you are certain -- you are trying to insert yourself into a value team which all has their own marginal production costs. that is an extraordinary contended exercise. so people who have these sophisticated s.t.e.m. skills, if they can marry them with the

navigational skills which are very different than traditional economy, that's gold. you know people who do that well because they have extraordinarily valuable tech companies. that's the dance you do. anyone who brings those to an organization while they're on the c suite, they are in the c suite quicker than anybody else. >> everybody knows the young generation are the most excited about doing this. i walk down the hall and meet students who started their first company in their first year and already talking about the second, third and fourth companies they're going to start. that is another part of the hopeful part, when we give them the tiniest part, they are ready for that. but i think they want to know what it takes to do that. and they need to have the chance to have a risk fail, risk fail and be successful. so we've got the material. and the opportunity. so we just have to get those double -- what was it? t squared, i squared.

>> on that note, which is very hopeful, we are going to end. and we thank you guys for your questions and your attention. >> thank you. [ applause ] >> to address the nations skills gap and how to better prepare americans to join the 21st century workforce on, ladies and gentlemen, please welcome the president of northeastern university, dr. joseph e. ayun and president of northrop grumman, mr. wes bush. >> hello, wes. >> good afternoon, everyone. and i would like to start by thanking the council of competitiveness because you brought us together. we are old buddies now. we have been doing this for some time. wes was at northeastern

university and we had a dialogue. we want to talk about the skills gap. we have tons of surveys to share with you. the surveys are an indication. they don't provide you with a solution. let's start by discussing some of the surveys at the business roundtable has been doing. give us flavor, wes, of what you found out. >> the business roundtable found a survey of its members. not surprising because they are similar to what the chamber had done, as well as other nonbusiness organizations and i would say there are some elements you could predict. but there are also some interesting insights. some of the more predictable were the number of companies in our case is greater than 80% which cited a significant skill

shortage. and their ability to find the talent they need and to support the business objectives they had. and not surprisingly as well, much of that skill shortage goes to the s.t.e.m. disciplines. just about every survey you see, you get that flavor and s.t.e.m. is a big category. we often think of the engineering part of it. but the math and basic science were identified as shortages as well. in addition to the disciplines, though, some of the other feedback that we got in the survey that i thought was particularly insightful was the identification of some broader sort of general applied skills from a business perspective we all look for and we try and keep track of how well we're doing. things like critical thinking, the ability to tackle a problem and really dive into it and test a lot of different perspectives

and come up with innovative and different perspectives. cognitive flexibility was another category we saw identified by many, many businesses. again, i think as a reflection of the pace of change that we have in the business environment, in fact, in the world around us. so it was for me a confirming survey of many other things that i'm seeing in either surveys. but it was insightful in areas that i don't think it quite got the attention. >> we just surveyed the college students nationwide. what we found is that only 14% of the students feel they are ready for the new world. for the ai world, for intelligence systems, for the tech revolution that they know is going to hit them. you know, they know that the

know the jobs are going to be redefined. so it is interesting to compare employers and at the same time the learners. the employers can saying, you know, colleges and universities are not doing a good job. the college students, only 14% feel that they are getting ready for that. starting with you, wes, you have been partnering with universities. we have been partnering with universities. what do you look for in a partnership? >> there's been a model out there a long time that business is utilized and working with universities. i think there has been a broader awakening that we need to develop very, very different models. the older model was sort of a combination of building good partnerships with the career

office because we want to make sure we're there and well and branded well when it comes to the recruiting. but sponsoring research and development was sort of a traditional model. and oftentimes it was just straight old philanthropic giving. which is good. all those things are really good. >> we like it too. >> and it is important we continue to do those things. but we all realized it's just not enough. it is is not solving the problems that we're seeing. and i have to give a lot of credit to the business higher education forum. we are members and have been for some time. a number of years ago, through a series of discussions just like this where we continue to identify these types of problems, we decided to pilot some different approaches and test what would work and what would not work. and we have found some models and we have applied it now both in the fields of cyber security and in the field of data analytics in a number of university settings around the country. and to your question about what

are we looking for, what works? first off, you have to have a partnership approach and it has to work both ways. the university has to be open to engaging in a little bit of a different manner. and business has to be open to changing its model of engagement. what's been working in these new models has been a much deeper level of collaboration. it goes all the way in many cases to the co-development of curriculum. business makes an investment. the university makes an investment. faculty comes together to define what some of the components need to be to better prepare the students. now, this isn't a training program. and i want to be careful about that up front. oftentimes people hear this and think, okay, we are turning university into training. and that is not the intent at all. it has to be education and it has to be broad education.

directly to the point you're raising, regarding feedback from students, we want students not just trained for the one instant thing coming into business. we want them to work for us over a lifetime and continue to grow. that said, there are some basic things they need today to get started that perhaps they did not need some years ago. and this model of engaging more closely around the notion of developing curriculum. how we do internships and co-op. northeastern is from my perspective the world leader in defining how to have co-op programs be most effective. but engaging in the design and development. oh, by the way, business has to step up and work together with the university so that these things are supportable. none of these things are inexpensive. so it is a little bit of a broader awakening across the business community that we can't simply stand by and conduct our surveys and complain.

we need to be engaged and be a part of the solution. is and we look for universities like northeastern that are eager to partner and are eager to help us learn about what works and what doesn't work. because universities like northeastern bring so much to that engagement. >> thank you, wes. when i talk to my colleagues in higher education, it is clearly there is a big unease. we don't want you to come and talk to us about how to shape the curriculum. >> right. >> however, at the same time, when we get together with our employers and we sit down, we have 3,000 employers working with us. it's because we send our students for six months and long-term internships called co-ops. when we look at the type of person they're looking for, it is clear we have to change the way we are doing it, how we are providing education.

what we are hearing from our employees is very simple. we need you to get our learners, our students ready for the new economy. what does it mean? we all know about it. they need to know coding. coding will become like typewriting. >> i guess. >> they need to know beyond the tech literacy. tech analytics. big data. they need to know about human interaction, human literacy. and you are here as leaders. you didn't become leaders because you are great engineers only. >> that does help, by the way, though. >> especially for you, wes. you knew how to motivate people, how to understand people. that's what we're not doing well enough of.

the second aspect that i want to discuss is that i am afraid that we in higher education are giving up an enormous opportunity. we are in the middle of an enormous revolution. there are new jobs that are coming other jobs are becoming obsolete. and people have to retool. people have to define what they do. the notion of lifelong learning is with us. now, higher education looks at lifelong learning as something very peripheral. we don't want to touch it much because we want to focus on the 18 to 22, undergrads. we want to do research and ph.d. but don't talk to me about lifelong learning. you know, this will bring down the brand. in fact, we are becoming the railway industry. i hope no one here is from amtrak. the railway industry missed the

transportation revolution because they defined themselves as being in the railway industry and not the transportation industry. and i think that's what's happening to us in higher education. we are not thinking of ourselves as being in lifelong learning mission. so when i talk to you, wes, i ask you, you have employees. you are recruiting employees. you cannot say to them you is accept once and for all. so what do you look for? you must have extensive training, correct? >> absolutely. >> to have them retool, but i have to tell you, every time a company tells me that they have set up an educational program is a failure of higher education. >> well, let me say a couple of things. one, most companies don't want to be in the education business. that's not what we do as our

primary business. but most of us are. in fact, in the survey that we did in the business roundtable on average across the companies that we surveyed, on average companies were spending $80 million apiece on continuous education, much of which were internal investments because they didn't have these partnerships. they didn't have this capacity to work with the universities on this continuous lifelong training. so we look for universities that have that flexibility to the deal with beyond the 22-year-old age point or ph.d. age point and engage with us in the development of programs that our employees can benefit from. despite what may sound like a criticism of higher education, let me say up front i want a strong believer in the united states we continue to have the very best higher education system that exists in the world.

so what we are talking about here is improving something that's great, but we have to improve it. because our needs for this, whether we're talking about the economic security of our company or the national security of our country we critically depend on the quality of higher education and the engagement of higher education. so these partnerships really are opportunities for us to connect in a deeper way and more meaningful way. and as a real opportunity not just company level. it comes down to the employee level. this means a great deal to employees. >> when we start talking about those partnerships and those opportunities, it led us to rethink our own model. for instance, when you work with people for are long on experience and short on time, namely professionals already in the field, you cannot tell them come and spend two years with me. no one has the time. so universities have to move into the short what some people

call the boot camps. actually, you know what happens, is there are companies that start boot camps in coding. why are they doing that? because there is an enormous need. now the need will be fulfilled. i think we were one of first universities to have done it, because we had to learn, if you want to meet the need, you have to meet it based on the terms of the company or the people who want to learn about that. come here for a certain time. you know, whether you are in the company or whether you are with us, it doesn't matter. but you don't have time. we're going to provide it around eight weeks. is similarly, you know, we have

to device a new curricula. when you have to the sit down and go over curricula, forget about it. that is unacceptable. however, we have to do it because we have to the learn what the needs are. for instance, we have an enormous shortage of our data analytics, cyber security. you and i discussed that. computer science. so can-can we create new pipelines for computer science. we sat down with companies in seattle. amazon and others. and then we took students who finished a b.s. degree and they give them long-term co-ops, those internships. and we gave them a masters in computer science over the period where they are there. they are coming with a background in physics, math, economics. for us we have to relearn. so a masters in x doesn't require a b.a. in the same field. so it is a learning process.

i agree with you, wes. we have the best educational system in the nation. because we have it, we cannot be complacent. >> i think there is another dimension that goes to the heart of the pace of the technology and the pace of business growth that we all expect to see and want to the see as we go forward. and that's around innovation and the way we approach that from an educational perspective. long gone are the days when innovation was the product of single individual. most enterprises today, i think this occurs in universities as well, it is the product of groups of people coming together. one thing that universities have been doing well for some period of time is working hard to develop that teamwork approach as students come through university. but as we see folks progress into business and into the work

environment, oftentimes the captions copyright national cable satellite corp. 2008 captioning performed by vitac