Where Technology and (a Better) Society Intersect
welcome i'm terry kramer faculty director of the easton technology management center and i'd like to welcome you to this special event the future of innovation working across boundaries for transformative societal outcomes now we live in a world today that's got huge opportunities but also huge challenges in almost every sector there's an important leadership call to action to understand society's greatest problems and to identify solutions to resource organizations appropriately and ultimately to lead in a way that creates value for all stakeholders whether that be shareholders customers employees and society tonight's program is a great example of the spirit of collective effort which is essential to success this program exemplifies an invaluable partnership between the anderson school and the greater ucla community our many students faculty and alumni who are committed to innovation and advancements in healthcare and sustainability i'd like to specially acknowledge the los angeles department of water and power rayton ucla's institute for carbon management the ucla sustainable la grande challenge and ucla health for their generous sponsorship of this innovation challenge i'd also like to thank ucla anderson's dean tony bernardo for his continued support of this very important cross-campus initiative and all the partners we have worked with across campus that helped us share this opportunity with their students now i hope you learned from this program and it encourages all of you to think about innovation opportunities that can be transformative in society and the many learnings that come along with it specifically tonight we have two objectives first is to share with you latest areas of technology-based innovation and their importance with a special focus on robotics health care and sustainability our second goal is to highlight the goals and three winning teams from this year's easton center innovation challenge now in terms of specifics we're going to begin with a fireside chat with nan bowden co of everyday robots a learning robot moonshot at alphabet that was born at x the moonshot factory she'll describe the latest areas of innovation with everyday robots and their impact not just on individuals but impact on enterprises and society this conversation then will be followed by an overview of our innovation challenge and we'll hear quick pitches from the winning teams followed by q a so i hope you find these discussions insightful and invaluable in your own leadership journey now as i mentioned i can't think of a better keynote speaker than nan bowden chief operating officer at everyday robots a learning robot moonshot at alphabet that was born at x the moonshot factory nan's got a very impressive background she joined google in 2013 via an acquisition into google's data center division where she handled various strategic initiatives as well as several mergers and acquisitions at google she spent her career working at the strategic intersection of technology and business she helped found and scale google's cloud global technology partners team which developed hundreds of technology partnerships including google cloud's foundational partnerships with sap cisco and salesforce prior to google she had a 19-year career at miracom which is a caltech spin-off that was a pioneer in high-performance computer networking she started as a software engineer and later moved into business roles such as evp cfo member of miracom's board and ultimately ceo she earned her phd and master's degrees in computer science from caltech her phd research runtime systems for fine-grained multi-computers led her directly into her work at miracom where she wrote the operating system that controlled the company's first products she received her bachelor's degree in applied mathematics from university of alabama and is a proud ucla anderson alum now for today's session i'm going to ask nan a variety of questions that gets her view on a variety of issues and then we'll go to slido for a moderated q a the slido event code is easton1 the number one so just go to slidoslido.com and you can either enter in your own question or upvote an existing one and again as a reminder the event code is easton and the number one so before i uh start out with my conversation with nan we'd like to show you a brief video that'll give you just a window into everyday robots robots today are still struggling with doing the most basic things the reality of robotics is that picking up a cup of a table if a robot could do that in any environment it was in kind of sitting next to us that almost requires a nobel prize it's that hard if we rewind prior to the mid 70s mainframes were big very expensive machines that required scientists to operate them they weren't really accessible to everyone then the microprocessor was invented and all sudden we had the beginning of the personal computer evolution it's called a chip computers are the future they're everywhere because they're useful they're doing things your home computer to read the day's newspaper well it's not as far-fetched as it may seem they became these general-purpose machines that could do multiple things and eventually the smartphones that we carry around with us everywhere today something very similar is happening in robotics we've had mainframe robotics or industrial robotics for 20 30 40 years and i think we're now on the cusp of transitioning into everyday robots what we are ultimately doing are building machines that can live and operate among humans one day our goal is to create a platform that enables lots of different people to program and teach these robots to do lots of different things we know that that's gonna just have a huge multiplicative effect where the robots are out there in the world doing things that we never could have imagined and helping people that's the goal i think robots can add a tremendous amount of value to society they'll work alongside us they'll be our partners that's not where robots are today robots are very simple machines can barely move around without bumping into things hey robot let's go for a walk let's go so now it's basically in this uh it's probably not the best thing um oh okay okay okay okay okay all right that is bad we should definitely cut that out there's this uh this thing called morvik's paradox that states that in artificial intelligence the hard things are easy and the easy things are hard basic motor control perception you know navigating a crowd at a baseball game or something like that these things are not actually easy they're easy for us because they have to be otherwise we wouldn't survive so evolution has prepared us over millions of years to be good at the things that are essential to our survival our brains weren't built to play chess but they're so flexible and so capable that we can sort of shoehorn them into this weird problem and get them to do uh you know planning and algebra and so on and it takes us a lot of effort for machines they can do algebra and math out of the box but the things that are intuitive things that are common sense those we have to actually help them do and that's been one of the biggest challenges in robotics nan what a great video you know starting out you know with the complexity of what you're trying to pull off against the upside of kind of the gain and impact and the idea of machines being right next to humans so first of all just a big welcome it's great uh great to have you here great thank you terry i've been very much looking forward to it and seeing you and having a great conversation about the innovations well you know let me start out because you know listening to your background introducing you and kind of talking about your ceo role at miracom and then going to google cloud and leading all these global partnerships and now you know chief operating officer on everyday robots just tell us a little bit about the leadership journey how did you get from place to place what were the challenges opportunities as you as you moved along well first of all i just i'm very grateful for these opportunities i think it's been quite a journey and i've really enjoyed each of those chapters i think they've each led to the next one i think from a leadership journey perspective each of them um brought a challenge uh that was more about what kind of impact can can i have can this overall enterprise have how can we make that impact larger um and you know particularly once once i got to alphabet into google you know the scale at which uh google and alphabet operate you know just scaling you know both yourself and your your impact in your project is just a huge challenge no matter whether it's in a startup or it's an you know a company like alphabet so i think that the overall thing in my leadership journey has been you know trying to follow a vector of impact um and also trying to make sure that i'm living the values that are they're really important making sure that impact is for better of my community you know my employer you know the world and i think that's that's one of the great things that i i feel very fortunate i've had the opportunity to do that in a bunch of different environments yeah and nana it's a very interesting idea about scaling your impact how do you do that how do you kind of think about am i really having impact or is it just kind of in my head that i think i'm having it versus really affecting you know others and organizations around you yeah i think a lot of it is being open and listening to feedback um you know really inviting real feedback not the people telling you how great you are but uh here's how you could have more impact here's a way that maybe i haven't seen a perspective that others can see you know and i think that when you have a culture of open transparency and and feedback in your organization you can you can hear those things which are sometimes hard to hear but you can also be like okay well maybe i should think about that and let me see if i can i can explore that you know and have a have a mindset of experimentation um and try things right just that's one of the the great things about some of the leadership training that i've had has been in those kind of leadership labs you know where you're trying something new and seeing how it works so i think that that applies when you're looking for more impact in your roles excellent and so why don't we dive in now because we're talking about now the innovation and the impact of your impact um tell us about the everyday robots project and you know if you want to start out with a state of the union give us the broad landscape about what's happening what are the offerings all those good things yeah well i i'm excited about it i can tell you some of it i can't tell you all of it but uh the parts i can say is that we have had a public launch last november which one that was much more open about what the project is doing um and in fact you can you can see some of our robots having left the la as we call it left the lab and operating inside commercial spaces inside alphabet so that our website everydayrobots.com has got some beautiful pictures and videos that you can really get a sense about what we're up to um but net net it's we've been bringing out the robots and teaching them services um things that they can do to help uh with everyday tasks so like right now as i mentioned they're in commercial spaces they're doing things like sorting trash uh they're doing things like wiping tables cleaning cafes you know so all of these tasks are um important to understand that they are learned they are not scripted they they're not programmed in a way like industrial robots uh have been and so when you talk to roboticists a lot of times you you i mean if you if you're in the robotics game you think well robots have been around a long time but those robots are typically bolted to the floor they're in some kind of um very controlled environment they're in some kind of perhaps um tele-opt you know where there's an operator who's operating every bit of it when you start saying like no in an unstructured environment you know like an office building like a home like a like in outdoors you know those kinds of unstructured environments are so complex that they cannot be scripted and programmed um some people say that the kind of robotics challenge that we're working on is like self-driving cars it's at that level of complexity but the car's not been invented and there are no roads you know so you're like well wait a minute that's that's even that's a really really complex problem so in part you know thinking about when you're getting into like business strategies or in just how you think about solving these kinds of world impact problems you first have to find the problem right you have to been able to say okay well i think this is the problem i think this is how we're going to go about it and then do a lot of experimentation to figure out if you're on the right track yeah and on that topic nan how do you decide what applications to focus on how much of it is kind of do-ability how much of it is wow this is going to solve a really big problem how much of it is something else well you know that's that is some of the art of innovation right being able to to know that you're trying to do something new but not so far out there that it can't actually be done and you know x the moonshot factory has some pretty well structured thinking on that you know where it's a large problem with a radical um you know radical approach and a breakthrough technology those three like a venn diagram of those three things you tend to find really strong innovation um possibilities there but but oftentimes you can find that well you know it's not we're not really able to do that kind of technology breakthrough yet maybe that's a decade from now and so when you're in the sort of far out innovation game you have to recognize that it may be too soon or not this way uh and being able to be really dispassionate about that is is one of the great hallmarks i think more moonshot thinking um you know in our case you know there's a lot of experimentation with the robots and teaching them things against the learning robot moonshot and so the robots are being taught they're taught by experience they're taught by simulation uh we had a huge amount of simulation last year 240 million robot instances where we were in simulating the world the robots could learn in simulation um so we don't just need the the physical world for that so it's a it's pretty exciting to see the technologies of like simulation and uh robotics when you're actually out there in the field learning things uh sort of coming together to produce uh you know what the robots are learning to do yeah and what applications i mean you're talking about sorting trash and other things cleaning cafes what applications are you most excited about and you know what might we see you know in the next few months the next few years and beyond yeah i think as much as anything understanding that robots are when they're in an environment like a commercial space um that that they're navigating a very complex space for them and so the if you're seeing them clean a cafe for example that cafe you know a human walks in there and sees it with human eyes and it looks like you know somebody's been in the cafe a computer when they see that um that that same cafe there's an enormous amount of complexity that they have to first perceive and then internalize and understand so when when i see when you see their applications like uh wiping the table for instance or sorting trash into compostables and recyclables it may look like um that the robots get better and better and they're grasping better and better what what we see with eyes is unbelievable amounts of just the robot starting to see if i grasp this cup this way and more successful more often you know and so doing that you know millions and millions of times in simulation you start to see just better and better more natural moving performance so it's pretty exciting to see that across a bunch of different tasks yeah and again analogous to autonomous vehicles where the more test miles you go the better accuracy the more safety correct and and also just the the more that the robots understand what works and what doesn't you know because if you think about how humans learn as children that's a lot of what is in childhood right you're learning how things work how the gravity works how things uh how you grasp things and it works better than if a different way and so we're teaching robots that um is a huge part of the moonshot knowing as it said in the video that more of x paradox we live with that every day that it's you know which is easy for humans can be really hard for computers but also vice versa and helping figure out these um these kinds of learning uh services that we wind up with blending the best of human and robot capabilities is really what i find really exciting yeah and um at the very beginning you know you made a point and i think in the video as well about these are machines living and working alongside humans not per se replacing them um say a little bit more about that and does that actually create in its own way an adoption challenge is because now you've got some machine next to you and this feels very bizarre etc etc well you know it's uh it's hard hard to express how quickly you get used to the robots in your environment so like if you were in our offices in mountain view i mean literally the robots roll by my desks i don't know how many times during the day i don't even notice it you know they go by sometimes sometimes they'll be like hi how you doing you know you speak to the robot even though even though you know it's uh it's not gonna speak back at least not uh not not to me and you look at those kinds of um getting used to things it's very quickly that you get used to the robots in your environment and in fact the robots are because they're on autonomously navigating around our building you know they're they're people walking in the same spaces that the robots are are rolling around and the robots will avoid the people they will make sure that they don't get too close and all of that is so natural now that you don't even think about it so i think that's that's something that we don't see a lot of robot resistance uh in fact one of the interesting side effects of the pandemic has been and there's even less resistance to having robots in them in the commercial spaces and i think the use of robotics during the pandemic has been very very moved forward in terms of societal adoption and so you're seeing a lot of people interested in the way the world is going to be when we have robots and humans working together uh much as we have you know humans and computers working together it's not there's less and less of us us or them it's like no it's it's all of us together and that's really the experience we're trying to design yeah and so say more again about this idea i'm trying to think i'm going back to my star trek days i used to watch is it basically the idea here is there's kind of a segregation of activities the robots are off doing one thing they may be in the same physical space you have humans or they're actually interactive on multiple uh activities they're actually interactive but in terms of what they're each most capable of doing so you look at robots they're able to do things that are repetitive they're dull they're dangerous they're not they're not things that necessarily humans want to do a lot of and yet you say wait a minute we've got robots that can do that but robots can't do everything that the humans can do so in a commercial space you'll have you know humans who are providing some amount of supervision or maybe some sort of help for the robots but not you know they're not doing the same jobs they're basically doing um what we would think of as a transformed job so it's not like it was the same as it was before it's a transform job that involves both human and robotic labor yep good so let me dive down again deeper about what kind of society might look like here so you know there's been an interesting study that pwc has done saying when you look at robotics and automation there's huge upside there they did a report that said there could be up to 16 trillion dollars in value added by 2030 in the global economy separate report though predicted that about 30 percent of all jobs and 44 of workers with low levels of education are at risk of automation their jobs going away tell us how you look at the dichotomy between those two things yeah it's certainly something we pay a lot of attention to um and i think the the main way i would think about it is that um it's not really an either or in the way we see it that the jobs are not okay it's a computer job or it's a human job the a lot of the statistics that i've seen are like so many more jobs than would be lost by any calculation are going to be transformed like a huge factor of it and if you think about what the personal computer did for certain jobs you know like maybe bookkeeping became accounting became you know how we do the kind of modern day um financial transactions we do now that you could not envision that back in the days of you know manual bookkeeping so what we're going to see with these kinds of robotics advances especially in general purpose unstructured environments is all of those jobs transformed in some way so perhaps a human being is suddenly able to do instead of one of their uh their own labor um the value of their own labor now maybe it's 10x you know what they were able to have as a human because they're involved in this transform job so that's what we see is exciting is that it's it's transformation of the way humans and robots work together much as you saw the transformation of humans and computers yeah and is there anything special that society needs to do enterprises need to do individuals need to do to make sure they're part of the track of jobs getting transformed as opposed to just not being there at all where they're not part of that revolution occurring well i mean i personally think you know education is is such a huge part of what we're what helps people be able to have that capacity for more impact um in whatever career and field they've chosen i mean certainly education's made all the difference for me not least you know anderson and we can talk about that um but it is something that people i think need to continue to do um their education but also understanding where where they can start to sort of plug into that um that sort of economy i think you're going to see more and more robotics out there in more specific applications and the more people understand that you know there's an ecosystem around robotics that you know maybe it's not you you don't have to be the person that's designing the artificial intelligence maybe you're the person that helps with uh you know the repair of them there's a whole ecosystem that's going to be there for uh for robotics just as you see with computers yeah let me ask you nan you've got an interesting personal kind of experience on giving back to the community and thinking about kind of this transformation that that goes on you were part of google's effort to put in a green data center in bridgeport alabama and this was the site of a coal-fired power plant apparently where your dad used to work and it changed the economy the jobs tell us a little bit more about that and outcomes and what motivated you to do that well i would say that was one of the highlights of my career certainly my time at google was helping with that data center launch in northeast alabama i'm originally from that part of the world and come from very blue-collar backgrounds my father was a maintenance electrician including at that uh that plant back when it was a coal plant um and so to see that full circle um where you know i was able to come back to a place where my dad had been uh but yet come back not in a cold plant you know capacity but in a green data center um was was really exciting um and to see the way the community there reacted um because in places rural places like alabama north alabama you know there's often a sense of you're somewhat left behind or it can be a sense of being left behind and instead what we saw there was in fact some of the the community leaders were saying we are on the digital map now and our children in our schools they know that they're on the digital map and that they're part of this um global infrastructure that google was bringing uh to that area and so helping people um all across the world but especially places that haven't had the advantages like we have in california having them have access to these kinds of opportunities is really important certainly me personally um and i love being able to be part of it was you know when alphabet was doing that with the data center yeah excellent wonderful wonderful to hear other things you think that society needs to do you start to touch on education other things if you basically say listen a lot of our economy needs to shift jobs need to transform technology can create good outcomes what are the other things that need to happen that enables successful transitions as opposed to divides from occurring well i i think the a lot of things that i think helped better solutions overall come to pass or when we think of things like involving the externalities of the impact of various um of various technologies meaning that that if you just look at things where there's a little bit of upside business-wise but you're not really thinking about you know maybe in uh in electric cars you know if you're not thinking about the whole ecosystem of what does it really take for that to be successful you don't see the you don't see the kinds of big moves of impact that you can if if both industry and you know to some degree i'd say governments um you know start thinking about this prob the problems holistically how do we prime pumps for new technologies i think that's one of the challenges for especially when you have things like electric cars you know or even self-driving cars when you have a a you need a sort of priming of the pump the technology needs to be there but there also needs to be enough scale to start to generate the benefits so um that's something i think is is especially as technology leaders and we need to be thinking about that bigger picture not just our little piece of it yeah and now without having to get too quantifiable and all this we always kind of think about how much of these issues does society own like our government how much is it business owns how much of it is individual needs to own if you were to kind of say who owns the big parts of this transformation who would it be well and i think the you know the answers really we all do to varying degrees you know i think this is partly where individuals need to live values that are that they can stand behind you know companies need to stand i i actually am a huge fan of mission based um uh especially innovation and i think before i came to anderson i used to think mission and value statements were kind of you know like somebody puts that up on the website it's not a big deal you know every mission looks the same they all sound the same i actually uh more and more see that as that's not that's a bad mission if it could be any companies if you really need to have like your your efforts be something that's aligned to a north star mission and the more that's aligned with impact and the more that that's something that you can all stand behind i think not only do you have better success in in hitting that uh impact but you also start to attract the people that see it the same way and you start to have that cultural resonance where you know like uh especially we have everyday robots you know we're really excited about our mission for helping people in their everyday lives with robots so the people that want to come work with us they're really excited about that mission and you the more you're aligned with that and you're public about it and you live it um i just think a lot of good things happen um even to every single day when we're making decisions about are we going to do this are we going to do that i mean we have that rubric we have that touchdown of what our mission values are and if you operationalize it like that it can really be powerful excellent excellent so let me ask you a couple other questions before we go to audience questions there's a bunch of questions from uh from the audience obviously tonight we're going to hear from the winning teams on our innovation challenge and their focus on two areas healthcare and sustainability and you obviously got a great background in technology and sciences and leadership and innovation etc etc any thoughts about those two areas and things that interest you and and where you think they may be going well i mean since i'm here talking robots i'll definitely take it back to that i think there's so many interesting things um you know in the healthcare field and in sustainability where robotics is going to make an enormous difference um there's uh you know there's just so many applications in the healthcare setting including things like um you're transporting the kinds of materials you need in a hospital the you know delivering drugs um being able to bring water to a patient a nursing home you know there's there's so many things like that that you know that we'll be all spending decades uncovering all the different ways that we might be using these technologies uh and and one thing i will say is these technologies are inevitable this is a little different than uh i'd say smartphones or personal computers it's inevitable that huma that robots will be in our unstructured lives doing things it's just a question of when and how and who and you know that i think that's really the exciting part um and sustainability you know that i mentioned we're sorting trash you know that is not just a hey we're sorting trash should say how do we make a sustainable ecosystem of you know so that recycling is really something that that it continues to deliver you know the kind of full um circle that we want to see on reused and so i think all of these things have benefits from robotics but but they have more beyond that because so much of what we as a society needs to do is is focused on sustainability right now and learning's nan from your work on robotics that could inform innovation in other areas whether it's health care sustainability or other areas you know i think tackle hard problems when you can right i mean this is uh i think from a business setting obviously a lot of the economic rewards come when you solve really hard problems but but beyond that it's also just leaving a lasting mark of you know what we're doing here and i i so i i think being able to be in places where you have that kind of impact being with like-minded people and trying really um audacious things that have a big impact uh is what i i definitely recommend people try to find those you know try to find those missions try to find the people that believe it with you and then lean in give it everything you got and hopefully you'll you'll have that kind of impact yeah and on that latter piece about kind of building the team and being with like-minded people how do you do that any advice for people about you know build an organization that's got the right skills and style right well one thing i'll say is that you certainly don't want everybody to be the same right i mean in the sense of that was one of the great learnings i got at anderson um when i when i showed up at anderson i think the very first conference call i had i was convinced that i had missed reading a paper because one of the people on the call was talking about you know the strategy netflix had followed for something and and i thought i didn't read that well the reality was i had read that paper with a quantitative mindset he'd read it with a strategic mindset so i was able to see that wait a minute there's different ways of looking at all of this and that was one of the great learnings i had at anderson's just the the power of a really diverse team where we have different backgrounds different ideas and different experiences and we could come up with so much better solutions than any of the kind of overly techy quantified folks we're doing and so that that when i'm looking to build a team i want to have a lot of different voices i'm going to have a lot of different capabilities i don't want to have any of those blind spots um and and basically want to make sure people are committed to the mission it's it's something that that lack of commitment or the commitment in the positive is contagious and so you really want to make sure that people are brought in excellent excellent let me ask you a couple last questions related to leadership and then we'll again go to the uh the audience questions so give us you know your broad view about leadership here and where you think it's going how the requirements are changing etc well i i certainly seen a lot of change um in how leadership i think what how it works in the current uh workforce um it i see more in uh being able to put yourself out as a you know a leader who's learning a leader who's on your own journey you don't have it all figured out then we're all working together to try to figure out the best path forward being open to really constructive but sometimes hard to hear feedback um not being you know autocratic from the top that just really does not work uh anymore if it ever did and being able to be a vulnerable leader i think that's some of the most powerful stuff i've seen over the last three few years has been just some of the work around being a vulnerable out there leader um it's even beyond being a servant leader and i i think that's been something i personally enjoy that kind of environment where you know i don't have it all figured out but together i think we've got a pretty good shot of doing something amazing and then uh last question for you what what is necessary to get more women in technology we kind of hear a lot about the imperative there what is your view about what would create better success um well in my career you know studying computer science um and until now you know there's been a lot of times when uh there were not very many women in the room um and in that sense i have seen it get better i think the way we continue to get better and not just with with um gender diversity but also with just diversity of the group is be more open to our um the biases that we built in that we didn't really mean to build in and this is one of the things i've seen at least in computer science education there's been some really great innovation in places like harvey mudd where they are not they're they're teaching the courses differently than maybe when i took my freshman chemistry courses they're more sorry my freshman computer science courses they're more open to project project-based they're more open to the types of things that are more collaborative which you know may or may appeal to more women at least in those early stages but interestingly it appeals to a lot of men too you know it's like it's not just this gender difference it's more like let's make sure we have an open way of people contributing and frankly you know project-based understanding of how to make a project deliver is really what we do in the workplace every day it's not about the loan coder at least not very often and that's something i think the more we do that kind of collaborative work transparent values-based work um and i think you're going to find that there's a broader adoption not only among women but across a bigger swath of the population excellent let me start taking uh questions we got quite a few here the most upvoted question how do you avoid unintended biases and discrimination in your training data um well you really need to make sure you know what's in your chain data questions of course about you know artificial intelligence um if you have training data that's biased it's easy to teach your your models uh something that you don't want them to know uh which is uh you know some biased outcome i think the being really clear and explicit in what training data you're using where it came from you know we spend a lot of energy at alphabet on you know labeling data and making sure we know exactly what it's for um and then knowing what your you know how much data you need to train is also a key part of a lot of models so it's not all the data that goes into a training set it needs to be a pretty pretty clean set okay good good another question how does your teaching service approach change when considering users or individuals with either physical disabilities or neurodiversity um read that one more time i want to make sure i'm answering the right question yeah how does your teaching service approach change when considering users and individuals with either physical disabilities or neurodiversity you know i'm i i think when we're teaching robots um you know we're teaching them in a broad environment you know it's not just one where we expect everybody to to be operating in the same manner um in fact when we think about cleaning tables you know we're we're expecting there'll be people around of all kinds of different um capabilities perhaps somebody in a wheelchair sitting there and so in that sense it's making sure the training data is legitimate making sure we have a lot of experience making sure that we have a broad view of of what we expect to see and that we're continually learning i think this is one of the things you see from self-driving cars is that the world is so complex you need to be continually learning um and making sure that your your in your technologies are learning machines excellent and is it fair to say nan on this we kind of think about technology companies not just google as an example it's kind of the heritage was the super iterative uh approach to development you know put something out you learn you try you see and seems like what's starting to happen is there's much more focus now about well wait a minute where's the end state i'm trying to get to what data am i using so this whole idea of planned product design as opposed to kind of just iterations is that fair to say or no no that's kind of a one-off you know example uh no i i think it's i think there is a lot of especially when you get to artificial intelligence there has to be some amount of direction about what we're trying to to achieve but but then good product design i i don't think that's changed fundamentally from you know the earlier days where you really need to be thinking about who is this for you know what what's the customer benefit and what's the market for it how do i go to market you know all those things wonderful things they teach at anderson that's that's still very much true it's that the way we design the technology is is definitely shifting towards some of these more you know certainly machine learning uh kind of technologies great another question what consumer applications of robotics will be first to reach the mass market well interesting i mean i think you already see some of them um you know things like roomba you know it was interesting and this may be helpful for those folks studying product design when i was in graduate school at caltech um back before roombas we had a chip design class where one of the the final project was let's assume you want to make a vacuum cleaner but yet you don't need to be there with your big vacuum cleaner so like if i have to be there then all of a sudden i'm going to want to have a big vacuum cleaner that goes really fast it has a giant motor and weighs a ton but if i don't have to be there wait a minute i've got a whole bunch of different design spaces available to me now which is what eventually you see with something like roomba so when you see the the kinds of technologies uh like that those are still special purpose um they're still obviously got tremendous advances in that technology but still a good ways to go you're going to see more and more things like that i think our moonshot is is beyond that in terms of general purpose and very unstructured environments learning that's something that i think you're still starting you'll see that more and more in robotic applications in the home you know in hospitals in a lot of places okay good good another question um in terms of um the cafe cleaning example of the the road robot they obviously have to be affordable there's got to be an roi to get broad adoption how far away do you think kind of that practical adoption is going to be that's really it's really hard to say i think the you know when you look at where general purpose robotics is it's still very much a moonshot in a can you really get to that last few percent you know if you look at and when and how you get to that last few percent of performance of um of ability to to deliver something of value so we're still a good ways away from that that's why we say we've left the lab but we're still inside um alphabet's offices now keep in mind alphabet's got a lot of real estate uh and so it's actually a great proving ground for technology a great place to learn with um with very tech forward people around but yet they're still people and yet we're still working on providing that value to really help people good let me take a last question here and then do a a brief wrap up on this um uh carrie asks a question china is looking to construct a dam entirely via 3d printing what is your perspective about robotic readiness for critical infrastructure with no humans at all well i i would say the technology is not there yet um mostly in a when something doesn't go according to plan uh you know that and that's something i think in the data center world you know you in google scales in the data centers you know they're tremendous design tremendous technology but there was always something happening you know and in that sense i think the ability for robotics to deal with a change a fundamental change in the environment around it is still pretty pretty challenging but that's where i think learning robots is the answer there because you can't program for everything that might go wrong you need the robots to learn and this is where something like simulation uh can make a huge difference in helping us advance much faster than we would in just ordinary uh physical world and i think that that's probably the key to a lot of this moving forward fast enough to to generate impact soon excellent and then let me do i always like to do brief takeaways at the end of every uh sessions kind of what did i learn let me share what i took away and then you give some upgrades on that and then obviously we'll have the innovation challenge uh winners to give a readout i had basically three buckets of messages from you one is about the innovation in robotics itself second one is about the enablers how do you kind of think about what are the enablers required for innovation to occur and then the third one is leadership itself and a bunch of great advice there so on robotics you know message is first of all this is hard stuff when you said you know autonomous vehicles you know it's actually more difficult than autonomous vehicles and wow this is pretty tough stuff so it's very difficult but notwithstanding that you basically say they are inevitable we are going to have it the variable question here is the timing you know where but it's not a question of are we going to have robots and the the model here is robots with humans not necessarily robots instead of humans but working alongside which is a very interesting model second kind of learning out of all this are the enablers that allow transitions to occur innovation to occur society to occur and your first kind of message is no ecosystems know all the different piece parts that are required to get some good outcome and that can be you know schools and education it could be partners it could be app developers it could be a lot of people in the mix but be cognizant about the ecosystem and then think about you know your role in leading a transformation because this will be a transformation it's going to be a transformation of work and jobs it's going to be a transformation of you know how we do work etc tests etc etc but be part of it as opposed to kind of sitting on the on the sidelines the final piece is on leadership and it was interesting to hear all the different piece parts and you know to me what i kind of heard is all of these things are are all kind of part of a system you can't kind of say well i'm going to focus on innovation but not work worry about enablers i'm going to worry about enablers but not worry about leadership you got to do all this together your messages on on leadership several things tackle hard problems when you're thinking about big opportunities don't be afraid of those number two as a leader be reflective take in feedback the more feedback you can take in the better you're gonna get as opposed to insulating yourself from uh from things think about the power of the team and the diversity of the team from your anderson experience one plus one needs to equal three if you're really making all of that happen um thinking about diversity and thinking about bias and data and know what you're trying to kind of work towards know what data you're trying to use so that you've got a thoughtful approach to uh innovation and then the final thing is be mission based you know you know for all the people think it's kind of fluffy and all that stuff it actually if you're doing it right will translate into responsible innovation um nan upgrades on that did i miss anything on your your key messages uh no i think i think you got it and you know i think uh you know the more we're learning machines and the more we're trying to putting ourselves out there for having a greater impact i think the better leaders will be the better our companies will be the better our communities will be and there's no reason we can't go for that you know we don't always have to be saying oh it's all about the profit motive it's all about this there's actually a bigger picture that we can all be part of yeah i i love the message it's aspirational and it says avoid binary thinking it's very easy to get into things are all good or all bad and it's a it's kind of copping out on the leadership imperative which is to find out how you can get the good and mitigate the bad right so excellent excellent and then you can stay with us for a little bit uh after the the team's present because i'd love to get your perspective on on what uh what you hear yeah i'm looking forward to hearing uh their pitches excellent excellent so listen let me do this i want to share a little bit i'm going to share my screen here and i want to share a little bit about our innovation challenge and what our innovation challenge is all about so that when you hear the the student winners the team winners you'll have a little bit of the the context um here so two objectives to the easton center cross campus innovation challenge you know number one is just to create great levels of innovation new product and service innovation that primarily can focus on serving society so that's the first objective second objective is the more timeless piece which is saying can we create through this innovation challenge a set of learnings about innovation that can serve future students future entrepreneurs so those are the two objectives in the innovation challenge as i mentioned earlier we have two tracks in the innovation challenge one is focus on healthcare and that's healthcare really thinking about the use of technology to create solutions that are going to improve accessibility affordability improve overall health outcomes uh in the us and abroad the second track is sustainability and again it's the use of technology to create sustainable solutions that improve water energy food agriculture transportation and or the ecosystems around them in the construct of the innovation challenge we want all of our teams to be cross-campus teams so all the teams have had to have at least one mba and one non-mba and then they can fill out the teams from there but they've got to have that mixture of talent and then all the participants have to be a current ucla student fellow or post doc in terms of the timeline of this innovation challenge all the activity for what you're going to see tonight started in the fall so we had a kickoff event back in october we had a series of workshops that help empower all the teams to think about the peace parts necessary for a successful venture and innovation so whether that that be focuses on on workshops on financial planning on how you assemble a team product management how do you pitch all of those things were going on in the fall then in the winter we formally opened the team registration process and each of the teams that submitted ideas how to develop a business plan and that was by mid-february and then we had a group of judges look at the business plans that were submitted and decide on a group of finalists those finalists then we look in the spring presented uh about two weeks ago so april 22nd and 29th to a group of judges and as you know we announced the judges just about a week or so ago and you're going to hear from the winners of the innovation challenge terms of criteria that are used for the innovation challenge four key criteria first one is impact the depth and breadth of impact on the enterprise and on the society both of those things are our key measures feasibility so we don't want just kind of interesting ideas that actually can't be executed on so all the teams had to demonstrate a pathway to execution third criteria was innovation we're looking for highly innovative creative differentiated solutions not me too solutions but things that are really going to move the needle and then finally we we're evaluating all the teams on their persuasion skills all of them are going to have to raise capital they're going to have to recruit teams they're going to have to build partnerships etc and their ability to persuade others uh is absolutely critical so as you know uh two winning teams so tied for first in healthcare uh in symmetry and then also cervicore and then on the sustainability side kelp magic and again you're going to hear from all three of those teams all of this was possible as i mentioned with a lot of support both internally at ucla as well as external partners and then our dean as i mentioned tony bernardo at anderson has been instrumental in advancing this so big thank you to all of the teams and what we're going to do now is we're gonna start out with them and they're gonna give literally just three minute pitches about uh their uh their ventures so let's start out on the sustainability track and i'd like to welcome the kelp magic team all right well thank you everyone for being here uh my name is karen geary and i am representing team kelp magic so kelp magic is truly a cross-campus collaboration with each member bringing a diverse set of experiences and uh skill sets so jessica is a phd student at the molecular biology program uh greg just completed his jb at ucla law while daniel and i are 2022 mba candidates at anderson so i'm here today to talk to you about why kelp matters kelps are a critical part of the marine ecosystem and found off 25 of global coastlines it is a keystone species providing resources for marine species at all levels of the food chain kelp cycles nutrients like phosphorus and nitrogen cleaning water of nutrient pollution globally seaweeds are estimated to sequester up to 200 million tons of co2 each year which is as much as new york state's annual emissions kelp also supports a global agriculture industry with commercial seaweed production valued at more than 6.7 billion dollars globally with an annual
growth rate of 10.9 kelp aquaculture is growing faster than any other food production systems kelp also serves as a habitat for commercially important fish species and is used as feedstock for avalon and other agricultural operations it is an important bioproduct used across a range of industries such as bioplastics pharmaceuticals and animal feedstock but all these benefits are being lost due to climate change in recent decades increasing water temperatures ocean acidification and new predators that are more comfortable in warmer waters like the purple sea urchin in california have decimated major kelp forests along northern california's coast a marine heat wave that started in 2014 contributed to about 95 percent loss of kelp forests and shuttered fisheries worth up to 47 million dollars so scientists have observed mass die-offs of kelp forests in australia and tasmania and believe that uh kelp forests in france denmark and england are at risk of total loss by 2050. this is where we come in kelp magic is focused on giving kelp forests a fighting chance in these rapidly changing ocean conditions our solution is an enhanced kelp that will preserve ecosystem health and support a sustainable kelp industry to do so kelp magic will use a patented crispr methodology to genetically modify giant kelp we'll first focus on designing kelp varieties that thrive in warmer and more acidic oceans and later optimize for other commercial uses such as bioplastics pharmaceuticals as well as looking into carbon sequestration crispr offers the fastest most efficient and most precise approach to gene editing resulting in a cheaper process for selection and breeding beyond our core product our anticipatory governance services will facilitate responsible innovation and sustainable environmental stewardship kept magic applies knowledge of regulation to expand the market and ensure social acceptance of gene edited kelp kelp magic is an enabling technology for the growth of this industry and we will enhance this entire kelp ecosystem the products and services will be important not just in california which is our beachhead market but globally across a broad portfolio of products and this time i'd like to thank you and take any questions okay and let's actually go to the next team and then we'll take questions right after that so in symmetry which is one of our health care uh winners let's go to you and then we will uh take the final health care team and then we'll do a group uh uh q a sure thing and i hope it looks like you guys can hear me well i'm just gonna share the screen yep all right well thank you everyone my name is jeff sepanyan and i'm here to introduce you all to at symmetry uh what we saw in clinton uh what we saw with the covet 19 pandemic it actually highlighted the critical importance of the clinical trials process to as being the singular pathway to approving novel a life-saving therapies now unfortunately clinical trials remain extremely costly on average they cost around 20 million dollars extremely time consuming they can exceed seven minutes or seven years and also extremely operationally complex now these have led to a number of challenges critical and core to those challenges is really patient access to those novel care within clinical trials if you're receiving your care and you're lucky enough to receive your care from institutions such as ucla and the metropolitan center you're lucky because ucla and institutions such as us have both infrastructure as well as the resources to have a broad and large clinical trial portfolio unfortunately this isn't really indicative of the greater population in fact when we're considering uh cancer treatment uh cancer clinical trials are still considered the gold standard for many clinical trial many cancer thera or many cancer treatments and especially when you're looking at pediatrics unfortunately only three percent of cancer patients actually participate in clinical trials and when you're looking at that three percent it does not represent the diversity that we see across our n
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