Speaker 1: This is Bloomberg Business Week. I'm Carol Masser and I'm
Speaker 1: Jason Kelly. We're here every day bringing you the latest
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Speaker 1: Business Week on iTunes, SoundCloud, or Bloomberg dot com. You
Speaker 1: can also listen to our radio show weekdays at two
Speaker 1: pm Eastern only on Bloomberg Radio. Yeah, we do want
Speaker 1: to talk about startups. We want to talk about a
Speaker 1: lot of things, science and innovation and entrepreneurship, all at
Speaker 1: work at the New Jersey Innovation Institute and adventures link
Speaker 1: here with more on the work that n j i
Speaker 1: T is doing to really facilitate the startups coming out
Speaker 1: of it into the real world. Dr Don Sebastian, he's
Speaker 1: president of n j i T New Jersey Innovation Institute
Speaker 1: and he's here with us at nj i T at
Speaker 1: their Newark campus. So nice to talk with you. I
Speaker 1: told you I was reading about your zation a little
Speaker 1: bit last night, tell us a little bit about for
Speaker 1: our audience kind of some of the work you're doing.
Speaker 1: Sure so. Nji is is an unusual organization where a
Speaker 1: nonprofit created under the university and and the expression of
Speaker 1: the university's economic development mission, meaning what we're a tech university,
Speaker 1: how do we help build a tech based economy? And
Speaker 1: having spent many years at this interface between university and industry,
Speaker 1: as they say in the commercial, we know a lot
Speaker 1: of things because we've seen a lot of things. There
Speaker 1: are a lot of models that just don't work when
Speaker 1: we try to graft academic research onto the needs of industry,
Speaker 1: and so we've arrived at a model that really focuses
Speaker 1: on how can we begin together bring together companies that
Speaker 1: are birds of a feather, small companies, startups, entrepreneurs, faculty students,
Speaker 1: whatever the source of the innovation is in technology specific
Speaker 1: clusters and help them not just grow with specialized facilities
Speaker 1: and coaching, but really make early stage matches between the
Speaker 1: big companies who need them now as a source of innovation.
Speaker 1: We all grew up in the era of large scale
Speaker 1: corporate R and D, and all the great technology we
Speaker 1: know came out of Bell Labs and Sarnoff, R C
Speaker 1: A Labs E C, R and D. They go through
Speaker 1: the whole catalog of industry. Those enterprises have to the
Speaker 1: large case atrophied or even disappeared completely. And M and
Speaker 1: A has replaced R and D in many, many industrial sectors.
Speaker 1: But then that's an inefficient process, you know, it's not
Speaker 1: like every tech these days can be done in the garage,
Speaker 1: and you do, well, wonder what's lost in the process
Speaker 1: with all of that R and D at those big
Speaker 1: facilities going away. Someone's going to do it right, right,
Speaker 1: all right, And if you're depending on the small guy
Speaker 1: to do it, there's only so much you can do.
Speaker 1: Apps in your basement and then you can, you do
Speaker 1: do some simple stuff, but when you get into nanotechnology,
Speaker 1: gene splicing, you know, AI, advanced AI and robotics, you
Speaker 1: can't do that as a one or two person operation
Speaker 1: in a garage. Well. Well, one of the things that
Speaker 1: we're obviously focused on throughout the course of this entire show,
Speaker 1: in our visit here is the future of work, in
Speaker 1: the future of jobs, but so much of that feels
Speaker 1: like from your perspective, needs to be proactive rather than reactive.
Speaker 1: You need to be helping sort of create companies, but
Speaker 1: also certain types of companies and cultures that that sort
Speaker 1: of dictate or help sort of shape the future of work, right, yeah, yeah,
Speaker 1: And if we don't do it, guess what the rest
Speaker 1: of the world is organized. Right, So, whether it's China
Speaker 1: Dot Com or it's the front offer models in Germany,
Speaker 1: there are other places in which there are very well
Speaker 1: oiled public private partnerships that try to help small, mid
Speaker 1: size and merging businesses come together and ultimately connect to
Speaker 1: the big O E M s and and bring products
Speaker 1: to market. So for every one company that maybe the
Speaker 1: next Apple that does start in the garage, they're probably
Speaker 1: a thousand who have a better destiny if they were
Speaker 1: to develop into some product that could be brought by
Speaker 1: a larger company or be part of a supply chain done.
Speaker 1: I think so much of this and startups is about
Speaker 1: future growth for this country, right, And if you take it,
Speaker 1: you know, certainly future growth globally if you take it
Speaker 1: on a mobile perspective. But I do think about so
Speaker 1: where is the US when it comes to being leading
Speaker 1: as startups? I mean, I think everybody for so long
Speaker 1: were so jealous of Silicon Valley, but I feel like
Speaker 1: China certainly on a mission, and there are other parts
Speaker 1: of the world too, So where is the US in
Speaker 1: that standard? So I just came back from a weak
Speaker 1: trade mission that the state sponsored Israel startup Nation, Yeah, oh,
Speaker 1: he is a place from innovation size of New Jersey
Speaker 1: and you look at the volume of startups to go there.
Speaker 1: So I think what's more important is how do we
Speaker 1: get them to the next phase, right from startup into
Speaker 1: something that can be functionally A startup is a business plan,
Speaker 1: angel investment at least, but what about actually producing enough
Speaker 1: for proof of concept? Doesn't make technical sense, but doesn't
Speaker 1: make dollars and sense. How do you get into that
Speaker 1: pilot stage? That's the big barrier for many of these
Speaker 1: small companies. If you have a thick drug, for example,
Speaker 1: a new pharmaceutical, if the big company says, well, come
Speaker 1: back when you've had clinical trials, we'll phase three clinical trials.
Speaker 1: That could be a ten year hald and even a
Speaker 1: multi billion dollar investment. Right, So what are we doing
Speaker 1: about a don Yeah? Well, so in each important industrial sector,
Speaker 1: we're trying to put together these expensive facilities. I use
Speaker 1: cell engine for example. We've invested in creating a pilot
Speaker 1: manufacturing facility as sterile manufacturing is called cGMP. We're inventors
Speaker 1: of these next generation of cart and gene spicing type
Speaker 1: technologies can come and create produce UH clinical trial arts.
Speaker 1: Right and and at the same time the big companies
Speaker 1: are coming for us. Tax is the same thing, right,
Speaker 1: because these are pivots. This is another important thing. Most
Speaker 1: of our anchor industries are facing true disruptive technology threats
Speaker 1: and either they're going to figure out how to become
Speaker 1: their own disruptor or they're going to go the way
Speaker 1: of the gas company. When when Edison strung up electric
Speaker 1: lights just got about a minute left. So what's a
Speaker 1: success story. So so this this model is emerging. I
Speaker 1: think in healthcare I T space really wonderful example where
Speaker 1: we begin in this transformation to digital health. About ten
Speaker 1: years ago when UH the Affordable Care Act created funding
Speaker 1: to create the transformation of doctors from paper to electronic
Speaker 1: medical records and the technology to interconnect. In that context,
Speaker 1: we transformed seven thousand physicians here in the state and
Speaker 1: then went on to show she's a hundred and seventy
Speaker 1: five million a year in cost savings by using that
Speaker 1: technology to achieve outcomes driven healthcare delivery. Now we run
Speaker 1: the state's healthcare information exchange and with that that's attracted right,
Speaker 1: So that's the honey that attracted bears. Yeah. We brought
Speaker 1: in a lot of small companies who want to plug
Speaker 1: into that infrastructure, and we've shown that we can then
Speaker 1: do the business coaching specific to the industry that's helped
Speaker 1: them grow as as small enterprises into thriving companies. All right,
Speaker 1: thank you so much for joining us and for having
Speaker 1: us here in Nework, doctor Don Sebastian, president of the
Speaker 1: New Jersey Innovation Institute here on the campus of n
Speaker 1: j I T n j I. I think I might
Speaker 1: have sent in, well, the president g I D will
Speaker 1: get angry about violence they find a pink slip in
Speaker 1: a novel. Thanks so much for the opportunity to talk
Speaker 1: technology and innovation. Man, they're impacting just about everything in
Speaker 1: our world, whether at home, at work, and at play.
Speaker 1: At work is one that is garnering more attention thanks
Speaker 1: to a lot of different technologies. And someone who knows
Speaker 1: about that as Robert co and he's vice president of
Speaker 1: Global R and D in Chief Technology Officer at Striker
Speaker 1: Joint Replacement graduate of n j I t UH and
Speaker 1: so we want to bring him in and talk a
Speaker 1: little bit about how innovations are changing how we work.
Speaker 1: He's joining us on site here at nj I t
Speaker 1: Nice to see you again. Oh thanks for having me
Speaker 1: in a proud Yeah, this like old home week? Are
Speaker 1: you like sort of like you know, walking through me
Speaker 1: like I remember that place, picking up some T shirts
Speaker 1: and sweatshirts, no comments. So I feel like there's more
Speaker 1: momentum when it comes to technology innovation impacting the work
Speaker 1: for his workforce. And I don't know whether it's because
Speaker 1: all of a sudden AI is picking up some speed.
Speaker 1: Tell me how you see well, actually between AI, between
Speaker 1: connectivity if you really look at at a division that
Speaker 1: I represent, like a striker where we do total hips
Speaker 1: and total needs. You know, we're trying to still to
Speaker 1: improve patient outcomes, make patients return to work faster, have
Speaker 1: patients leave an operating room, manage expectations, patient satisfied, remove
Speaker 1: their offstere arthritis, but they get them back to a
Speaker 1: normal level of functions. So innovation needs to be strong.
Speaker 1: And we're living in a global world right now, and
Speaker 1: that works for R and D as well. So and
Speaker 1: necessary for R and D globally, like it's going to
Speaker 1: be a global take, does it not? Oh? Absolutely? If
Speaker 1: you look at the innovation across the United States, by
Speaker 1: the way, where you have a geography difference, you go
Speaker 1: to go to where the talent is. So whether it's
Speaker 1: in Australia, whether it's in Japan, whether it's in Europe.
Speaker 1: It's really the combination. And as you look for this
Speaker 1: technology and you look at where the people are who
Speaker 1: are smart, the universities that that dwell upon this, you
Speaker 1: want to go where they are. You want to connectivity
Speaker 1: and connectivity will allow a rate of innovation that incorporates
Speaker 1: that technology. And so does that change not just how
Speaker 1: you hire, but also once people are on board sort
Speaker 1: of how they work where they are Like with play
Speaker 1: play it out for us, right, So if you're to
Speaker 1: go after let's say a new technology, so let's use
Speaker 1: your your augmented reality example, right, artificial intelligence. There are universities,
Speaker 1: by the way, such as nj I T that that
Speaker 1: focus on that. Now that labor force may be local
Speaker 1: to that college. For me to say, hey, labor force, uh,
Speaker 1: you're a university in Germany, you come to Northern Bergen County,
Speaker 1: New Jersey. The likelihood of that may not be all
Speaker 1: that great, But if you really think about it, why
Speaker 1: can't people feel that they're all working together? Why can't
Speaker 1: through video conferencing, through augmented reality, through all the computer
Speaker 1: simulation and that power that can merge people together in
Speaker 1: ways that never could before. Well, I think about the
Speaker 1: medical community. So does that mean I mean maybe we're
Speaker 1: already doing it, that you could have an expert surgeon
Speaker 1: in Australia who operates robotically possibly on somebody in New York.
Speaker 1: I mean, can we get you know, I don't know
Speaker 1: if it's there yet. Is that where we're going? Yeah, well,
Speaker 1: maybe the world gets there eventually, but but I don't
Speaker 1: think we're there right now. So we're not practicing medicine.
Speaker 1: So we will get more data. But the purpose right
Speaker 1: now of a company like Striker to gain more data
Speaker 1: is to make that surgeon smarter about that patient. The
Speaker 1: more data we can help give that surgeon on that
Speaker 1: individual patient that's unique to that patient, we will win.
Speaker 1: But the data can come from many places. So why
Speaker 1: don't we look at, say, say large medical centers that
Speaker 1: are well known, and why don't we capture the way
Speaker 1: they do worthpedic surgery. Why don't we learn from those surgeons,
Speaker 1: their technique, their approach, where they place an implant, how
Speaker 1: they do physical therapy, when their patients go back to work,
Speaker 1: what's their rehab procedure. And now we could track patients
Speaker 1: through artificial intelligence, through data like never before. And that
Speaker 1: means the pool of patients right gets bigger, right because
Speaker 1: you can share information with everybody who's doing a particular
Speaker 1: procedure or dealing with a certain implant. Correct. Well, So
Speaker 1: it's a striker with robotic surgery if you really think
Speaker 1: about it. We're sitting here now and we're analyzing CT
Speaker 1: scans on last year over a hundred twenty thousand patients,
Speaker 1: and we're checking checking to see what their operative condition
Speaker 1: was when they returned to work, what their pharmaceutical use was,
Speaker 1: very patient satisfaction. You can out pool data in massive
Speaker 1: quantities that you never could before. Stratify that. So let
Speaker 1: me give you an example. If you're a sixty four
Speaker 1: year old woman and your b m I of thirty
Speaker 1: four rheumatory darthritis, what's the best implant for you? Now
Speaker 1: we can help answer that question. Should you go to
Speaker 1: a hospital home from the hospital same day, or should
Speaker 1: you stay in the hospital for four days? What is
Speaker 1: your expectation for when you return to work? When will
Speaker 1: you walk upstairs better? When we get up a car better?
Speaker 1: All right, so let's talk about in the minute or
Speaker 1: so we have left, let's talk about the patient side
Speaker 1: of this, because a lot of people listening watching, they're
Speaker 1: probably your current customers or future customers. Let's be honest,
Speaker 1: like this is something I hang out with a bunch
Speaker 1: of runners, and you know we're of a certain age,
Speaker 1: and like, this is the sort of thing that you
Speaker 1: know is very relevant to folks going forward. Tell us
Speaker 1: about the market out there right now. So the market
Speaker 1: right now, the patient's expectations have changed so much in
Speaker 1: the last ten years. No longer do people not want
Speaker 1: to play golf. No longer do they not want to
Speaker 1: walk in No longer they want to have have pain
Speaker 1: and be staying home six months after surgery. They want
Speaker 1: to be able to walk faster, they want to return
Speaker 1: to a normal sense of quality of life. That's a
Speaker 1: higher and higher expectations. Robotic assistant surgery allows us to
Speaker 1: do that. But eventually we will learn in the hundreds
Speaker 1: and hundreds of thousands of patients across the globe with
Speaker 1: digital health and be able to look at that data
Speaker 1: and make recommendations on patient care and implants like never before.
Speaker 1: Customization to right, It's exciting, it's exciting stuff. Um, thank you,
Speaker 1: thank you so much to come by you. Are you
Speaker 1: thinking about like a knee replacement? Yeah, yeah, but I
Speaker 1: just I'm looking down the road. You can have the road.
Speaker 1: Want to keep running? All right? Robert Cohen, Chieftain, technology
Speaker 1: officer of the Joint Replacement Division over at Striker And
Speaker 1: as he pointed out, produm of this fine institution. All right,
Speaker 1: our next guest. We love talking to him. And if
Speaker 1: you're talking about science and technology, he's gotta be talking to.
Speaker 1: Dean Kennedy is the founder of First for Inspiration and
Speaker 1: Recognition of Science and Technology, joining us on the phone
Speaker 1: from Manchester, New Hampshire. Dean, Carol and I were talking
Speaker 1: before we came on about the last time you visit
Speaker 1: us in New York City. You brought that amazing the
Speaker 1: rugged terrain robotic wheelchair. It was so cool, so great
Speaker 1: to catch up with you. It's great to be back
Speaker 1: with you. And since I saw you last we delivered
Speaker 1: for those machines to a couple of our a few
Speaker 1: incredible Americans, including Medal of Honor recipients that left their
Speaker 1: legs in places like Afghanistan and Iraq and one of
Speaker 1: the early one in Vietnam, and we're changing their lives
Speaker 1: and it's great. That's amazing. Congratulations. Well, we look forward
Speaker 1: to catching up for you next time you're in New
Speaker 1: York City. But let's talk about STEM education right now.
Speaker 1: That's the core of everything we're talking about. When we
Speaker 1: think about the future of work, it starts with education.
Speaker 1: Tell us what you are working on right now in
Speaker 1: that will soon sort of be making its way through
Speaker 1: the educational system. So there's two paths for that. In
Speaker 1: my day job, as you know, I build medical equipment.
Speaker 1: And we just received, believe it or not, another grant
Speaker 1: in excess of fifty million dollars from Health and Human
Speaker 1: Services to accelerate the pace at which we're building the
Speaker 1: core technologies to manufacture replacement human organs, which would be
Speaker 1: a huge wind for patients that need chronic care like
Speaker 1: dialysis because the kidneys don't work, or insulin pumps because
Speaker 1: they are pancreas doesn't work, and since I do pumps
Speaker 1: and dialysis machines, I can't wait to put myself out
Speaker 1: of all those businesses by manufacturing the organs to replace
Speaker 1: replace them. But by the way, the theme here is
Speaker 1: I already have eight hundred engineers on all these projects,
Speaker 1: and my little company has got a hundred open positions,
Speaker 1: so as you know, everything, but my day job consumes
Speaker 1: first and uh and at first, we're trying to create
Speaker 1: the next generation of the workforce that will solve the
Speaker 1: problems we're all worried about today. Whether it's manufacturing organs,
Speaker 1: solving the healthcare system, solving the global warming issues with
Speaker 1: better ways to make use, transports, store energy, you name it.
Speaker 1: There are almost an unlimited number of incredibly important problems
Speaker 1: that need to be solved. They all need to be
Speaker 1: solved by a generation of people that have better technologies
Speaker 1: than the one we're leaving them with. And the only
Speaker 1: way we're going to get there is to dramatically increase
Speaker 1: the number of kids that have the skill sets and
Speaker 1: the ambition and the judgment and the courage to go
Speaker 1: and do bold new things with technology to solve these problems.
Speaker 1: I can also tell you go ahead, no no, no,
Speaker 1: please finish, Please finish. I was gonna say that I
Speaker 1: listened to some I must say, I don't want to
Speaker 1: insult anybody, but some silly people that seems to think
Speaker 1: there's a credible debate about whether science and technology and
Speaker 1: engineering and robotics are going to eliminate jobs. I wonder
Speaker 1: if those people are around, you know, a hundred years
Speaker 1: ago and two hundred years ago, when the steam engine
Speaker 1: came around, or when the first you know, uh, you
Speaker 1: know bulldoz who was built saying, oh my god, that
Speaker 1: Bulldoz that can do the job of a hundred ditch diggers.
Speaker 1: That machine is gonna put everybody out of work. Well,
Speaker 1: actually it'll take work away from the people that are
Speaker 1: doing backbreaking work now will have a limited time in
Speaker 1: their life to do it. It's not a fun job.
Speaker 1: It's a dangerous job at the boring job at a
Speaker 1: low paying up. But the idea that the the caterpillar,
Speaker 1: that the Bulldoz who would do the work of all
Speaker 1: the van bag figgers, and there would there'd be no
Speaker 1: work for them. No, once you raise the bar and
Speaker 1: you can make that many more holes, you can move
Speaker 1: that much more stuff, you just build super highways, not
Speaker 1: just little houses, and every single technology ever developed creates
Speaker 1: way more jobs than eliminates because it creates way more
Speaker 1: opportunities for everybody to share a better standard of living.
Speaker 1: Dean just got about forty seconds. We are sitting or
Speaker 1: at n J I T. I'm Jason, and I are
Speaker 1: in a room full of students who are studying engineering, science, technology.
Speaker 1: Given that six students entering school today will work in
Speaker 1: jobs that don't currently currently exist, you got forty seconds.
Speaker 1: What's your advice to these students. My advice to them
Speaker 1: is to get about learning what's in the textbook today
Speaker 1: about solving today's problems. By the time they graduate, those
Speaker 1: problems will be solved. But don't worry. There'll be new, better,
Speaker 1: more exciting problems that have more pressing needs to be solved.
Speaker 1: The world is moving so quickly now that educator from
Speaker 1: the has to be preparing you to learn how to
Speaker 1: learn and relearn and stay current. And kids that have
Speaker 1: those skill sets will never have a shortage of opportunities
Speaker 1: and careers. But kids that don't learn how to learn
Speaker 1: and don't learn how to embrace technology are going to
Speaker 1: be under the bus on it period. Be nimble. That's
Speaker 1: what's important. Dean came in. Thank you so much, founder
Speaker 1: of First the Robotics competitions that he does to encourage girls,
Speaker 1: boys at all ages to be involved in STEM is
Speaker 1: just remarkable, really wonderful to see. You're listening to Bloomberg
Speaker 1: Business Week with Carol Masser and Jason Kelly on Bloomberg Radio. Yes, indeed, everyone,
Speaker 1: this is a special hour of Bloomberg Business Week in
Speaker 1: the next sixty minutes live from n j i T,
Speaker 1: New Jersey Institute of Technology. We are also streaming on YouTube,
Speaker 1: and we're focusing on the future of work because there's
Speaker 1: so many different things going on, and I think a
Speaker 1: lot of folks were filled with a room of student
Speaker 1: here at n j i T wondering about, you know,
Speaker 1: what will work look like, what kind of jobs will
Speaker 1: be needed? And our guests for the hour Marcus Weldon,
Speaker 1: he's president of Bell Labs and corporate Chief Technology Officer
Speaker 1: and Nokia. Also Virginie Mallard, who is head of Corporate
Speaker 1: Technology for the US at the German engineering and manufacturing
Speaker 1: giant you know them, Semens. She also heads up the
Speaker 1: global research activities of Semens, Head of Technology, Field, Simulation
Speaker 1: and Digital twin. I had to actually look up and
Speaker 1: understand which digital twin is one of the coolest things
Speaker 1: that we're going to talk about. Love love this, Love
Speaker 1: this and Joe Millitichi's senior vice president of R and
Speaker 1: D at Mark former senior vice president of R and
Speaker 1: D at embdin. So what's really wonderful about this panel
Speaker 1: up here is that they're looking at technology innovation what
Speaker 1: it means for the workforce in some different perspectives. So
Speaker 1: first up, what I just say, I'm also excited to
Speaker 1: have all these students in the room because they're going
Speaker 1: to keep us honest, Like you know, we're gonna look
Speaker 1: out and see if they're paying attention or not, and
Speaker 1: if it gets boring, they're gonna flag and they're gonna
Speaker 1: start waving their hands the more interesting and more interesting.
Speaker 1: Um No, it's gonna be very interesting. And I want
Speaker 1: to start with I think talking about the technologies that
Speaker 1: really are front and center for you and you know, Marcus,
Speaker 1: let me start with you, um what are the technologies
Speaker 1: that you guys are really spending a lot of time
Speaker 1: on knowing that it's going to change your industry and
Speaker 1: potentially change the types of jobs you're going to need
Speaker 1: in the future. That's a great question. I mean, we
Speaker 1: were in a weird business because we're in the networking business.
Speaker 1: So to some extent, our job is to connect all
Speaker 1: the technologies, and because of the way things become interconnected,
Speaker 1: we have a role in all of them. So the
Speaker 1: digital twin concept we talked about earlier, we think about
Speaker 1: how to create digital twins. Why would we do that
Speaker 1: because that seems like more of a semens thing. But
Speaker 1: of course part of digital twinning is getting the information
Speaker 1: in and out of that digital twin over a network.
Speaker 1: And then the outcome of digital twin is to move
Speaker 1: a robot, So we have to think about robot moving.
Speaker 1: And it's all because we're sort of the fabric company,
Speaker 1: if you like. I think it's very new Jersey to
Speaker 1: be in fabrics. But with the networking, we're the networking fabric.
Speaker 1: And that's five G. You've had a lot about five
Speaker 1: G from everyone. The current waiting, we're waiting waiting waiting,
Speaker 1: not waiting as long as if as when it was
Speaker 1: LTU because it's faster download speeds. That's my that's my
Speaker 1: five G joke. But the effect, but no, the next
Speaker 1: version of five G is all about industrials. So that's
Speaker 1: the thing that people don't realize is five G today
Speaker 1: is about faster consumer. But the next version has lots
Speaker 1: of features built in for industrials, so it becomes the
Speaker 1: fabric of industrials, which then allows you to digital twin
Speaker 1: and control robots and and control things remotely and do
Speaker 1: remote teaching and and and instruction and all sorts of
Speaker 1: interesting things. For us, we see ourselves as building fabric
Speaker 1: technologies connect to all the other technologies. So we are
Speaker 1: thinking robotics, we are thinking AI, we do think five G.
Speaker 1: We think all sorts of interesting thoughts and invent at
Speaker 1: bell Lapps. All right, So one of the other things
Speaker 1: New Jersey is known for is the pharmacy lital business.
Speaker 1: We're going to get to that in just a second,
Speaker 1: but I don't want to get too far from this
Speaker 1: concept of digital digital twins. This is probably something that
Speaker 1: the students are like, yeah, we know what that is,
Speaker 1: but I don't know as much as do you know
Speaker 1: what it is? Educating here? All right, tell us what
Speaker 1: it is. I don't know why. I was pretty sure
Speaker 1: you will ask the question. She's ready. I have a
Speaker 1: short version, very simple is the digital twin is a
Speaker 1: virtual replica of a of a physical phenomena or physical
Speaker 1: set of machine or process. That is a very simple definition.
Speaker 1: Now beyond of that physically is to connect the physics
Speaker 1: to to the to the simulation and to interact each other.
Speaker 1: For example, with a model, you can predict and you
Speaker 1: can simulate, and you can send this information to the
Speaker 1: machine and the machine can collect some data for example
Speaker 1: with sen source right and saying this information to the simulation,
Speaker 1: and the full concept all similar. They're telling me, put
Speaker 1: put the machine. Consider to your mouth. So I'm gonna
Speaker 1: be I'm going to be not quite that digital twin,
Speaker 1: but I want to move in it because we want
Speaker 1: to hear what you're saying. Go ahead. So, as a
Speaker 1: as a conclusion, that digital twin is the full concept
Speaker 1: of physical set the machine, for example, and it is
Speaker 1: a virtual replica the model or the simulation associated to
Speaker 1: the machine, and they interact each other, sending for example,
Speaker 1: predicted data to the machine and machine sending a measured
Speaker 1: data to the simulation. But Virginia, I have to say,
Speaker 1: my version of digital twin is of the entire physical world. Yeah,
Speaker 1: so you would see your world like a game. Yeah,
Speaker 1: So if you think of it as a massive game
Speaker 1: world that you enter, but it's actually your physical world,
Speaker 1: and you can explore it and you can ask questions
Speaker 1: of it because it has all the answers, and then
Speaker 1: you can experiment with what if right, because you can
Speaker 1: ask the digital twin to simulate a scenario. Which is
Speaker 1: why Siemens and others you know, really like this is
Speaker 1: you can explore conditions that otherwise we destroy the physical thing,
Speaker 1: and so you can do very interesting things. But for
Speaker 1: the students here, it's sort of like a big game
Speaker 1: but of the real world. That's I think how I
Speaker 1: think of the twins. So what is interesting in in
Speaker 1: Sements it is, you know, it's a old company of
Speaker 1: one android seventy plus. Your old company well well known
Speaker 1: in industrial manufacturing and more recently is also a big
Speaker 1: player in a software UH provider. And that's why what
Speaker 1: is interesting in Sements. We have this knowledge of manufacturing
Speaker 1: and the machines and process and we have also the
Speaker 1: simulation and the software right availabel, and now we are
Speaker 1: able to connect and to combine the two physical and
Speaker 1: virtual world to to propose a new tools. You are
Speaker 1: listening to Bloomberg Business Week at special edition here live
Speaker 1: in Newark at n J. I T I want to
Speaker 1: jump right back in with Joe Militich. He's over at
Speaker 1: Murk relatively new job. I think, for you, what's the
Speaker 1: coolest technology you're looking at right now? There are a
Speaker 1: lot of them, so that it is a hard choice,
Speaker 1: but I'll but I'll give you one. So the Nobel
Speaker 1: Prize was given for chemistry and for bio catalysis, which
Speaker 1: is so okay. So first of all, um, when we
Speaker 1: we look for we look for ways that you can
Speaker 1: modulate human disease with with drugs, with new medicines. A
Speaker 1: lot of times are chemicals. They're made synthetically. But the
Speaker 1: more complex molecule we want to make, the harder it
Speaker 1: is to put together, because most chemistry actually can make
Speaker 1: two or three different kinds of the same molecule and
Speaker 1: then you have to sort them all out at the end.
Speaker 1: It's a big purification process. But but inside the human body,
Speaker 1: inside all living things, we have enzymes, catalysts. These are
Speaker 1: proteins mostly a few exceptions, but mostly proteins that actually
Speaker 1: bring things together and then make the thing you want
Speaker 1: out of them. And they do it with very little waste,
Speaker 1: and they do it at high efficiency, and they're catalytic.
Speaker 1: They do it over and over it again. So what
Speaker 1: we've been able to do recently is make much more
Speaker 1: complicated chemical structures but use bio catalysis. We've been able
Speaker 1: to invent enzymes that never existed before because of a
Speaker 1: convergence of many technologies that make it possible for us
Speaker 1: to actually start with a certain kind of enzyme and
Speaker 1: change it into something we wanted to do specifically for
Speaker 1: a specific reaction. It's amazing. So twenty seconds. So what
Speaker 1: does that mean in terms of our world. It means
Speaker 1: that we can invent better medicines faster, and we can
Speaker 1: make them cheaper, and we can make them greener with
Speaker 1: very little waste, very little, very little impact on the environment.
Speaker 1: So it's very important, and I was thinking a win
Speaker 1: win on so many different levels right everywhere. To see that,
Speaker 1: you are listening to a special edition of Bloomberg Business
Speaker 1: Week Live from nj I T here in Newark. We're
Speaker 1: having a conversation about the future of work, and part
Speaker 1: of understanding the future of work is understanding where science
Speaker 1: is going, what the jobs are going to be, and
Speaker 1: what the aspirations are for this next generation of technology.
Speaker 1: Joe Militage, I want to put this question to you.
Speaker 1: You have the senior VP over at R and of
Speaker 1: R and d over Mark uh local company, and I
Speaker 1: do wonder what's going on in the world in terms
Speaker 1: of disease biology. We're talking about this during a break
Speaker 1: and I'm so intrigued by what that actually means. So
Speaker 1: I've been a student of human disease biology from my
Speaker 1: whole career, and the essential problem we have is we
Speaker 1: want to understand what goes wrong when people develop a disease,
Speaker 1: and then we want to figure out something we can
Speaker 1: do to modulate that, some medicine or some vaccine we
Speaker 1: can give that will modulate the human disease. But the
Speaker 1: problem is we don't know as much as we would
Speaker 1: like to know. I can tell you during my career
Speaker 1: we know three order of magnitude more about human biology
Speaker 1: than we did at the start. And it's not even
Speaker 1: a tenth of a tenth of a tenth of a
Speaker 1: percent of enough. We're incredible that old. Uh, You're right,
Speaker 1: I'm not. You're only as old as you feel, so
Speaker 1: I'm not old at all. Um. But what here's here's
Speaker 1: the exciting part. The the exciting part is because of
Speaker 1: a convergence of many different things, we can now it's
Speaker 1: now possible to study human disease biology with a resolution
Speaker 1: and with a continuity that's never before been imaginable. Now
Speaker 1: we haven't cashed in on it yet, but you can
Speaker 1: feel it coming. So think about it. In the past,
Speaker 1: if we want to know something about a human disease,
Speaker 1: we relied on a patient going to a health care
Speaker 1: provider and telling them once a month or once a
Speaker 1: week about Now you can know everything continuously. If you
Speaker 1: do it ethically and if you do it in a
Speaker 1: in an informed way, you can understand not what a
Speaker 1: disease looks like at a doctor's visit every few weeks
Speaker 1: or months, you can understand it what's going on, can
Speaker 1: genuously what the patterns look like. If you want to
Speaker 1: actually take a sample from a patient with consent, of course,
Speaker 1: and if you want to analyze it, you can analyze
Speaker 1: it with a depth of resolution, down to finding out
Speaker 1: what's going on in single cells inside each tissue. You
Speaker 1: can understand it with a depth and complexity that was
Speaker 1: never imaginable, even just even just a decade ago. I
Speaker 1: have to think this is something you're seeing Virgin that
Speaker 1: you know because of the the equipment and and all
Speaker 1: the research that you guys are doing. I can't tell
Speaker 1: exactly the same story. But in the factory, for example,
Speaker 1: the robots and the artificial intelligence are bringing to us
Speaker 1: more safety, safety environment, are your quality maybe sometime quick
Speaker 1: quick execution of the task. And at the same time
Speaker 1: the human will be dedicated to elevated the task. They
Speaker 1: will be maybe in charge of the logistic programming the robots.
Speaker 1: That's why the segmentation of the task in factor will
Speaker 1: will be different in the future. But definitely the robots
Speaker 1: and the AI are going to bring us higher quality
Speaker 1: and at the same time giving the human the possibility
Speaker 1: to have elevated roles. Well, this is what's interesting, and Marcus,
Speaker 1: I want you to come in on this because I
Speaker 1: feel like we've written about this a lot in Business
Speaker 1: Week magazine, this whole idea of it's not robots taking
Speaker 1: over for humans, but you're going to see man and
Speaker 1: machine kind of working much more closely than ever before.
Speaker 1: Well said, that was actually my punchline. Sorry touched that collaboration. Yes,
Speaker 1: so there's a what we look at this a lot
Speaker 1: of you of the future of work is it's man
Speaker 1: and machine, a woman and machine in perfect harmony, and
Speaker 1: digital twining is a way to create a harmony between
Speaker 1: them because think of it, the machine, the software system
Speaker 1: or the AI system has a view of the world.
Speaker 1: The human has the same view of the world, and
Speaker 1: they can interact in that world. That's the point of
Speaker 1: a digital t when they can sort of experiment and
Speaker 1: interact with each other. So that perfect harmony does a
Speaker 1: bunch of really interesting things. It increases productivity because if
Speaker 1: you think about what our problem is today, and we've
Speaker 1: eventuled these great technologies, but to some extent, they distract
Speaker 1: us more than they help us. Meaning what we are
Speaker 1: deluged by data that you don't know what to do with,
Speaker 1: or social media or reality TV not Bloomberg. That's that's credible, positive,
Speaker 1: high quality and just life enhancing. There's a lot of
Speaker 1: static out there, static and the static actually we don't
Speaker 1: we're not equipped as humans to deal with. So you
Speaker 1: can think of the role of the machines is actually
Speaker 1: to help us, you know, wade through that static and
Speaker 1: that morass of data to create knowledge and understanding that
Speaker 1: we use to perform tasks more efficiently. And the key
Speaker 1: is we perform the task because humans are actually incredibly
Speaker 1: well adapted for physical world tasks. We have lived in
Speaker 1: the physical world. We know how it works, We know
Speaker 1: how to manipulate things much better machines. For all the
Speaker 1: very clever robots you see out there on YouTube, they
Speaker 1: have been highly optimized to do humanlike things, but the
Speaker 1: human was already doing that thing. So our view is
Speaker 1: that it's about augmenting humans. And you can think of
Speaker 1: a robot that you can control is your extension AI system,
Speaker 1: is your extension of your brain. All those things allow
Speaker 1: us to be better versions of ourselves that will actually
Speaker 1: work fewer hours but more productively, and normally, more productively
Speaker 1: means higher wages. Oddly enough, so a fewer hours, higher
Speaker 1: wages means more leisure time. Leisure time you tend to
Speaker 1: do things that are cognitive and cause growth, and that
Speaker 1: makes you a better worker. So we've got this very
Speaker 1: positive feedback loop we see of humans when they're augmented
Speaker 1: actually work more productively in similar jobs that have been
Speaker 1: adapted by a roll of machine takes well and Joe,
Speaker 1: I mean, we do get this sense and we're talking
Speaker 1: um you know with the series Executive and Striker earlier. Uh,
Speaker 1: this notion that machines can also you know, prevent humans
Speaker 1: from making misstakes. Absolutely, so we can if it just
Speaker 1: got about thirty seconds. Okay, if you look at the
Speaker 1: pharmaceutical industry, we need our factories to be more modern
Speaker 1: than they Yeah, and that's eminently possible now for all
Speaker 1: the reasons that have been described and more. There's a
Speaker 1: convergence of all the things we've learned about what we
Speaker 1: want to control, that we can make things tenser, safer, smaller,
Speaker 1: more productive, more unit productivity for time. All Right, you
Speaker 1: guys are gonna stick with us? Yes, I was looking
Speaker 1: at definitely. I think human and machines collaborating each other
Speaker 1: and the complimenting each other. You're listening to Bloomberg Business
Speaker 1: Week Karl Master along with Jason Kelly. We're live in
Speaker 1: front of a room full of students here at n
Speaker 1: j I T at their campus in Newark, New Jersey.
Speaker 1: We have a great panel. Marcus Weldon is President of
Speaker 1: Bell Labs, corporate chief Technology officer at Nokia. Virginie my
Speaker 1: Art she has head of Corporate Technology for the US
Speaker 1: at Semens, and then we have Joe Military Chief Senior
Speaker 1: vice president of R and D at MURK. So here
Speaker 1: we've been talking about some of the different technologies, whether
Speaker 1: it's five G, whether it's AI, digital twins, UM. You know,
Speaker 1: what does that mean for the type of workers that
Speaker 1: are going to be needed in the future. So Marcus,
Speaker 1: let me start with you. What do you what do
Speaker 1: you look for when you want to hire somebody? Super
Speaker 1: smart people? Uh so n G I T grants you
Speaker 1: qualify that. What we actually look for is UM people
Speaker 1: are willing to adapt to changing realities. So one of
Speaker 1: the things we really think is that the role of
Speaker 1: digital twins and augmentation and intelligent assistants will be to
Speaker 1: help you do whatever it is you do better. But
Speaker 1: therefore you will be expected to do more things. So
Speaker 1: instead of getting an education that is linear like I did,
Speaker 1: and then I go and do a job and I
Speaker 1: do that job forever, I think you'll be expected to
Speaker 1: be adaptive, maybe on a weekly or maybe even daily basis,
Speaker 1: because you'll be augmented with the task will be taught
Speaker 1: to you or sort of on the fly, either because
Speaker 1: you put a headset on or somewhere you're augmented and
Speaker 1: you'll be able to do many more things because you'll
Speaker 1: learn those things on the fly with the information you need,
Speaker 1: rather having to be pre trained on that thing. So
Speaker 1: you're gonna have to sort of be agile and adapted.
Speaker 1: But that sounds like an awful lot of fun. As
Speaker 1: Joe said that, my job will be to be adapted
Speaker 1: to any changing reality and I'll be well paid for that. Yes,
Speaker 1: go ahead, Yes, incments. We are looking also for smart people.
Speaker 1: But we also believe in the diversity of people. Could
Speaker 1: you just stand up. I just want to know who
Speaker 1: that is. Just believe it. In the diversity of education. Yes,
Speaker 1: we believe that in different paths of education for example
Speaker 1: apprenticeship or community college, or also people coming back to
Speaker 1: education after having another experience in their life, and it
Speaker 1: could they could bring to us and experience we need.
Speaker 1: In very good point, I love this idea of diversity,
Speaker 1: and you know, until come on in on this, because
Speaker 1: I do think we increasingly understand that a company performs
Speaker 1: better when their boards are diversified, their senior talent and
Speaker 1: really all along in terms of their workforce. So tell
Speaker 1: me how that is important to you, guys, and what
Speaker 1: else you're looking for. So I'll just echo the sentiments
Speaker 1: on diversity. But what I think I'd really like to
Speaker 1: reinforce is the comment about the fact that we can't
Speaker 1: think of education the same way. It's going to be
Speaker 1: continuous and forever, so you can't. We have lots of
Speaker 1: different skill sets we depend on to discover and invent
Speaker 1: and develop a new drug and get it to market.
Speaker 1: They used to be in silos. You just you'd be
Speaker 1: a specialist you'd get good at So you need a
Speaker 1: hundred different specialties. We still need those, We still need
Speaker 1: that depth of expertise, but we also have to have
Speaker 1: people who can understand across the whole spectrum and integrate it,
Speaker 1: because if you don't integrate it, you don't see the
Speaker 1: opportunities when convergence if possible. I agree that you really
Speaker 1: have to really really push on that, and that's where
Speaker 1: diversity comes in for us exactly. It's a spectrum function.
Speaker 1: The more spectrum of disciplines and genders and nationalities and
Speaker 1: cultures and educational backgrounds, broader spectrum to look at the problem,
Speaker 1: all equally able to sort of solve it because they
Speaker 1: helped in the way they need to be helped. It's
Speaker 1: diversity sort of happens as a catalyst for all of this,
Speaker 1: I think, I think it's really good. And the thing
Speaker 1: that I think is the most important thing is just
Speaker 1: being intellectually curious, relentlessly curious about how everything works, everything
Speaker 1: that's everything that could touch what you tell. I would
Speaker 1: say that about journalism. I think it's just you have
Speaker 1: to be curious about the world and stuff. Go ahead, Yes,
Speaker 1: intimates where we believe in the in the education program
Speaker 1: for our workforce in the US, we have a fifties
Speaker 1: thousand US employees and we spend fifty million every year
Speaker 1: to in education program to train them and to to
Speaker 1: reskill them in the new technologies. This has been and
Speaker 1: that's interesting to go ahead, No, but I think there's
Speaker 1: been a debate about what's the corporate responsibility and re
Speaker 1: educating the workforce to make sure that they have the workers.
Speaker 1: And it sounds like obviously semens as being important. Yeah,
Speaker 1: we do too. But I think in the for the
Speaker 1: students in the room, what I would say is they
Speaker 1: will be live trained. And that's what's the really interesting change.
Speaker 1: Because today you have to take courses in a rather
Speaker 1: formalized way, even though their online, there's still sort of courses,
Speaker 1: But what if I could learn the task minutes before
Speaker 1: I have to perform it? So I think that's the
Speaker 1: really interesting change in the future, and it will be
Speaker 1: perfect knowledge, not the noise we were talking about. I mean,
Speaker 1: I do wonder about in thirty seconds sort of the
Speaker 1: delivery system to some extent of education. Right, Well, certainly
Speaker 1: it needs to be real world in real time. But
Speaker 1: there's another big component we need, and that's that there's
Speaker 1: a lot of challenge. So we look at data sets
Speaker 1: that are as diverse as you can possibly imagine, and
Speaker 1: they're not in common formats. So we need a We
Speaker 1: need a whole coundry of data scientists too, who can
Speaker 1: work with biologists and worth chemists and with you know,
Speaker 1: microbiologists with toxic common language, you know. But but they
Speaker 1: have to be able to actually get to the data
Speaker 1: because putting it in a data lake isn't good enough.
Speaker 1: We are here at n j I T. Marcus Weldon,
Speaker 1: Virginie Maard and Joe Militage still with us, and I
Speaker 1: want to quickly pick up on this theme of sort
Speaker 1: of diversity of thought. But how you get there, Joe, Like,
Speaker 1: how do you institute that sort of thing or how
Speaker 1: do you train people to to think like that? I
Speaker 1: think you have to create the right environment, the right
Speaker 1: work environment. It involves everything from facilities, to who you hire,
Speaker 1: to what you make accessible. But you know it's working
Speaker 1: when people are so excited because they're learning new things
Speaker 1: and they feel that they're going to have an impact,
Speaker 1: you know you've got it. And and it's it's not
Speaker 1: it's not something you can necessarily make perfectly formulaic. But
Speaker 1: when people are learning, they tell you. When people stop
Speaker 1: stop tell telling you that they're working long hours, and
Speaker 1: they tell you that they can't wait to get to work.
Speaker 1: That's when you know you have to have that kind
Speaker 1: of a learning environment all the time. So how do
Speaker 1: you institute At semens, we we strongly believe that the
Speaker 1: diversity brings value to the company. It's about the competitivity.
Speaker 1: If you play a soccer game with five players, you
Speaker 1: have less chances than with eleven players. That's why we
Speaker 1: have to include all the people out of the game
Speaker 1: today and to propot them some education program to join
Speaker 1: us and to bring the experience the background right. And
Speaker 1: it's it's about the diversity or so of the mindset.
Speaker 1: And Marcus just thirty seconds here we are completely background
Speaker 1: blind oddly enough, meaning it really is if if you
Speaker 1: have the enthusiasm, the curiosity like you take care of
Speaker 1: UH and UH, a thirst for new knowledge, the rest
Speaker 1: just happens, right because it's like you said, visionally, we
Speaker 1: look at the largest population people who fit that criteria,
Speaker 1: and that naturally is everyone. So we never limited by
Speaker 1: any category. UH, it's all categories in to be the
Speaker 1: most sort of thriving population. You are listening to Bloomberg
Speaker 1: this week live from m j I T. It's a
Speaker 1: special edition. We're focusing on the future of work. Our
Speaker 1: guest Joe Militich. He has senior vice president of R
Speaker 1: and D at Mark Virginny Major. She is the head
Speaker 1: of Corporate Technology for the US at Siemens and Marcus Wilton,
Speaker 1: President Bell Labs in corporate Chief Technology Officer at Nokia.
Speaker 1: We had a great question from the audience here, one
Speaker 1: of the students posing this to to the panel. We
Speaker 1: talk a lot about AI and automation. We talk a
Speaker 1: lot about sort of being intellectually curious, but we do worry.
Speaker 1: I think we should worry about those who are left
Speaker 1: behind to some extent, who might not have the capability
Speaker 1: of the opportunity to play at that at that higher level.
Speaker 1: What do you make of that, Virginia. I like this
Speaker 1: question because it makes me the opportunity to to tell
Speaker 1: you that sometimes you can overcome this uh this point,
Speaker 1: we have, for example, instruments low code platform called a
Speaker 1: Mendis were quite or two years ago, and this platform
Speaker 1: allow you to create apps without knowing how to code it.
Speaker 1: It's you have just to know maybe how to solve
Speaker 1: a problem, how to have a common sense, and then
Speaker 1: the platform is coding for you and create the app
Speaker 1: for you. And this is an example of how we
Speaker 1: can interiorate this kind of workforce breaking to us an
Speaker 1: experience from the from the shop floor with a with
Speaker 1: a good technical knowledge without knowing how to code. We
Speaker 1: like this Coostin. I think the excellent question because actually
Speaker 1: one of the great equalizers of AI and augmentation is
Speaker 1: it augments the people who know less, perhaps more than
Speaker 1: augments the people who know more. So it's actually meant
Speaker 1: to level the playing field so everyone can do their
Speaker 1: task whatever it is better. And in fact the toss
Speaker 1: the hardest to replicate with a machine of physical toss.
Speaker 1: So I would argue What it does is in the future,
Speaker 1: physical task performance will be more human augmented with an
Speaker 1: assistant that tells you what you need to know. Even
Speaker 1: if you didn't know the math or the engineering, it'll
Speaker 1: be telling you how to do it in a way
Speaker 1: that helps you. You may have had the form of education,
Speaker 1: so I think it's a it's a really bright future
Speaker 1: for leveling things. Well, does it also mean then going forward,
Speaker 1: that you don't have to know so much math, are
Speaker 1: so much science going forward? That would be a huge
Speaker 1: rely for me. But I do wonder about that. So
Speaker 1: I think it will augmented because because whatever level you
Speaker 1: start at, you can get ten times better in a
Speaker 1: much shorter period of time. And there's almost no limit
Speaker 1: of questions that I can think to ask. So I
Speaker 1: don't see the future getting limited. The only thing is
Speaker 1: going to limit us is whether or not we can
Speaker 1: sustated economically at all. That But it's not actually a
Speaker 1: technical or a scientific limitation anymore. The future is unbounded.
Speaker 1: I mean why everywhere? What also a level? If you
Speaker 1: level an bounded which is sort of really interesting. Well,
Speaker 1: and I just think about something as silly as Siri
Speaker 1: or some of the go home devices, right, that you
Speaker 1: can ask so much information because there's so much data
Speaker 1: fed into it. Think about, you know, how much you
Speaker 1: can know automatically and what you can do with it.
Speaker 1: Remember we had to look stuff up in books, remember encyclopedias,
Speaker 1: to a library, go to a library, or pick up
Speaker 1: a phone or something like that. All right, So in
Speaker 1: a few minutes that we have left, you know, we
Speaker 1: also want to talk about especially since we're at the
Speaker 1: top university that's obviously thinking very aggressively and ambitiously, and
Speaker 1: yet we have an educational system that maybe might be
Speaker 1: a little sclerotic, as they say, and not so quick
Speaker 1: to change. What's the piece of advice that you guys
Speaker 1: would give to universities or higher education institutions out there?
Speaker 1: And I think that and the great question was how
Speaker 1: can industry and education partner to create these lifelong partnerships
Speaker 1: that are going to be needed in terms of education.
Speaker 1: It's a great to question. I think we saw Dr
Speaker 1: Bloom earlier saying a lot of really good things about
Speaker 1: maker spaces and makerspaces in generally will be involving types
Speaker 1: of equipment industrials will be using. So I think collaborations
Speaker 1: between places of ng I t and industry are more
Speaker 1: naturally happening because the types of equipment used to be
Speaker 1: massive and industrial. Now you can because of course More's law,
Speaker 1: you can now get in a small form factor. You
Speaker 1: can have an university, and then it's just a case
Speaker 1: of coupling the two by some programs. We have summer internships.
Speaker 1: We hire a lot of graduates from the New Jersey area,
Speaker 1: but they've been working on systems and machines and tools
Speaker 1: that we would also use. But do you see sort
Speaker 1: of institutions sort of separating a little bit in the
Speaker 1: sense that like, if you can't keep up, if you
Speaker 1: can't be as progressive, maybe you're not gonna exist. But
Speaker 1: but I think the most important thing is to teach
Speaker 1: students how to ask questions. Yeah, that's the most important thing.
Speaker 1: How to problem solve, What are the right questions to ask?
Speaker 1: How do you actually delve in and to and really
Speaker 1: to actually gain enough confidence doing that so that you're
Speaker 1: not afraid and so that it doesn't seem intimidating, because
Speaker 1: the tools will be there to get whatever information whatever
Speaker 1: is possible. And then when you don't find the information right,
Speaker 1: you know what you want to work on because that's
Speaker 1: where you've got to add value to the system. Ask
Speaker 1: the question, keep asking, you get the answer exactly. And
Speaker 1: so I think the major job of universities is actually
Speaker 1: teaching people that you can be curious, now much more
Speaker 1: curious than you ever could fairy well, but maybe we've
Speaker 1: been a bit linear book knowledge. But we have to
Speaker 1: turn knowledge into curiosity again. I think I think that
Speaker 1: the partnership between universities and companies are very important because
Speaker 1: we've benefited each other from the academic knowledge, of course,
Speaker 1: but the company can bring to the to the college
Speaker 1: and high school also kind of understanding of what we need.
Speaker 1: And for example, sements provide us some software to the
Speaker 1: high school to teach the kids right and to and
Speaker 1: to show them what they can do with the software
Speaker 1: and how to design the parts. And we provide also
Speaker 1: some equipment right. And that's what's interesting. You're finding it's
Speaker 1: starting at younger and younger ages that you want to
Speaker 1: get into UM education and certainly have an impact. Folks,
Speaker 1: thank you so much. I mean, we certainly could have
Speaker 1: continued for a much much much longer time. So I
Speaker 1: just want to thank our guests here on the panel.
Speaker 1: Marcus Weldon, President of Bell Labs, Corporate Chief Technology Officer
Speaker 1: at Nokia, Virginie my Yard, head of Corporate Tech over
Speaker 1: for the US at Siemens, and then Joe Millitan, she's
Speaker 1: Senior VP of R and D at Mark. So thank
Speaker 1: you both so much, and thank you to our audience
Speaker 1: as well. Really appreciate it. Thanks for listening to Bloomberg
Speaker 1: Business Week. You can subscribe to the podcast on iTunes, SoundCloud,
Speaker 1: or Bloomberg dot com. You can also listen to our
Speaker 1: radio show every weekday at two pm Eastern only on
Speaker 1: Bloomberg Radio