Tech-Driven Innovation and the Role of AI

hello and welcome i'm tony bernardo dean of ucla anderson and i'm honored to welcome you to the 2021 wilbur k wu greater china business conference ucla's largest annual conference focused on the greater china region we're especially excited about this year's conference as it highlights ucla anderson's broad and deep capabilities and partnerships including our key relationships with alumni industry leaders students and departments across the ucla campus our talented faculty and academic centers at anderson including our host and organizing center the center for global management and its deep relationship with the eastern eastern center for technology management this is part of an overarching initiative at ucla anderson to enhance our ability to work across boundaries to learn and work in an interdisciplinary manner to work across the many important programs and schools we have here at ucla to connect academia and industry to work across geographies and to work between business and society these are critical leadership imperatives that our students and community must appreciate and excel at and this would not be possible without the long-term invaluable and generous support of the family of wilbur k wu whose legacy we celebrate with this annual conference born in 1916 in a village near guangzhou in southern china wilbur wu received his bachelor's degree in business administration from ucla in 1942. he went on to become a major figure in la's business political cultural and charitable arenas and was known for his decades of leadership in the chinese-american community global reach starts with global thinking and two day two decades ago recognizing the rapid expansion and modernization of china's economy wilbur wu the vice chairman of cathay bank and his wife beth endowed the wilbur k wu greater china business conference at ucla to show their gratitude for the training wilbur had received at his alma mater the woos are represented here today by their son michael wu the wu's goal was to facilitate dialogue promote understanding and strengthen the important ties between the greater china region and the united states to identify areas of collective opportunity foster cooperation and bring a group of leaders both aspiring and current together to collaborate and to learn together that goal feels especially important at this time in the united states when racism and violence against asians and pacific islanders are shamefully on the rise conferences like this one have a powerful and positive impact on our community here at ucla and beyond i would like to acknowledge and thank all our guest speakers and moderators who are joining us from all over the world including ucla and ucla anderson alumni i'd also like to thank our gold sponsor cafe bank our silver sponsor lancee holmes and our partners including the los angeles world affairs council and town hall the china general chamber of com commerce los angeles the ucla asia pacific center and ucla center for chinese studies as well as our student organizations ucla's chinese students and scholars association and anderson's greater china business association and a special thank you to the wu family for their continued support and enthusiasm around the focus of this year's conference on technology-based innovation in normal times a large group of our mba students would have just returned from shenzhen and hong kong where in non-pandemic years they are able to learn and witness first hand the remarkable innovations and tech transformations happening in the region while we look forward to resuming those on the ground experiences we are pleased this year to be able to highlight these same issues for a broader global audience technology is a key focus for us at ucla anderson leaders in every industry must understand the role of technology tap its opportunities mitigate negative externalities and be prepared to lead in a world that is increasingly technology-based finally let me welcome and thank each of you for joining us whether you're a student faculty member an anderson alum or a member of industry your engagement this week brings learning and impact now it's my uh my pleasure to introduce a longtime friend of anderson's a pioneer in los angeles political circles and a strong and positive force in the los angeles community michael wu was the first asian american elected to the los angeles city council he is dean emeritus of the college of environmental design at cal poly pomona and he's the son of wilbur k and beth wu we are so grateful to michael and to the wu family for endowing this important conference and for their ongoing engagement support and partnership with us thank you michael and thank you for joining us thank you dean bernardo and uh on behalf of the woo family we want to express our deep gratitude to you and the anderson school for your continuing commitment to the wu conference and to our father's vision of ucla as a bridge between the united states and the greater china region for the conference attendees who never had the opportunity to meet wilbur wu i'd like to tell you a little about him wilbur wu was an international student at ucla back in the days when westwood saw very few students from china born in a small village in guangdong province our father's first two years of higher education were at the old lingnan college campus in guangzhou one of the handful of institutions started by western missionaries from in china but transferring to ucla opened up the door to a great career and a great life our father always wanted to find a way to repay his debt to his alma mater and hence this conference dad was always was particularly gratified to see the success of the conference hinging largely upon the hard work of students especially international students whom he saw as following in his footsteps our father also would be gratified to know that a leader of technology and industry on the level of dr kaifu lee has agreed to be the keynote speaker unlike our mother beth wu who as a senior citizen joined a group to learn computer skills our dad never had an email address never had a social media account and probably would have had to stretch to try to explain the meaning of artificial intelligence but dad knew that technology was something important something transformative he was very proud of the fact that his granddaughter nicole and his grandson scott worked for companies such as google and twitter nicole who's in the audience today was deputy general counsel at google when dr lee was the head of google google china and occasionally had reasons to discuss legal strategy with him at a time when u.s china relations continues to be volatile and also at a time when chinese americans and asian americans are squarely at the center of a reckoning on race relations in the united states it's timely to remember that wilbur wu used to believe that it was always useful for people to try to talk to each other in that spirit on behalf of the children the grandchildren the great grandchildren and the in-laws of wilbur and beth wu thank you all for being part of the 2021 edition of the woo conference and for keeping wilbur wu's vision alive thank you michael uh let me just first say a big thank you for your warm words i want to thank you for your support of this conference your vision of the the conference i'd also like to thank our dean tony bernardo for his work in creating bridges in bridges across ucla anderson bridges across the broader ucla community and bridges across the pacific all of that is going to allow us to really kind of tap into the best learnings and ensure relevance on a global stage now as many of you know we made the difficult decision last year to cancel the conference which was slated to focus on china's rapidly advancing technology ecosystem as any technologist knows necessity is the mother of invention so this year we've moved the conference online for the first time ever we're excited that all the sessions will be available to students to educators to policy makers and people all over the world including in china and the themes that are originally planned in 2020 are even more relevant today i'm very excited about the opportunity this year with this conference to focus exclusively on the dynamic areas of technology-based innovation that are occurring in the region and how it's transforming the lives of consumers of enterprises and of society overall i believe there are many areas of critical learnings to come from the region how technology can be used to advance offerings in areas such as education health care financial services and manufacturing i remember when we were putting this conference together my early days at vodafone with its 28 wireless country operations and the mantra about learning uh best practices from across the globe to learn from other places and adapt them for your own market and to advance the cause of technology innovation for the benefit of everyone i hope that you find that this week's conference gives you a glimpse into the successes in the greater china region and the related learnings for all of us now to accomplish all this we've organized a conference into four days this week monday tuesday thursday and friday evening pacific time that's obviously tuesday wednesday friday saturday morning in the greater china region local time each day will have its own focus so today we're going to take a broader look at the innovation imperative and outcomes in the region tomorrow we're going to focus on innovation in internet services thursday we're going to look at the incredible innovations in high-tech manufacturing and friday we're going to look at innovation in fintech and the tech sector investment environment each session is going to feature incredible speakers and also moderation and our moderators are leaders in their own right here at ucla and from industry now first let me share a couple of ground rules and philosophical underpinnings about the conference and at ucla more broadly first of all the u.s china relationship is a long and a deep one with any relationship there can be complexities and areas of disagreement especially with a community as diverse as ucla these differences are understandable and they're appreciated we hope to build positive channels between the us and china with this conference in areas of mutual interest technology innovation especially in the areas of societal need we hope that these will further help each of us on our leadership journey and also to build a greater understanding as such we will be focusing the discussion and the related q a on areas of technology-based innovation avoiding political and or polit polarizing topics which could derail us from the important insights and learnings we have set as our objectives we appreciate your understanding and alignment on this vision for the conference and its objectives i'd also like to take a minute to acknowledge as dean bernardo has and michael wu has about the recent attacks on asian americans these attacks are antithetical to our values as a nation and at ucla and they violate the belief that we have that one plus one should equal three in terms of the diversity of our community bringing greater gains than people working independently i hope you'll enjoy the conference contribute and engage with it and that this conference builds our collective understanding about the transformative impact that technology can have on consumers on enterprises and on society now let me get started with the next part of the program i'd like to provide a little bit of context and then obviously an introduction of our very distinguished keynote speaker first to start with some context the global pandem pandemic has made it clear more than ever that technology is playing a foundational role in our lives as individuals and more broadly as society can you imagine what the last year would have been without services such as e-commerce streaming solutions video conferencing etc etc etc microsoft teams has added 95 million new users in 2020 from march to june alone it grew by almost 900 sales of zoom have grown by 320 in 2020 and their profits have grown from what was 22 million dollars last year to 672 million this year according to the mobile analytics firm app annie spending on in-app purchases in the first quarter of 2021 has reached 32 billion dollars a 40 increase year over year these are just snapshots but they emphasize how fundamental technology is and how it continues to grow radically day by day ai looms large in this arena and the us and china are dominating according to the market research firm cb insights there are 610 tech unicorns at the moment defined as startups with valuations exceeding a billion dollars and 49 of them are in the area of artificial intelligence fully 23 of those are in the united states 15 are in china the next closest country is the uk with only four of these unicorns now let me introduce our esteemed guest dr kaifu lee who we are so excited and grateful to have as our keynote speaker for this year's conference dr lee is deeply admired in the u.s in china and across the world as one of the most foremost exports in technology and in artificial intelligence and has been a keen observer of the impact of technology on society he's a world-renowned expert on ai and has worked on artificial intelligence for over three decades and has made breakthroughs using machine learning for speech and gains early in his career he was the founding president of google china and microsoft research asia and a longtime investor in chinese startups dr lee founded synovation ventures in 2009 managing over 2.5 billion dollars in venture capital investing in more than 400 companies including 18 unicorn with seven in ai dr lee is also the co-chair of the artificial intelligence council for the world economic forum and was named one of the 100 most influential people in the world by time magazine as as to the format of today's session dr lee will be sharing opening comments around the theme of technology driven transformations innovation and the role of ai and from there i'll ask him a set of questions that delve further into the key issues and insights and draw upon his career we'll then take audience questions using the slido platform for those that are joining the conference platform you'll see slido embedded at the bottom of your screen please type in your questions there you can either enter your own question or you can upvote one of the existing questions we'll obviously endeavor to have the most popular questions posed it is now my pleasure to welcome virtually dr kaifu lee uh hi uh thank you very much it's a real honor to speak to all of you at the ucla china conference and i want to share my experience in artificial intelligence in a sense it's the technology that i thought would really highlight the capabilities of china and u.s and bring opportunities for the two countries to work together the last point seems a little bit difficult at present but i remain optimistic in the long term i'm going to share my slides now and so in this talk today i will give a brief introduction of what is ai followed by the rise of ai in china and then new developments in china and u.s in light of kovid and projecting out uh over the next 20 years on what opportunities lie ahead so what is ai you know when we first think about it we probably think it is something that is to replace the human brain and in fact that is called general ai it's creating an ai engine that is in every way shape or form equivalent or better than humans but i think that is a kind of a narcissistic tendency of humans to compare everything to us to our brains uh what ai really is today is we are nowhere uh in building the general ai because there are many aspects of human creativity and compassion uh that we don't know how to do with ai and and ai actually the part of ai that works well is called narrow ai and that is taking ai applied to a specific problem with and training it with so much data that it excels uh well beyond human capabilities so the ai when we talk about ai today we're talking about algorithms that on specific problems with proper training data can beat human by orders of magnitude but in terms of our general ability to reason and think and create and love an ai doesn't come close it is really a different way of thinking never really intended to follow the human thinking process and so it does a lot better on some things but it doesn't do many of the things we do generally now this may become confusing when you look at the headlines right you see ai beating human in go something that's considered the best example of human wisdom and intelligence beating doctors and in neural imaging uh and now with ai able to generate texts that appears to be amazing in content and actually beating uh humans in a scientific endeavor of protein folding something that has puzzled uh biology researchers for 50 years has now been solved by ai so these progress would certainly have you think ai is trying to push us into a corner but in fact these are all tasks that are quite suitable for ai and that huge revolution in ai came around 10 years ago when deep learning began to be published and began to be applied around five years ago in very pervasive ways it is by far the greatest disruption and and let me talk about that in a little more detail deep learning basically works by taking a massive amount of data with very accurate label so what is a label well you you label an object you label label objects with the people and their identities and computers and phones on in an image and have a computer learn that similarly you can label um in a financial application good borrowers versus bad borrowers good borrowers being those who return their money bad borrowers being those who default and you train a system that learns how to select good borrowers out of a pool of applicants and improve your insurance companies financial success and it can be applied to amazon where whatever you buy ends up being labeling the path of your click-through so that other people who clicked the way you did or bought the things that you did are likely to buy the things that um that you just bought so ai basically trains on huge amount of data and and labels and basically very accurate labels and it tends to work well in a single domain so if you think about a large uh excel on steroids that's often the way i try to relate ai and deep learning to people who are not familiar with it think of it as a giant huge excel when you enter all the data you know about something and you describe an outcome and you push a button and it computes and it tells you what decision prediction or classification it makes ai makes requires a lot of computation power and requires ai experts to tweak the data so these are the five key things that make ai work pick a single domain collect a large amount of data train the system and run it it can be applied to obviously most to industries where there's plentiful data so that's why companies like google facebook and amazon and alibaba and tencent and bydes have become super successful because they possess the most data every time we click on a facebook or amazon or google page we're providing data we're describing intentionality we're describing that's something i'm interested in spending time looking at it or i'm buying it therefore it will learn not only on what i want to do but also other people like me and and the other power of ai is that it can target each person differently so that when i go on amazon and when you go on it its recommended purchases are different because it know my past history is different from yours so static web pages and human driven algorithms cannot do that so ai can really accurately based on data learn to optimize and that's the power of ai it doesn't have any of the other things that humans do uh and that's why when when people ask the question of can ai love can ai create some new economic theory or make the next picasso it it cannot it can replicate it can optimize but it cannot invent so apply to different industries is not surprising that first ai applications are from the bottom of the page apply to internet where data is the most plentiful and that's why google amazon facebook have become the most powerful and valuable companies as well as the companies that possess the greatest number of ai practitioners as well as ai driven data next ai can be applied to any domain with a lot of data so naturally financial services banking insurance investments and pretty much any other enterprise applications become possible candidates you could imagine these zoom sessions becoming a hugely valuable data to interpret um what people say and how audiences react and and they can learn intelligent things from that to build a better products uh thirdly ai will is actually gaining on the power of perception that is ai can see and hear speech recognition already works better for ai compared to humans object recognition is improving rapidly for specific objects objects in fixed images ai also does better than people and what's more is that human perception is mostly vision and hearing but for com for computers ai can sense a lot more than that you can sense temperature humidity you can sense a 3d reconstruction even in the dark that is equivalent to seeing in the dark and you can sense motion so ai can sense a lot more than people so if ai can do as well as people envision um and in in speech then ai can do a lot more with these additional sensors and iots that will become all the more intelligent and then the fourth wave is when ai starts to move around gaining the power of motion and manipulation then you can create ai that will do agriculture manufacturing warehouses autonomous vehicles robotics assembly uh delivery of goods so if you apply ai through these four waves it is surely going to disrupt all industries that are imaginable and and i think ai will really enable and empower in some cases disrupt uh these industries and i often talk about ai as the new electricity because it's one of those big general purpose technologies that's not just a point technology that improves one aspect of work but it is an omni use technology that is a platform just like electricity was and just like computers and internet were that can create opportunities to create value save time make money and help take over repetitive routine work for us so that's what ai is really all about so the narrow ai implemented through deep learning is now beginning to penetrate all kinds of industries i think over the next 20 years we're going to see a lot more changes although it's already creating a huge impact in the society as you heard earlier it's created some 25 unicorns in the u.s and something like um uh 15 unicorns in china and it's rapidly increasing and actually uh sounds like u.s has more unicorns but actually the most valuable ai unicorn is in china it's by dance and the company that builds tick tock it's privately valued over the 300 billion dollars right now so if you measure by value i think china has a head if you measure by numbers u.s is ahead so speaking of china let's go into the next topic about ai in china and as you heard in the 60-minute introduction this is over about a book that i wrote almost three years ago and these really are the seven key points that i made in the book and i'll go i will be uh talking more about the key points here so uh so if you uh have trouble paying attention to the next 10 minutes of my talk just remember the seven key points are at number one ai is no longer rocket science it is becoming mainstream and with the four waves we talked about secondly ai is the new electricity because it's omni use number three ai is the new oil because sorry data is the new oil because if ai cannot be trained on concepts like people are ai is trained on data so if data is the new oil then china is the new saudi arabia bringing huge opportunities with a number of people creating more data in china therefore china with its capabilities of building uh great entrepreneurs and startups plus with all the data china will collect ai with the us when i made this point three years ago it was a little bit controversial some people didn't believe it but i think now it's becoming clear number five is that china will probably lead with internet just because they're more people online china will probably lead with automation because china has more factories that it has to automate u.s will lead in research all the key technologies have been mostly invented by the u.s and u.s will lead in enterprise applications because that in that area us leads china by far and that will create huge amount of data in the enterprise so i think these six predictions have been uh quite accurate in the in that book uh the last uh a prediction i think will just remain a wishful thinking that i think all of us hold in our hearts so the chinese ai is in the last few years has been all over headlines we clearly see china having a lot of success with his entrepreneurs with this large amount of data and also with um smart government programs that have propelled it forward and i would say that in as described in the book the six key things that made china into an ai superpower right china was clearly a laggard 10 years ago in almost every imaginable i.t air industry but in the last 10 years six things gave china the opportunity to leap ahead and basically catch up with the us right now i think china and us are just about neck and neck if you evaluate all the different aspects of ai china has a huge number of ai engineers computer science is the most softer sought-after degree with ai being the hottest area that pays more secondly china has very tough entrepreneurs who compete uh tenaciously in the winner-take-all environment i don't have a lot of time to go into that in my book i use the example of meituan which is one of the most tenacious companies that went up to challenge alibaba and in the u.s you wouldn't imagine that to be doable who could have challenged amazon but since i've published my book metron has gone public and the stock has gone over um gone up as much as eight times uh currently six times at about 225 billion dollars putting a serious challenge to alibaba because it is the delivery company for food in china and when you can deliver food and meals at 70 cents per delivery you you can challenge e-commerce because you're delivering things in 30 minutes not in two days right if you can imagine doordash becoming huge it's delivery capacities could challenge amazon but it would be my bet that door dash founders don't have that ambition for the chinese entrepreneurs such as wong xing and mei twan does bhai dance is placing a serious challenge on tencent something also not imaginable that you wouldn't imagine snapchat could really dislodge facebook but the chinese entrepreneurs have that tenacity and as i mentioned uh dance is now close to a billion daily active users more than half of uh 10 cents and it's winning more minutes per user it's creating more value per per user and is creating a wide array of products including successful products overseas such as tick tock and its market valuation is also now closing in to maybe a third or a quarter of 10 cent but going up much more fast much faster than tencent um third is really the outcome is that china has developed a parallel universe in terms of what the chinese internet looks like in many ways i think the chinese internet is much more efficient uh if you for me uh let's put it this way for for my personal life in order to make myself you know well fed and get all the good things i need to buy make my family happy and entertain and be entertained and get all my news and all my readings from the internet and connect with my friends and communicate with them i would say the chinese apps are probably saving me an hour a day out of you know a few hours online for personal activities so much more efficient than the american apps the enterprise is a different story as i mentioned so the fourth reason is now with the chinese apps taking so many minutes per user uh byte dance today through its doing and total apps are taking more than a hundred million minutes per user well more than the equivalent american app so china has the advantage of having more users and more usage per person and that creates more data and trains better ai as a result china's ai funding in number five has actually basically caught up with the us it's neck and neck depending on which year you look at and finally it's support from the government that has been helpful note that i put this as number six because if you read the western media they would have you think if that's the primary reason but i would say uh probably 90 of the credit goes to the chinese entrepreneurs maybe a few percent goes to the vcs like myself and certainly some goes to the government but i think the key things the government does has done is to create um a techno utilitarian environment that supports innovation and and create incentive programs uh for cities to to give incentives to attract top entrepreneurs and to build infrastructure something that commercial companies can't afford to do so let's quickly go over some of these key things we know the uos still leads in research all the touring or world recipients basically are are north american chinese american americans or canadians but note that the young researchers are catching up from china this shows you uh the top 10 of all ai papers uh actually crossed last year where that means they're more if you look at the top ten percent of all ai papers now there are more chinese papers than the american papers us obviously top fifty percent the same way top one percent will take a few more years uh we talked about the uh the entrepreneurial environment being very tenacious winner take all um so while china has fewer unicorns it has more companies that are over a hundred billion dollars that have data on the internet space and that means they have a huge amount of data and they have a huge advantage compared to their american core equivalent company as well as their competitors in china and also these companies growing bigger are coming up with new business models that are actually making the chinese companies are quite innovative and we're now seeing some copycats uh in the us we've now seen you know facebook make several attempts at copying tick tock without success uh we're seeing um doordash being a copycat of metron so the copycat began from china copying from us and now we're seeing copy from china and actually i see huge opportunities there if any of you are thinking about entrepreneurship i think you should study the new chinese e-commerce the e-commerce plus entertainment model the pindodo model of social plus e-commerce china is now coming up with a new generation of e-commerce successes i won't have time to go into them i think all of them would fit the u.s and they can particularly build off of the post covid improved digitization in the us we've seen the dual world and i mentioned the huge amount of data just makes better ai and china of course has a lot more data than the u.s this shows you you know china has 10 times more food delivery than the us this was pretty pandemic but i bet today is still easily more than 7 or 8x a lot more mobile payment i know now that in the u.s paypal and square are offering a mobile payment but still china in china there's cash has been eliminated and all of that becomes powerful training because transactions by mobile payment is actually purchasing not just clicking very strong power of the uh indication of the labeling uh china's ai capital we've talked about and then we've covered also china's techno utilitarian policies and and again the infrastructural environments whether it's building 5g and 6g and or whether it is building infrastructures in cities that facilitate autonomous vehicles or smart highways and this is being advanced further since the completion of my book china has announced a two trillion dollar high-tech infrastructure plan called the new infrastructure it is about building out what's on the right 5g industrial iot data center and of course ai and data and that infrastructure will make entrepreneurs have a much easier time whereas the american government chose to give trillions of dollars to the consumers to relieve their challenges for kovit china put an equivalent of the money to build the new infrastructure and and of course china is putting a lot of research whether we measure by publications or by patents uh china is improving so let's talk now about since the publication of my book what has happened so my book i think we've kind of reflected on the last three years and showed you where we are but going forward what is the future so this is the first talk in which i'm going to tell you i've written a new book and the book is called ai 2041 and i won't go into details here but i think all the questions you have about the future of ai in the next 20 years including ai's challenges on privacy externalities and quantum computing ai in singularity is it real or is it a hoax and you know how how the future robotic teachers will change your kids and whether matrix or real ready player one might become a reality as well as the future of work future of war and post scarcity when everything can be almost free and the ultimate question of um can ai make us happy so this is a book with uh 10 stories and 10 visions for the future that i hope will be even more uh exciting and it's um now it's coming out and it's available now on uh online bookstores uh but coming back to the a couple of the key points i make i don't want to spend too much of this session on 20-year predictions so i'm going to pull it into more like five years what are the things we see certainly one thing we see is that kovit has accelerated digitization by making everything uh digital it makes creates data and data makes ai possible so and also the social distancing creates opportunities for automation and robotics so i'm going to pick a couple of sectors where i can see big changes happening in china and three in china and one in the u.s that i think will create huge opportunities uh for your future jobs employment entrepreneurship or thinking about ways to benefit from these uh changes i mean covet is a terrible thing but it has digitized the world in different ways so first on automation because of social distancing china needed to make safer factories safer warehouses safer restaurants so automation and robotics has really taken off in the last year since the beginning of kovit from a china country point of view chinese labor is now two times of india and vietnam which creates a serious challenge for china's position as the world's factory and so china has it had a concerted national push to improve and increase the number of industrial robots you can see in the second graph china has way exceeded any other country in building industrial robots to automate its factories and of course energy revolution is going to drive down the cost of um of manufacturing and china has made very ambitious i think the most ambitious plan for going going to carbon neutral and some companies are doing amazing things in china so as china brings the cost of energy down it makes the energy cleaner install robots uh the china will be able to produce more goods for lower prices because the major cost of production is energy materials and labor and this will bring down two of the three components making china competitive and maybe even less expensive and higher quality than other developing countries and this can be applied to many areas obviously in manufacturing assembly picking on the on the first column on the upper left you see a chinese innovative company that has robotic arms that can pick up an egg yolk on the bottom is an autonomous uh company that waters uh for agriculture and it also harvests fruits in logistics autonomous carts autonomous forklifts are automating movement of goods in the factory and warehouse smart cars are now being applied everywhere um in in airport shuttles in the mine in the mines robot robotic robo buses are happening in china you hear about robo taxi in the u.s because waymo and tesla are thinking about it that's very cool but going from any place to any place is hard robo buses are a hundred times easier so china is actually deploying robo buses in a number of cities and in in pharmaceuticals actually a company in china has automated the laboratory so the researcher can do experiments uh without touching anything and the lab technicians are gone and also the same technology applies for covet testing so cova tests in china are incredibly effective because there are a number of reasons one of the key reasons is the automation of the process by robots in healthcare there's a lot of details here i won't be able to go into it i would just say that china has every reason to lead the world in ai healthcare obviously covet has brought people's attention about healthcare and the opportunities but key a couple of key points one is that china's healthcare spend is way less than u.s in percentage and it's got to catch up and also china is the biggest market with a huge increasing aging population so this is a big growth area also there are a number of things happening such as telemedicine that's now covered by public care and telemedicine is another digitization that will create data that is being kept and china is actually catching up in biology chemistry research so i think is a wonderful huge market where a lot of things will blossom and they'll be combined with ai but on the key point of this talk is that you know data is the most important thing for ai what's the status of chinese ai data well in the u.s i think things like the hipaa regulations make it very difficult to collect data from a patient even with anonymization and even requiring user consent per use that creates a huge problem because if i wanted to donate all my data it's not i can't even do that i was uh i'm a cancer survivor i would love to donate all of my data i don't care about the privacy issues but i have no means of doing that in the us but in china i can and for people who care about privacy there are ways to anonymize do they donate your anonymized data for general you good use but not specifically for this user that use so so china i think has obviously privacy laws but it's not nearly as stringent as the hipaa laws in the u.s as a result a public company edu cloud has now you know launched a company built on a billion pieces of medical records and it's trading on hong kong stock exchange and doing very well worth billions of dollars in education is another area where ai and tech can be used to reach more users integrating online and offline and ar and vr we we now have a number of startups that have virtual teachers it turns out virtual teachers are better at teaching students of younger ages because these could be their favorite cartoon characters that make learning fun ai can be used to customize learning for each student if a student is stuck on some point ai can teach multiplication very well with a lot of drills before it moves on to division if a particular student loves basketball ai can reshape all the problems or many of the problems to be basketball related to make it more engaging ai virtual assistants are great for education there are these um actually one of the companies in china has not only built virtual teachers uh they build virtual students so you're in a virtual classroom like this zoom room uh with maybe 10 kids and a teacher one of the kids is virtual and and it's proven that child that student actually livens up com communication in the class you're probably wondering how do we render a realistic human child or we don't yet do that we actually use recorded video but that has proven to work uh rendering a accurate video i think can be done in the next one or two years uh inexpensively uh to liven up the classroom this of course still means there's a huge role for the human teacher to play right human teacher is is too valuable resource to do drills and homework assignments and tests human teachers should be motivators and coaches and mentors and care deeply about helping define the future of each student and that's what the human teacher should do partnering with ai that takes care of the routine part of the teaching so that's a huge area as well and and lastly look back to the u.s actually we talked about a lot of areas where china is strong in automation robotics and healthcare and education for using ai but i think u.s has an unassailable lead at this point in enterprise ai because because kovit unfortunately kept u.s workers from at home for quite a bit of time and that duration has digitized the workflow and made tools like zoom and docusign um microsoft teams and and products like that uh very easy to use and layers of new products like snowflake are coming in as well so if we look currently at cloud use you know china lags uh us by about an order of magnitude china will catch up but it's way behind now but if we look at sas and the use of enterprise software china u.s is now 21 times the head of china and if you factor in all the boosts to microsoft and zoom and docusign all those companies it's probably even more this was done about half a year ago so so i think china so while china has digitized consumer space much better u.s has digitized enterprise space and as we know enterprise space has huge value for companies to be able to apply ai and extract value from the treasure trove of enterprise data that they've collected so now these two ai tools will surely come out of whether it's for human resources finance finance department legal department for managing for the ceo to have a dashboard to manage the company and and for you know uh a business school like ucla i think this creates huge opportunities for students to see what can be done with this data that's now being collected by enterprise apps can ai put things together and help companies manage better just as i describe how ai is helping teachers and healthcare providers in china and factory owners i think applying ai to enterprises is the defining application for u.s to continue its leadership in the world in ai application in an area that very much fits the success and leadership position that u.s has so to conclude i believe ui ai will create unprecedented value and wealth to society uh china and u.s will co-lead the ai revolution and i see even more opportunities in the next five and in the next 20 years thank you very much kaifu what a fascinating discussion i do a lot of these uh and i think i've learned more in 20 30 minutes just listening um to you um i have a whole bunch of questions the audience has got a bunch of questions if i could just start out with a little bit of your personal story i mean you you went from industry you were at microsoft you were at google you've been an investor you talked about being a cancer survivor tell us about the dots that all got connected that kind of gave you this kind of insightful view about where technology is going uh yeah so i have been extremely fortunate um that when i went went into my phd program i selected ai and i studied under one of the best professors um in ai raj reddy who was a touring award recipient uh he not only taught me the basics of ai but gave me the freedom to pursue machine learning back in the 80s this was quite rare now you're going to run into a lot of people who said they've done ai in the 80s but they rarely did they get to use machine learning because while machine learning is pretty much dominant in ai today back then this was a very uh niche kind of technology and and it was not the area of my professor but he gave me the freedom to pursue something i wanted and that has really taught me um you know when you lead smart people you really need to get give them latitude and treat them as equals so i think that was a very lucky step one and and then i i was very lucky to have worked at apple microsoft and google and i learned amazing things at each company at apple i learned what it meant to be maniacally focused on the user to do everything to please the user and that that was incredibly important to me because technologists tend not to think about that at microsoft i saw the management of you know 20 000 people project as windows was built how companies can be organized efficiently and and how um how large number of people can actually work together on giant project also something i never imagined at uh universities where usually you work on one two three person teams um and then at google i saw a new man a new model the internet model of where speed matter mattered more than size where um the company at the time tried to essentially eliminate bureaucracy by saying um the greatest um what microsoft did extremely well google did the antithesis it says don't build twenty thousand 000 income projects let's build a 10 person project and if we remove layers of management small teams of super smart people who have a single shared goal can do more than layers of hierarchy especially in the internet space where we can use the internet to test trial ideas do a b test and let's not we don't have to be steve jobs to know what the user wants we can tweak products and figure out what users think and make them better and better and that of course is the energy that uh the thinking that allow china to uh to catch up because i don't think there are a lot of c jobs in china but when you have the internet as your experimental platform a smart entrepreneur can come up with an idea see what users want and tweak them so these i think are my fortunate american lessons i think my chinese lessons are the following first i arrived in china in 1990 as a un program my first time in mainland china and i saw that even though we have the same ethnic roots that here are a bunch of people in a very poor underprivileged environment with no resources i was touched by students who programmed on paper and professors who graded the programs by running the program in their heads that under such tough conditions they were still working much harder than me and i felt that there are all these you know 1.3 billion smart people and hardworking and and there's things that i can do to make help them realize their potential so that has caused me to seek opportunities to write books and actually you know you know my two books in english i've written seven books in chinese mostly helping chinese people i think have access to you know self-improvement understanding yourself finding your strengths and weaknesses planning your career those are some of my books but also introducing new technologies like social networks and ai or some of my other books that have been published in china so helping chinese youth realize their potential and that has caused me to build microsoft research for um for in beijing that has turned out i think to be perhaps the best ai research center for asia and and trained 5 000 people over the next last 21 years i also got to run google china which was a fun experience and there are so many billionaires who have come out of my company now but and i'm so proud of the team with accumulated even though the company decided not not to continue its business it created kind of my um learning about the um internet how to build products and and also the the chinese internet which is becoming uh successful and huge at a time and then of course i found the sign of asian ventures which really brought made 100 of my time helping young people um make their dreams possible whereas at some of that at google microsoft now i get to do it full-time so these are some of the dots i can now connect uh and i just feel very fortunate to have had the essentially the best opportunity to learn from the u.s and from china fascinating great impressive story impressive story let me now ask you you know you've mentioned the impact of data and artificial intelligence across a whole host of sectors you've talked about healthcare you've talked about education you've talked about manufacturing you're obviously an investor now the whole idea about what do you invest in when so how do you know which sectors are going to happen now i mean is it because you look at the size of them you look at the potential impact of ai how do you overlay timing on it what's kind of your mental map in looking at these opportunities yeah i think there are three really important things i think one understanding technology is something that really is our true edge because other vcs are good at other things too but really understanding technology and we do that by we actually read academic papers so we try to do two things first we try to understand all technologies that may tip in the next two to three years that may become may go from unusable to usable or barely usable to very useful okay second we try we understand the weaknesses of the technologies and the requirements of these technologies so those become preconditions for example if you want to do a company that reads mris more accurately than humans well accessibility to the data is important that would mean doing such a startup in the u.s would be incredibly difficult in china would be somewhat easier so understanding those requirements as well as the weaknesses and problems i think that's important these are technology related and i think unique to us um because we we actually at synovation have a technology team in addition to the vc team the uh the other side is that we want to come from the other side and look at uh businesses and deeply understand uh their problems and challenges and what needs to be solved and and and also related to that uh what is their current way of doing things um and and and making sure that as we think about the technology application in an industry it is not out of some naivete that says oh this should work build it and they will come but rather than we don't want to educate the market we want to fit as much as possible within the existing infrastructure and channels so using the imaging example again if you came up with a great way to read mri i would ask the question let's say red mris better than most radiologists i would still ask the question how do you sell a product do radiology departments have an uh software purchasing process what is their workflow does it fit in can they make make big orders or and also the question of what would the equipment manufacturers want to embed these technologies uh into the software platforms people use you can't just sell the technology the radiology reading technology needs to be embedded in the entire workflow software and hardware so those are some of the questions we ask and ai uh ai scientists often um don't don't ask such questions and so if you look at some of the ai products that haven't been most successful uh what happened there right there actually i have been a bunch of radiology ai companies they're struggling because hospitals don't have a way of buying ai software today now that can change over time but you better make sure it changes before your company runs out of money another example is ibm watson i mean a great technology great team but they really uh in order to work but but they didn't realize there's a big gap between the way ai people think and the way medical researchers think medical researchers think incredibly high quality data needed to teach my students so if you go to the likes of sloan kettering or md anderson you know they're proud that they have 120 cases of ovarian and cancer to teach students how to treat ovarian cancer that's all you need to teach people it doesn't get better with quantity you need to carefully select them to teach the students but can you imagine teaching an ai with 120 examples you need at least 120 000 so those things are practical issues when rubber meets the road and i think it's incredibly important for those of us who have experience in technology and in business really uncover all the details the nuts and bolts and ask all the tough questions before we naively think this industry is ready for ai or this technology is ready for prime time excellent very very helpful let me ask you the next question on this and that's about geography so thinking about where innovation will happen and you've mentioned obviously luminary companies in china do you envision that a lot of the innovation the customers is going to stay within china for the foreseeable future because it's a large market it's growing etc do you expect it to be sold outside china in the us and europe give us the geographic piece here okay uh so i would first give the caveat that i still believe fight dance's success with tick tock is not going to uh be easily replicable um but i think that by dance will be successful because they now have a great product and now they're now snowballing their experience i think there are two major issues why chinese technologies will have a hard time going to china and going to u.s and europe first is that china is such a large market it's a blessing but also a curse right because the opportunity cost to build a product for europe or for the u.s let's say you are a chinese ai startup you're doing well in china and you're thinking about going to the us and you hire 10 people for that well that same 10 people can probably be applied to extend your product for china without all the cultural and other issues language issues channel sales issues you have to learn to south america so just in terms of opportunity costs it's more more profitable to deploy new resources in china than going abroad so you usually only see companies when they saturate the chinese market to go abroad such as henson alibaba and maintenance but that's going to be take a long time and by the time you do that probably you will have had you know five to ten years of media coverage and tech crunch coverage that some american ought to be tipped off and maybe started before you that's the first reason the second reason is that i think the the challenges in the u.s on europe are very substantial these are not just language and culture but obviously some of the recent tension but on top of that i think the chinese people are closer to other developing worlds in the sense if you look at the average youth what they spend their time on and their typical patterns their families and so on china is after all a country that's emerging out of developing countries so it serves very well to to what india might be like in five years or um or brazil or middle east or africa in ten years so chinese products i think will generally do well in developing countries because china is a good leading example for them but um chinese users habits in u.s and europe there is a quite a bit of difference and overcoming that difference is hard tick-tock has obviously done it but i think that will be the exception rather than the rule so i would predict that in developing countries we will see quite a bit of success for chinese companies in the next five years in fact i would predict chinese companies will become the number one country in which software is provided overtaking u.s and overtaking domestic companies for the reasons i mentioned one final point related to that is having worked in a large successful american multinationals uh honestly american companies just don't value developing countries uh all the energy is put on countries with larger armed for u.s europe japan maybe china but very little attention paid to developing countries and that used to be okay when u.s had a hegemonic position in the market but as china becomes an equal it's basically exposing a weakness that unless americans companies change and i think changing old ways are hard uh i think these developing country markets which is you know over half the value of the population of the world is uh i think for the easy picking of the chinese entrepreneurs wow fascinating fascinating let me go through a couple other items and i want to get to audience questions you mentioned in several points about the importance of chinese entrepreneurship and you said almost it's kind of underrated from a u.s point of view say more about what you're referring to there uh yeah i think hard work is one of them um mike morris wrote the paper a while ago in financial times it was a little controversial but i think what he said was correct you may or may not like it but the fact is that the chinese entrepreneurs most of them having come from single child poorer families see their opportunity as once not just in the lifetime but the entire family tree of you know 20 generations the one chance to make good so there's huge pressure and huge hunger for success and entrepreneurship is a great example of role model where jack ma and others provided a great role model so i think this pushed the chinese entrepreneurs work really hard when i take chinese entrepreneurs to silicon valley uh they're both impressed by the creativity but also surprised by the how few hours american entrepreneurs worked i'm not saying it's better or worse but it's kind of the current situation that chinese startups typically work uh 996 or 007 996 being 9 a.m to 9 p.m six days a week double or seven meaning noon to midnight seven days a week and these workout hours i think by you know american standards would definitely be bad for work-life balance very hard to to have a family with these but chinese entrepreneurs whether they're married or not really do that the other aspect of tenacity is this idea of winner take all right i think partly because uh people are hungry for success partly because china is such a large country with so much vc ready to fund you to become a bigger and bigger and bigger company um and partly because large ambition aspiration and greed that push companies to never stop uh that's good enough so an example i gave was when may 1 was founded there were 6 000 startups to build going after the groupon like model and they started being copycats of groupon but metroid turned out to have evolved their model into groupon plus uh doordash plus uh opentable plus yelp so they cover it all so the chinese companies want to overtake the entire thing and build a huge platform on which it can service customers better and of course extract more value so do whatever it takes to become a huge success market leader or monopolist if you want to call it and and they keep going at it and even when they clearly won the food war became the food giant in china it's now going after alibaba right so uh and and and so people would ask from business school what about checking uh the power of a monopolist well yes uh it is true that a monopolist can get complacent and less creative stipel creativity and jack up the price but in uh in uh essentially a dog eat dog world like chinese entrepreneurship the smart ones the small companies want to take over your business the large ones want to kill your business uh every company is living paranoid all the time so my time never had a chance to sit back and say hey how do we extract more value and and rip off consumers because the moment they do that alibaba and tencent and by dance will come after them so these giants are checking each other unlike in the u.s google has its space instagram has its space pinterest has its space you know yelp and uh and uh doordash and uh groupon they are all you know sort of um accepting the role that they have in an ecosystem i play this role you play that role we compete and we collaborate in china pretty much you just compete and and that actually leads to an interesting point where uh where large successful companies have to always be on their toes and so far has worked pretty well but of course both u.s and china are looking at anti-trust for the giants but that's another another matter yeah let me ask you before i start with the audience questions what's your view on india i mean obviously india is a large domestic market it's growing rapidly but as a supplier of technology a creator of technology not a market just you sell into where do you think india will go um well i think india has huge opportunities because it has a large population and that has the potential of generating data but that market is rather fragmented right because because the many languages are spoken in india and also because of the larger wealth gap between the haves and the people who are extremely wealthy and the others who are not and and a lot much larger number of people living in poverty compared to china and of course now it has to deal with uh still surging covet so i guess you know i think i'm obviously impressed by the engineers in india with their capabilities look at how successful they are once they got to america right leading companies like microsoft and google now um and i'm impressed by um the some of the entrepreneurship that is happening in india but i would say some of the problems about the really uh the over the overall economy and i'm concerned and also the lack of a complete vc ecosystem and just needed to support the entrepreneurs and i haven't seen the indian government put in the infrastructure and the incentives so i guess i'm kind of uh mixed on that various constraints and very weak weaknesses makes sense makes sense let me start taking there's a huge number of questions and quite a few of them have to do with enablers and public policy issues so first of all on data privacy you've talked about some of the challenges that u.s technology companies have with the data privacy rules um here say more about it eric schmidt kind of talked about you know broadly the us competing with china and plus it was a bit of kind of the data rules do you see the data privacy rules lightning somewhat in the u.s when you see the potential benefit of ai or do you think this is going to be a step function difference between china and the us that will create a step function difference in innovation i do not think there is a substantial difference in how china manages chinese companies on their compliance with data there is a growing tendency to accept something like gdpr globally so i think in some sense that is pushing all countries forward and that's a good thing um i i think um the you know the punishment in china is actually more severe for certain violations uh consider what cambridge analytica did but the founders are starting another company there is no criminal or even civil charge right in china they've been in jail already over the basically stealing data that is against commercial use of the contract that is very much enforced in china more strongly between companies at the expense of consumers um i i do think consumers in china don't have a strong advocacy right you know you watch a film like um social dilemma it really strikes strikes a chord with many american watchers in china it would be less so but that's i think a maturing of the chinese consumer gradually consumer advocacy will happen so i don't think that itself will be a big gap but now i think the chinese consumers are more willingly willing to trust large companies and use it a lot and hope bad things don't happen and believe that when bad things happen government will punish the offenders more effectively than um then i think the americans will so i'm not sure the the government regulation is the main thing my main point on privacy and government governance is i think we have to give the technologists a chance to come up with ways to resolve that as much as i respect many aspects of gdpr i think there are i mean also many aspects that don't work very well at all when i go to a european website all the pops up pop-up windows you know i just close my eyes and say yes yes yes it hasn't really done anything it has sort of successfully said okay well you clicked yes so now something bad happens uh you click yes it's your fault that doesn't really solve my privacy problem what i really need is a technology that protects me because no human can really understand what every website and app does if i cannot most users cannot and and if these are hard to understand then you've got to have some way of technologically filtering you know using technology to provide my privacy if you will right what has protected us from uh from viruses why isn't our pc and phone contaminated with viruses all the time because we've allowed technology the antivirus software to protect us we don't we don't go read every aspect of every virus for me to click every download and read its um you know its registry table to determine it is acceptable i let software do it so i believe in the future some kind of software protection and there are a number of technologies being promoted uh federated learning homomorphic encryption trusted execution environments i think we got to let technologists contribute and chip in and not believe it's a purely regulatory problem makes sense makes sense let me ask you the next question it's on antitrust related uh issues so you know there's more thought work actually out of harvard business school about competing in an era of ai that basically says there's increasing returns to scale with database businesses large tech companies can move across sector they improve products and services etc but then you do have this view more from europe but someone in the us that said that big is bad that we got to watch out for these large companies they can become anti-competitive what is your view on antitrust in the us and you know news in china as well on antitrust issues what is your view about where it is today and where it should go this is certainly beyond my expertise i certainly agree that large companies with data increases their power over users and society and that needs to be checked and so i think whether u.s or china looking at antitrust is is a good thing what i am concerned about is the speed of governance that can move uh because technology moves much faster than governments when i was at microsoft there was the anti-trust probe that took so many years by the time the final ruling and punishment came down microsoft was no longer that much of a monopolist google had taken over you know it was just too slow so how can governments move faster would be one question uh the other question um well actually on that point we saw the china punishment for alibaba came much much more rapidly one has one can have different opinions on whether it's effective or not but i think that speed is uh is needed taking forever to do all these congressional testimonies um is slowing things down i think and and the results are no better i think than the chinese outcomes i think a speed is important because you know bureaucracy government bureaucracy can be very slow and technology moves at lightning speed the other point i would make is that the current types of more more more stronger punishments namely breaking up companies we have to remember these were developed in the days of att antitrust or standard oil antitrust not so suitable for for something as complex as internet giants right because you know the thing that atnt did wrong or quote unquote wrong was just the power over uh the entire telecommunication chain so you break it up the thing that standard oil did raw was uh go into things like gas stations that was monopoly extensions you don't let them do that but it's much more complex and i think eric's point is that you have to look at a multiplicity of issues and not just use simple-mindedly used old rules and break up google and facebook and i i do think that would be something that needs more care and i think something new needs we need to come up with something new to check the giants i actually think china has organically come up with one way which is a tenacious market uh which which means let the companies check each other but obviously it's not sufficient but i think that's one of the mechanisms that probably would not have appeared possible even to uh you know professors in business schools yeah but anyway it's not enough and i think more innovation is needed on how to keep the companies in check the old ways um just are outdated not effective makes sense next question is on the future of work and you mentioned in the 60 minutes clip up to 40 of jobs could go away etc tell us you know where you're most worried and then importantly what is the role of government versus business how do you see that playing out in the u.s yeah um i think it is a huge issue because while i believe technology revolutions will ultimately create more jobs and more exciting jobs than they destroy jobs that is i think a long-term optimism but in the short term uh creation of the new jobs are yet to be known we don't know what jobs ai will create yet but we do know what jobs they will eliminate so we're kind of in a very difficult window where the decimation is imminent and the creation is lagging by maybe a decade so we have to deal with that the other challenge is that the jobs that ai will tend to replace are the routine jobs the jobs that are basically copy paste the same thing uh rpa watches over that and replaces that doing the same movements in the factory or moving carts around basically very routine work and and i think the jobs that will be created will be anything but routine because if ai is most successful at replacing routine tasks then if there are more routine tasks that people can go apply for the chances are ai will do them as well so so i think the main challenge is not so much a numbers game how many jobs are created and destroyed but rather what are the jobs that people were displaced can do and if they require training who will provide that training that's why i don't think ubi which is often talked about as the ultimate solution i think is part of the solution it creates a buffer for people who are displaced to have an income to prepare himself or herself for the next job but i think that income part of it should be required to get the training to get a job that can't easily be replaced so in my book i talk about what jobs can't be replaced and we earlier in this talk i also mentioned it's about creativity about compassion and creativity means we need to elevate people to use ais tools where people create an ai optimizes uh and compression means a lot more service jobs uh require human to human touch that ai cannot deliver so how do we create those jobs how do we provide training i think these are some of the keys i think the government can provide a blanket buffer that provides enough money to carry people over but also requiring some degree of effort in retraining themselves and also i think government programs should make it clear to people what jobs are going away and what jobs are not i mean it's actually very well known you know you and i know that a plumber job will be safer than auto mechanic right because the speed these industries are moving and we know which jobs ai companies are going after and we should really have vocational schools our vocational schools to stop teaching people or reduce the number of people in jobs that are in danger and the government should do that and the government should assist locational schools to reallocate their resources and re-prioritize their curriculum companies can do something but it's it's a little bit difficult because companies have a responsibility to shareholders a good example that i think went beyond that is amazon i know sometimes it's controversial because uh jeff bezos says a lot of things but one thing that amazon has done very well is provide a program that retrains its employees they will provide up to four years of training at about 12 000 per year for jobs that are not easily replaceable jobs like nurses or aeronautic repair jobs that they don't require you know you to become a scientist or anything but they do build uh they do train you for jobs that uh robots and ai cannot easily do but i think it's also difficult for companies uh to afford this program because amazon is essentially saying if you're an amazon employee we will train you even if it's training you for a job that amazon doesn't have and to me this program at least is i think a demonstration of altruism and caring ultimate care for the employees yeah how do you overlay the geographic issue on job displacement so in the u.s i remember reading a statistic on truck drivers if you assume there's going to be autonomous trucks there as a percentage of the population 10 times more truck drivers per capita in missouri than there are in california so is the burden on the worker to relocate to california if the jobs are being created how do you think about the geographic displacement uh geographic is a tough one i think given the degree of displacement that i believe will happen uh people will need to be more open to uh to to moving and but i think also another big issue is i saw the segment i think pbs did on on this job displacement and they talk to a number of truck drivers the other big issue is if uh if truck driving starts to being taken over by ai and the most most of the new jobs are in the service industry such as elderly care a lot of the truck drivers respond that there's no way they would do that job and that creates another challenge and then it creates a family challenge because assuming the truck driver is a man and assuming he doesn't want to do the job then and then assuming jobs available are service jobs like elderly care the family may be shifted and disrupted where now the wife who may have been a homemaker or some other profession now needs to provide for the family because she might be viewed as someone who's more open to elderly care so i think it creates some a lot of tearing based on the geographical job type family shift of burden between husband and wife uh i i think these are much larger than we imagined yeah they're also incredibly hard programs for governments to pass because you know and you know i saw you know trillion dollar funding in the u.s went reasonably smoothly a couple of times now but that's because it's coveted on issues like this i think many uh congressmen in the u.s would say hey i don't see employment uh dropping dramatically why i'm not i don't believe it's happening i won't i won't believe it until it happens but by that time it'll be too late so it's it's very tough yep is it fair to say that china is actually better equipped to manage the future of work disruptions that are going to happen then certainly a more laissez-faire system like the us uh yes i think so i think that is true china has had a history of managing transitions from the agriculture to manufacturing shift that created a lot of challenges and disruptions and china basically had a state-driven plan to us reassign many of the workers and retrain some of the workers it was still very disruptive to society but it did emerge successful the the challenge for china though is back then when it did the agriculture the manufacturing transition most of the jobs were state-owned enterprises so the government had stronger control over them now there are many more private jobs too so it wouldn't be easy at all for china but i would think the chinese people would believe and accept some government arrangements more readily than the american counterpart yep last question from the audience and then i want to do a summary here is about standards and again it goes back to some of the comments that eric schmidt has made about what the us needs to do to kind of compete and do well in an ai environment do you basically believe that there's going to be a bifurcation of internet standards 5g standards etc that's going to put china in the us on separate paths or do you see there's some convergence that can and should happen i hope both countries will converge on a pragmatic plan there will be some areas where u.s may choose to isolate its supply chain and own a supply chain there may be some areas for national defense or national security issues there may be some inefficiency created to to improve those metrics but i i believe most issues are commercial and are not about national security and countries and companies want to be pragmatic they don't want to pay more than they have to they don't want bifurcated standards that will cost more for everyone and and also i believe the efforts to decouple uh have not been successful i think china actually is becoming a stronger supplier to the world for for commercial products and i think that i think people should apply more pragmatism and kind of use use some uh decoupling only on issues that truly relate to national security and not over extend it because a world divided i think is not good for anybody yeah well said well said let me do this kaipu i always like to summarize my own takeaways from the presentation and let you at the end of it either upgrade or share any parting comments um you've got i got three pages of notes here i mean this has been terrific number one you're defining message about ai as excel on steroids about data as being the new oil as china having an environment where it can create and capture and utilize data that allows lots of innovation to uh to happen about the multi-sector nature of this innovation with ai and you mentioned a whole bunch of sectors healthcare education financial services that this is not a single sector set of innovations this is going to happen across a lot of different areas you had another message about the unique context in china you talked about ai number of ai engineers you talked about ai funding you talked about government policy but you talked a lot about entrepreneurship and this kind of unique almost darwinian environment that has bred an ability to succeed and excel etc that is uh that is unique in in the market um you talked about some of your personal learnings which i found fascinating um learning from apple that was uh maniacs on the user experience you talked about microsoft the understanding about organizations how do you manage large organizations you talked about google saying that speed is more important than size these are all kind of leadership learnings that we should all take away you talked about a mental map in decision making understanding the technology first don't fall back on the business right away but understand the technology the maturity the weakness etc and then understand the business issues what are the problems who is a consumer how do they buy etc etc and then a couple of last items which i thought were very insightful quote-unquote warnings for the us in many ways about the u.s needing to understand developing markets that that's where a lot of the growth is and you better be attentive to that and the u.s is going to become maybe less representative its own market of what's going to happen uh um elsewhere and then finally you talked about the future of work and the fact that this is a looming issue and we've got to be planned and thoughtful about it and don't um kick the can down the road to a future generation or the government alone that businesses have got to take a role in that those are the messages that i got i want to see if you have upgrades or parting comments uh thank you terry those are great summaries uh i think this conference is trying to do something that is quite important it is bridging between china and u.s two great countries that have complementary strengths despite the currently challenging environment i think these bridges are incredibly important a case in point in what i talked about is how china has learned from the us about entrepreneurship about business models to bootstrap the chinese style of innovation and i think it would be a disservice if american entrepreneurs choose to basically close their eyes on the progress china has made it a disservice from the sense that china is now learning from everything in china and the us and continues to do so and that the american entrepreneur if you don't look at the chinese innovations chinese business models you're missing 50 of the exciting things going forward so even for people who continue to have trepidation about you know u.s china relationship or any other issues it is important now that china has proved its success to spend enough time engaging and learning and i believe if you do that you will see that a lot of what you hear from the media from certain government officials are are not true i think china is a country with a phenomenal environment for entrepreneurship and great ideas and the people-to-people interaction and learning from each other is something we all need to do more of yeah kaifu what a what a great way to close the messages here because i think this whole idea of one plus one should equal three not one and a half and what we have to learn collectively and it's a great living example the importance of this conference and you know what we do at ucla listen i can't thank you enough i have learned so much in the course of about an hour with you and i thank you on behalf of all of our attendees our faculty everybody big thank you and i hope we can have you come back again soon thank you that'd be great bye you

Channel: UCLAAnderson

Views: 6,666

Keywords: UCLA Anderson, UCLA, UCLA Anderson School of Management, MBA, Bschool, Business School, Los Angeles

Id: bZ9rcyzU_Z0

Length: 97min 9sec (5829 seconds)

Published: Wed Apr 28 2021