女士們 先生們 各位貴賓我們會繼續討論這個謊言我相信每一刻我們都在保持這個謊言在世界各地的地方有 break-throughs in the technology of AI有些大部分的改變我們都在保持這個謊言我們都在保持這個謊言我們還要提供我們的想法我們也有一些藝術科學和研究研究我們都在保持這個謊言我們會討論他們的理解在於 AI 和政策及有優點的挑戰他們會介紹給我們 kind of future world will be faced withdifferent people are telling usthat future world will be totally differentfrom today's world.So I'm fortunate to havethese panelists with me today.Firstly, we haveProfessor Joanna Bryson fromBoss University of the UKand the Computer Science Department.And the next oneis the president and CEOof Splunk CompanyDog Merit.Thirdly is Mr. Liu Jinranrepresenting the new soft Chinaand also Mr. Joe Kuifrom Square Foundation Capitaland we alsoso welcome you alland what kind ofwe also have theKirstie Kajulatthe late president of Estoniaand faced with AIand especially in the next5-10 yearswill be faced withdifferent important milestonesand important notesand at this momentwhat kind of moment we are incould you describe for uscertainly you have your specialtyfieldsand my first questionMr. Liuyou are the first generationof doctor in computer scienceand you representnew softcomputer science companyso you are one of theartist who was in touch withAIand from your firsthand experiencewhat kind of stage we are in nowalso what will be thethe next 5-10 yearsby looking at the technologyby looking at the pastdecadeswe really set upa digitalized worldwe laid a foundationand infrastructure and platformsnumber one the computing costis being driven downonce it was very costlynow computing cost hasand storage has become cheaperand telecommunication hasbecome fasterand cheaperand also digitalequipment or devicehas become everyone's deviceput togetherwe got to seethis world connectivityhas become fasterconvenient and cheaperand thereforeon the basis of thiswe see morethe multiple applicationswe see e-commercee-learningwe got to seedifferent kinds ofsocial media and platformsand the connection betweenpeople and objectsand so realtimecheaper and cheaperactually and thishas led towethis led to some majorbreakthroughs like in AIread about AIand alsovirtual realityand we see upheavalsups and downsbut why AI has not been turned into a realitybecause we do not have a foundationor infrastructure in placehowever nowadays computingnowdays we can do computingto do weather predictionforecastand in the instantbut oncetodayto predict the weatherand storage also has become cheaperanother major changeis the extractionof data has become more proactiveand cheaper as welland once when you want to get datayou have to purchase the databut now you have free datapeople are contributing dataeven about their privacytheirtrack recordtheir lifestyletheir contributing all theseand in digital societyand you have more accuracyin identifying different individualstheir behaviorall these changesin discussing AIthe foundation is totally differenttoday than yesterdayand once we talked aboutwhat kind of algorithmand once we thoughtthe algorithm was not speed enoughthe speed is not a problemand onceyou did not have enough preconditionsdata informationbut you got sufficient data informationand so this is unprecedentedand what is AIand what kind of legal statusshould it haveand ethical issues surrounding AIthis is something we never experienced beforeand so becausetheir datahas given us a totally new worldnow worldwidewe see more and more populationliving in anotherspacetheir commercial behaviorgovernanceand it's totally different from yesterdaybecause of the differencesso they turned into economiesthey turned into culturesthey turned into some major challengesand issues were to discusstalking about the next 5 to 10 yearswhat will be the biggest major changewe will seenot to talk aboutmore lossaccumulationcheaper and better fastercertainly this is something we will seebut in the next 10 yearsafter 10 years our understanding about the whole worldwill be more accurateand the relationshipbetween different objectswe will have a clearer pictureand put togetherand if we come up with a new algorithmthen regarding every sectortoday we will be talking aboutinternet and peopleand their connection with peoplenow all these sectorstechnology has becomea disruptoror promoter of the internetso in the next 10 yearswe will get to seesomething we never got to see20 years in the past20 years or 30 yearswe will come faster and fasterbecause of digitalizationand better accuracyand more business modelsnew business models as wellChina for example on these kind of platformsmore and more Chinese companiesare coming into beingand their productivityis being enhancedand entrepreneurs of startupsthey are becoming younger and youngermore quicklyand this is something we never experiencedespecially those who do not have any capitalonly got a brain powerand they could have a startupand this is somethingwe will get to seein the next 20 years10 years digital startupsto accumulate wealthto come up with new business modelsI call it something new normalnow I have a question for Joannayou started in the 80syou got involved in AIcomputersyou have started your researchconcerning tocomputer and AI since80sthat's a long timeI really want to know your feelingabout those biggest changecompared to those timeswhat is the most exciting thing lying aheadoh well okI think the biggest changeis not because of artificial intelligenceit's not the algorithmsbut it has been as everybody saysthe expanding of the computersthe expanding of the internetand soand then of course since 2007the expanding of the personal dataso it isn't been the detailsof AI that's changedbutin the lasttwo or three yearswhat's been changing radicallyis the governanceit went from being toysto changing the worldand we've seen it changein democraciesthat there's been a challengeto democracyand so now people pay attentionalso there's the changeboth on both sidesthe great firewallthere has been a changeof the tech companies becoming morepowerful than petrochemicaland then manufacturingso that's a big changethere's a big change in power structuresso I think it isn'tand I loved your videobut I don't entirely agree with itit's not that artificial intelligenceis a bunch of peoplethere was a focus on these robotsartificial intelligencehumans get controland informationover their world including each otherand so I thinkthe challengesthe biggest challenges going forwardthat we're spendinga lot of time onishow do we handlethe problems ofaccountabilityI actually don't think we needa lot of new lawsI think what we need is tohelp people to enforcethe old lawsand to hold accountablecompanies that were notdoing the correct thingswith respect tobeing carefulso some companies for examplefacebook became very powerfulmaybe even not entirelyintentionallyand thenthey weren't following the best business practiceand if the courts find themincorrectthen they should be held accountableso I thinkthat we'remaking companiesare incredibly powerfulthey're very rich, they're transnationalwe need to figure out new waysto negotiate with thatI don't think that was really the question you asked meso just to say the technologyand before this sessionI had thought this when I first heard someone sayI would be most excitedif we could do live translationand everyoneeverywheretalks in their own languagelike we have herebut we use peopleI think I keep expectingat one of these meetingswe're all going to have these headphonesand it won't be as good as the peoplewe can put something herewe won't get the idiomswe won't understand all the piecesit's still worth learning another languagebut it will be likegoogle translate onlineat least we could get the wordsand kind of guess if we know enough about the cultureso I wouldI would loveto have everybody speakin their native language all the timethat would be greatwe're looking forward想請問周葵先生I want to ask youMr.周葵very famous startupcompany founderand also the investorswould you please to share with mehowwhat are the fundamentalor the most important changewe are experiencingand in your visionin the futureof course you will selectsome major changeshave great impact on the companieson the industrieswell we are in the processof informatizationtechnology is a big stepof humanity's civilizationeverything could be digitalizedwe could stay connectedwe can pull things togetherfor algorithmand computationand a lot of things are enabledthe symbolof the civilizationis savedat cloud yesterdayin Shanghaiwe invitedamazon tencent googlewe saidthe peoplewisdom could be calculatedand computed and saved at cloudsuch kind of wisdomyou knowin china we say thatold elderly seasonsare most wise peoplebut you know the cloudstay young foreverand the brain of the cloudis expandingand exceeding the individual capacityof a single brainof a goalis one of the milestonesand a chance is so difficultand i believeit will have a lot ofchallenge to peoplewe need to get used to many changesthe topwisdom in the societycould be accessed by everyoneat cloudmaybe it's not todaywe already see such a progressmaybe some of your personal lifechoiceyour personal choiceyour career choiceneed to get adaptive to such a changei believethese are the changeswe are having nowand we can form such a structurewe may have a very verysuper social brainin the cloudwhich is able to support everyonewell i think thatindividual personwe get techwisdomwhich means that the mobile phonesyou can do it on your mobile phonewhich cannot be imagined in the pasti'm able to see my locationthe accurate locationwhich wasyou cannot imagine 20 years agoi believethis iswhat we have nowadaysand in the wisdomof the informatizationpeople believe that connectivityisgrowing quicklyis also the accumulated wisdomare also growingwell withinyour ownyour own visionwhich industry or sectorwill enjoy the fastest growthi think industrystill are in difficultieswhenever we talk about the technologicalrevolutionit was the change of mobilitywe know that mobilityis one of thehigher cost of human livesand mobilitytransportationtheautonomous drivingfive years agoi thought it was not difficultyou know nowadays i think it is muchless timewe already have somelicense for the autonomous drivingmaybe in the next five yearsi could even useautonomous driving vehiclesand you can try ityou can use it in the next five yearsor less in some regionalrangetransportation or mobilityis one of the topic of people's lifewhich is usually cost some moneyhealthcareit's difficult to educatea student to become a doctorand the doctor has toreceive education in the past eight to nine yearsbefore he isqualified as doctorbut such a medical informationand knowledge could beaccumulated and used byby the machineswhen this brainor the machine brainis able to help youyou know that so we can have fastertraining of the doctorswhen providing treatmentto the patientsand they are moreaccurateand they will have less mistakeslet madebut you know this is a rising partis just startedthe other industry or sectorstake a securityas an exampleyou know that we have vulnerabilitiesand the machine brainhas less vulnerabilitiesit is able to identifyeverything in its memorybut i use itto serve for the security purposeof course it brings new problemsand challengesthe other thingsfor example China is a large manufacturingcountry whybecause China has a large populationbaseand i used to workwithin a plantthere are so many assembly lineand the testing linein assembly linewe have visual inspectionat the planthumans are slowerthan the machinesin the visual inspectionnot only the speedbut also the qualityfor example the apple mobile phoneand it is notthe job is not done by peopleit must be done by the machinesthere are a lotof sectors and industriesand we will seepenetrationof such a technologyanywaythe companies will be driven partially by AIpeople say that AIis not a special industrybut it will go into any kind of industryi know that Mr. Xiaoyou areand i know that you are one of the pioneerin AIin combination with internetMr. Joe talked about securityprobably you have more things to saybut in terms of financeor other sectorswhat do you think are some surprising changesyou want to tell usin the past several yearswe do see radical changesin the world everydaypeople feeldepressionin fear ofthe possible changesor replacement by AIyou know that chinese peopleare very smartand we develop practical sciencetechnologythe application of AIin chinaat presentwhich we see very clearlywhich can create most valuewithin the commercial useis the advertisementthe advertisement push upthe other thing is thatin the new financeit already creates new valuewe do see the profit driven by AIthe autonomous drivingwhich is still on the experimentwhich is not readybut in finance we already have itin terms of financeand there is a conceptyou know that in chinawhich is the earliest industrywhich isis digitalizedthat is a bankor infotainmentizationin the past we had a large machineslarge computersvery good storage of databut how to use the datahow to apply datawithin the financial sectorwhich was not discussed in the pastchinese populationbillion 1.4 billionpopulationyou know the supply demandis not in right balanceespecially when providing financial serviceto the individual in chinathe integrity system in chinais not quite soundthere is an inadequateof integrityor the accredited ratingdata of that in chinaonce AI penetratedinto financecan create a lot of valuethe first one is in terms of antifraudand the background checkand the resultof using AIin financial industrycan drive down your costwhich means bring money to youin the small loan operationyou know that usually in traditionalindustrythey do not wantto serve the individualbecause they have a lotof costthey have a lot of costof application for claimingback the loanand the all office could be addressedby the AI solutionin the past years we followed closelywith the technologyit is truethat from the customeracquisitionand how to pick the right customerfor examplewhat we can offer to themfinanciallyand also we use some AIrecommendation algorithm to our customersthe other thing isbefore the approval before the loanand antifraudwe talked so much aboutthe data generated at the terminalswhich can help us toidentify some small risksof a fraudI still rememberseveral years agowe find out one caseof a fraudand in the past we can onlyidentify the fraudby hundreds of thousandsof examplebut now some small possibilityof fraudcould be detectedby several casesself-learningchecking the ordersand the location of the transactionswhich can greatlyprevent riskand in ourapproval 90% of themare automatic withouthuman interferencepost loan managementwithin our systemand our organizationis not very largemaybe tens of a billionit's the quality of the assetthe newthe asset from last monthhow much percentage is goodhow much of them were not workingyou know that there are6000 variablesthere are so many variableshow to make the analysis by the peoplewe have machine learned automaticallythey can identify the MPLwe are able to optimize the modelsso that in the post loan managementwe can accurately identify the riskto make ourAUM in a healthy waythe other thing is the claiming backof the loanand we also use the AI technologyand we can lower our costand we can make ourfinancial service more inclusivewithin the industrytherefore in financial sectorAI has one single applicationbut already a good symbolshowing that the whole industry chainalready receive the benefitsthat in the coming dayswith more practical applicationof AI we will see efficiencygrowth in the societythe service received by uswill have lower costyou have two productsone is called ego eyewhich is very interestinganother expert at datayour company is very popular nowis analyzing collecting dataand help other companiesto make better choiceso what is your opinionyour perspectiveof what kind of moment we are inand what is the biggestto change lying aheadso i think likeall the other panelists saidwe are in the very early daysright now of what is possibleas much excitement as there isaround digital transformationand IOTthe number of processesthat truly are censoredand the ability to collect that datais still really earlyand nascentwhen I look forwardI think for all of usto have a healthy societythere is always going to be risksand benefits to a new technologywith every progress comes risksand benefits and AIand machine learning have got that same edgeof good and badbut part of the benefits should behow do we expose as many peopleto participate in the way of this comingand what we seewith the many organizationswe are working withthere is three core aspectsthat I think will helpthe broader base benefitthe first isopen access to datawe have all been talking about data on the paneland I view data as the oxygenfor machine learningor for AIit is the backbone, it is the fuelwe will all need to continueto progressour overall attempts at machine learningand artificial intelligenceand right now there is a lot of databecoming available as everything becomes censoredbut I think we have to strikea healthy balance betweenand anonymity of data and protecting rightsand still making data availableso we can see the gainsand healthcare and retailand financial servicesthat are possible if we really have accessto massive broadbase of non-structuredand structured dataI think hand in hand with thataccess is the trustworthinessof datawe all hear reports of manipulationthat is now possible in many different frontshow do youand not just data but then obviously the algorithmsthat operate on the datagiven that there is a very tight virtuous circlebetweenapplication different algorithmsand the data sets that you are manipulatinghow do you get visibility and truston the lineage of dataobviously blockchain and distributed ledgercan be one of those aspectsbut it goes through many stagesit has touched many timesand if you can't trust the foundationof the element that you're working withor you don't know where it's beenand how it's been enhanced in some wayI think that starts to minimizeagain the potential for societal gainbut also could take AIand tracks that we wouldn't always understandand the third piecethat I think is absolutely criticalthat lots of people have been talking aboutis how do we lowerthe bar and capability setso that more people can participateso we can democratizedata democratize machine learningso that the average citizenthat's not a data scientistthat may not have been trainedin very deep computing capabilitycan still benefitand I think we're seeing a lot oftooling be birthedthat is able toboth represent algorithmsand data setsin ways that our storyprocessing brainwhich is not a logicprocessing brainthrough evolutionin ways that our storyprocessing brain can actuallyattached toand if wedo it properlythen againSponsored uhื่is naught 정도anduh公開fordatanoneyrpure并且在更好的方式和更好的方式上我们的变化和变化能够达到最佳的影响对 最佳的东西和最佳的东西我们将会在一起我们没有选择我们没有选择到刚才说 其实从 data 的这个 use所以从 data use perspective我们仍然在最早的 stage我们的报道说根据大致的大致的大致的大致86%的大致的大致的大致并没有大致的大致甚至2020年甚至40%的大致并没有大致的大致并没有大致的大致但是85%的大致会带来变化的有些专辑的机会带来很多的差异有一个问问是刘济然对于车捉的事情 punish rates like oxygen盒toryand put togetherthere will be a new engineand to maketo upgradethe different industriesThe different sectorsbut for some sectorsthis could be disruptions所以我的問題是,在視乎社會的改善和改善的影響,我認為這些改善的影響會很大,讓我舉一個例子,在國際上,我們在過去一百多年來,我們打算給我們人們更多的健康,更多的優惠,但沒有國家能夠保護生命,因為我們的貸款和服務貸款都分割了,我們不可以問醫生為何會給我們這個薪水,為何會給我們這個薪水,而且在不同的城市裡,我們也看到了病毒的影響,因此,我們會看到繼續的影響,在不同的國家裡,但他們是關於我們的醫療系統,首先,我們看到了很多分別,沒有很好的接觸,因為我們沒有很好的接觸資訊,在任何城市裡,我們也不會知道,哪個醫院是最適合你,哪個醫院是最適合你,你也不會知道,你只會知道哪個醫院是最適合你,所以我們永遠去到最適合的醫院,但最適合的醫院,並非是最適合你,他們不可能有醫生來治療你,他們可能會很難以治療你,在這種背景裡,所以AI,在未來,一定會進行自己的 role in medical care,我認為有很多的做法,要做到的 role 要做到的,首先,我們有不同的目標,是如何打擊醫院的醫生,但這不是我們的目標,我們想把最適合的醫院,我們不想AI打擊最適合的醫院,如果我們能把最適合的醫院,打擊最適合的醫院,只有5%的醫院,他們會給我們更多的 benefit to the society,因為,很多人,70% to 80% of us,我們的治療 are common ailments, and chronic diseases, or treatable diseases, curable diseases, but you do not get cured, you do not get the right diagnosis, it doesn't mean that, by going to the visit of the best doctors, you would get treated or cured, that's not the picture today, and also in China, we have the regional disparities, at the county level, many medical doctors do not hold a degree, medical degree, and we have a farmer-to-farm treatment, we call it bare-footed doctors in China, and so in medical care,AI, if we can turn the worst doctors into the best ones, if we can turn the best doctors into many more, how we can turn best doctors into many more, they can turn their methodology into algorithm, their medical plan can be connected to other doctors, so the prescription can become best practices to go to most remote areas to treat people there, and I think this is something we need to pay attention to, but we have a long way to go, and from China's perspective, in medical care, firstly, our population is beyond their affordability, and because of the diagnosis, it has got a problem, it's not just the drugs are expensive, the most expensive part is the diagnosis, you got the wrong diagnosis, and then you were prescribed the wrong medicines, that makes your treatment very expensive, secondly, your disease could be treated in a village, at the county level, but you took a train to Beijing, and to wait in Beijing for one month or two months, and that made your medical care very expensive, because there's a lack of trust to hospitals, you have to move to bigger cities to get treatment, therefore, in medical care, if you do not go beyond medical care, even you just want to adopt some reform measures to ask a doctor to be cheaper, to ask a hospital to be cheaper, you cannot solve the problem, because our doctors are like artists, doctors are artists, they are artists, so you have an eye on a doctor, you just want to go to him, but we need artists, but we also need engineers of doctors, and engineers can deal with the most basic problems, and the payment can also make some changes through AI, I think AI can play the biggest role, and there's the biggest possibility for AI to play a role in medical care, and for the society, we can feel the benefits very easily if AI is deployed in medical care, so Mr. Joe, talking about the economic structure changes, what kind of disruptions we will witness in the near future, and Mr. Liu talking about medical care, so which sector will be transformed thoroughly by AI? I quite agree with what Mr. Liu said, it's about inclusiveness, I mentioned AI is to be used by all of us, and other sectors also have these kind of features, for example, medical doctors, teachers, education, I think that would be a big sector for AI, between teachers and students, they may give students assignments just like doctors, but we require skills on the part of professors, the communication is one-to-one, on a small scale, and AI, regarding knowledge per se, regarding the teaching of knowledge, for example, my personal experience is one teacher teaching dozens of us, and 90% of my homework were correct,10% were mistaken, but I spent a lot of time on the correct items, but we put students into batchments, we can ensure the most basic quality, but in the future, we will have a tailor-made teaching education, they won't be luxury as well, and tailor-made won't be just for luxury, and teaching as a process, in the teaching process, you will face with different kinds of mishaps, unexpected events, but a machine can do management on the mishaps, and after they discover the mishaps, the people will step in, and when machines got involved, when there are mishaps, they send off a signal, and the human beings will step in, and this can happen in many sectors, and AI can discover mishaps in the teaching process, further kids started to cry, and then the machine will send out a signal, and the teacher will come over, and the teacher will come over to intervene, and so this kind of thing will happen in many sectors, so I call it major changes,Sotiana?economy, industry, or social order, social structure.Oh wow, thank you for that question, that's one of my favorite questions right now, I think this is really a huge issue, and I want to say in the first place, I don't want to make an open prediction, because what we do matters, and that's why I travel, I think it really matters that we get engaged, and we use our brains, and we try to build a better future, but specifically I almost want to take the question back to Professor Liu, when you say make the worst doctors the best doctors, that sounds great, I get really excited, that's why I got into AI, but then because I've been learning about economics, I know that means everyone can be a doctor, Does that mean a doctor is no longer a prestigious position?So one of the things that we're worried about is artificial intelligence affecting inequality?And I know that this question is very different in a traditional capitalist versus a traditional communist society,but it seems that social coherence comes from the ability of people to move between jobs and to have trust, so that there isn't just an upper echelonand a lower echelontotally separate from each other.We want a continuum.So I'm not saying this is not a challenge, it's a question, I sincerely wonder what all the consequences are,although I'm working for them too,but this is a big, big issue.The second part of it is I mentioned before,the transnational question,when there is one big winner,and again China is famously the exception,that's why I mentioned the firewall,that they have been able to createa tech sector here separately,has been really interesting,but in general,for the rest of us outside of China,we have all the big companies in one countryand they're getting a lot of wealth,and even in China,a lot of wealth is going to the mirror companies,like Tencent.So how you handle that in your economyis a big question,especially within one country,the government can work,but outside when it's multi-companies,multiple countries,then there's that,who is the government then?How do you agree how to deal with that wealth?So and then finally,there was another piece,I wanted to say,the economic social council,oh finally,the AI itselfand we,there's been a little mention of this,it shouldn't be the thingthat has responsibility.So again,this goes back to the person thing,but people talk about makingAI a legal person,so that the driverless car,for example,has its own liabilities.It's a convenient thing,there's called a legal person,like a company,and so when Professor Liu saidthere was no precedent,some people say companies are the precedent,that they're a form of AI,but when a company is not,when the people who own the companydon't really care what happens to it,this is called a shell company,and when we have shell companies,then we have corruption,and I was very excited by what you saidabout the looking for fraud.So you can create fraud,you can say build a building deliberatelyso that it goes bankruptso that you hide money,circulation.If the reason that can happenis that no human,so justice works by applying,for example,jail,or a loss of face to a human.The machine doesn't care,and we cannot make the machine carein a way that we can't un-make,because we build the machine,it's not like a person.So with us,we are built,even fish are built to carewhat the society thinks,so we care.So we have to maintainthe legal personhood with humans,and if anything,we've overextended it already,that's why we are the shell companies.So I think that's a very essential partto the economic and social order.我覺得這個有意思的就是說This is very interesting,and we do see some many exciting changes,and the series of consequences,and they rise and go down together,and that's why it's highly significantto discuss them.We need to get preparedfor welcome these changes.I want to ask Mr. Xiao,and Joanna have talked so many things,and I cannot elaborate all of them,and these are great problems,and Mr. Liu,you talked about the doctor's issue,and you know maybe in the future,the banks don't need people,people often talk about employment structures,and it is a trend,and how could people becomeAI-driven people,you know companies could becomeAI-driven companies,and people might be phased out by AI,and how to help them to find a new places,and 70% of the jobs will disappear,of course the data are different,and so what is the view on this?This is one of the trend,people,you have the worries too early,and even the replacement takes place,it takes time,and many historically jobs were disappearing,and but new jobs showing up.In the past we had no programmer,we have no product managers,and when we are facing to the job,to this problem,and the change will not be that sudden,even though the society is in fast changing,but it is still a slow penetration,and you know that people are the speciesmost or highly adaptive to the world in the earth,in the long term and the middle term,there is so much a repetitive labor or the manual work,and very likely we are going to have more creativeor innovative people,there is so much a population,maybe people can take off,can have holidays one after another,and we take terms to go on holidays,and what do we need,and if there is AI help us to have our daily lifein good order,and like our food accommodation,I believe AI makes people happier,and so we can,we are free law of the troubles and repetitive work,we can be with our families,we can develop our interest,we don't need to invest our time in the resourcesto do some mechanical or repetitive work,routine work like clean up and cooking,and I think that we can do more thingsand interesting things and changes words,and what kind of people,and from now on,you can't expect what kind of technology you want,and what do we need to save,and so that you can get prepared for the future,well what we need to have,or what kind of things we need to learn,and you need to follow your own interest,to get adaptive to the social changes,and it's not that you do some repetitive work,and it is true,it's very likely you will be replaced by machines,and you need to show respect to the future,and you can try something unknown,and challenge the future,and change yourself to get adaptive,and prepared.I'd data to company,and then help them make the smart choice,position.Do we still need entrepreneur?Maybe you can,you can tell the data will tell them how to do that.Your data is not intelligence,data is data,so there's still the,going back to the earlier comments on,we are not always as creative as we could be,in the 1800s if you told a farmer,the world is going to go 90% non-agriculture,and there's machines that will do everything that you do today,but somehow we're going to still have global unemployment under 10%.I think very few people would have rushed forward and said,fantastic,I can't wait to imagine what those jobs are,so we do find a way to adapt,but it is,it's always scary,social economic changes are not smoothly taken up,and what can we do this time to get in front of it,what can we do on skill development,and rapid retraining,because we will lose jobs,those repetitive jobs,that the industrial revolution created,will likely go away,and we need to help our population become,we need the right frameworks,and the right delivery,so that people can quickly get into new areas,that they wouldn't have imagined before,but I think from a society perspective,we have to shift resources to that.I don't think ten years ago,we would have imagined that there would be billions of applicationson the iTunes and Android storesthat people are making some economic living from,but that still required people to understand computingand programming,and data is really just,again,the oxygen for that.So I'll go back to my core point onhow do we make data as accessible as possible,and I'll ground it with an example.There's a group called the Global Emancipation Networkthat's working on a difficult problem,human trafficking globally.It would have been impossible to have solved 15 to 20 years.I think for a number of reasons,one of which is data was not very open 15 to 20 years ago,and it's largely unstructured data,but if you can tap into the hundreds or thousands of sourcesacross travel industry,retail industry,different local agencies,police agencies and others,patterns can emerge very quicklythat show who the victims might beand who the perpetrators might beso you can actually be proactivein trying to solve this very difficult problem.That only happens with broad access to data.And again,we've got to balance the anonymity needswith that access to data,but I think if we look at the pastand we're willing to lean forward,AI and ML is coming.How do we participate in it?And let's focus back on what do we have to doto make sure that the broadest number of peoplecan benefit through open data,through transparency and trustworthinessand through the skilling necessaryso that people can get rapidly retrainedand we don't have the dividethat I think is causing a lot ofnegative ramifications around the globe todayas people get nervousand try and do what we can never do,which is try and go backward.You can't even stand still,the world is moving,so how do you move with that worldgiven that it's continuously evolving?We have no choice.We have no choice.刘先生您觉得如果...Mr.You know that Mr. Liu,what do you think?What should you teach to your kids?What will be still be usedin the next 30 to 40 years?What are the skills and the capabilitieswe need to grasp?Anything,emotional exchanges,I believe such kind ofmajor skills are highly secured.For example,interview,like this dialogue,interview dialogue,maybe not,you think it's also replacedbecause you know the moderatorsif highly logicand highly computed,you can be replaced by the algorithmand in the future,technology in the futurecan have a very similar expressionlike people and only very deep emotionand you can have different feelingwhen you talk to himor talk to this person.For example,if you want to make friends,you can make it's difficultto make friends with machinebecause the feeling,it takes a long time.But you can't make friends with machineif you look at these moviesand filmsand people can also feel in lovewith the robots sometimes.So,in nature,at emotional level,the computation is based on logic.I,the other viewI fully supportis like this.In fact,when a portion of jobsdisappear,of course,are created,in the past,we don't have so many data analysts.We didn't have so many peopleworking as programmersand in the future,on the platform of AIand we will call it data democracy,AI democracy.What does it mean?Any kind of industry may use it.Any skills may use it,which is available in any companies.In the past,we are a manufacturer.We had loads of workers.In the future,we will havelove designers,engineers,data analysts.They will become a new profession.To me,you need to think about yourself.Do not think about the world.You don't need to worry about the world.You worry about yourself.You lose your job.It's not the world is changing.It's because of you.You didn't get prepared for the changes.So,I hope next yearI will still be here,will not be replaced.You have two to three minutes.And this is a very,very big question.There are so many dimensions of it.And we can only touch the surface of it.We already have some inspiring idea of you.Would you please use some wordswhat we should get prepared quickly?Mr. Liu said you prepare yourself.And what is most thingwhich made you worry most?What kind of things you need to get prepared?You need to get prepared for yourself,for your society?Well,I want to mention one thing.That is education.Education is delayed.You know that the content of theeducation is delayed.What you learn today will be usedin a long time,days.And I learned what I will be usedin the next 10 or 20 years.But you know the test bookwas made 10 or 20 years ago.So,there is strong conflict there.I think education.In China,to a broader sense,we need to have a regulatoryand a legal framework.Coin has two sides.You not only see the positive benefits,great changes in valueto the society and the economy.The other side,once it isutilized by bad guys,it issomething we should be fear of.I watched a movie.It was about aJoan and UAV,which can becontrolled to killing people.You can't imagine that.We need to get prepared.If abused in financial sector,it is also scary.I know.So,quickly to answerthe learning question,I wouldlearn to learn.I think it is still worth goingto university.What specifically you learn,it will probably not be usefulby the time you graduate.I think it is important tolearn a group of people tomake the contact.University is more aboutconnecting the networks.I think this goes back tothe most essential thing.I think we will buildrobots that will fool peopleinto falling in love with them.But I think the people whowill be the mostsafe andpowerful are the ones whoconnect with other humans.Let me tell you one more storyabout the jobs.We have only 30 seconds left.I bet your story is fantastic.We will read your article.I will repeat what you said.I think you are eithergrowing or dying.So,what can you doto be excited about change?It is always a constant change.And we are just seeing itincrease because the evolutionsin the digital world arenot gated by DNA and genomes.The cycles aremuch faster.So,I think curiositycreativity,interpersonal relationships.Learn how to learn.But underneath that,we haveto love changeand embrace change.And the more resistant we are,I thinkthat's the easiest way to get eclipsedand fall backward.Thank you.That's a very great conclusion.非常感謝各位嘉賓今天在這裡給我們分享他們的觀點.確實是Thank you very much for your sharing.And this is a big waveregardless of your personal view.And the people sayit's also a roller coaster.What should we dothat is to have your safety belt?And we need tofollow with the big wave.Being in the forum.Thank you.


Live from San Francisco, extracting the signal from the noise, it's theCUBE, covering Oracle Open World 2015, brought to you by Oracle. Now your hosts, John Furrier and Brian Grace Lee. Hello everyone, welcome back to theCUBE live here on Howard Street in San Francisco. We're shutting down everything in San Francisco for 60,000 attendees and people all around the world watching the keynotes from Larry Ellison and Vishal Sikha who kicked it off as the CEO of Infosys. I'm John Furrier with SiliconANGLE. This is theCUBE, our flagship program that's powered by SiliconANGLE Media, SiliconANGLE.com, wikibond.com, research at SiliconANGLE.tv. I'm the founder and I'm joined with my co-host, Brian Grace Lee, research analyst at wikibond.com, with the cloud, Brian Kino from Larry Ellison, kicked off by Mark Hurd who introduced Vishal as their number one partner Infosys. And obviously Larry will get to Larry in a second, if you saw, is a legend in the tech community. He was doing web services, talking about the API economy going back to the early decade of 2000, 2001 timeframe. And that really is the genesis of service-oriented architectures that led into APIs, that led into the cloud. So great to see him on stage. I thought that was a fantastic addition. Super great guy, talking about human intelligence. I thought I'd love that angle. But the show is all about Larry Ellison. And Larry Ellison brought the meat on the bone and he went deep. He kind of was philosophical Larry. And my takeaway from Larry Kino was, hey, let's step back and understand reality, security. It's all about security. So real big message on the security and the M7s and the hardware, all the sun investments and really pushing security down the stack. That was his primary message, really highlighting the silicon software. Silicon security is better than operational security in the US. Got a little long-winded, blew through his slides, knocked down some other stuff, multiple private clouds, management cloud announcement, but really silicon secured memory, the stolen credit cards, fear and gloom and doom. What's your take? What's your assessment? You kind of roll in your eyes a few times. He said Splunk's not in the cloud. That's a factual mistake. They are in the cloud with Amazon web services. Other than that, he's only one. I saw one mistake. That was a Splunk mistake. Other than that, he was pretty on point, very philosophical. Yeah, no, I mean, he was trying to make the point. Security, security, security, a lot of trying to put some fear into people's eyes. I want to say there's a certain amount of fud, but a certain amount of it's just reality. Security is very hard to do. He was basically trying to push, you need security down at the hardware level, and you know who has security at the hardware level? Oracle does. That's been a huge push this week. Yeah, and the other notion that you've been talking about is always on security. And he was saying there shouldn't be an on-off switch on security, so that's ridiculous.  I'm glad he brought up the overhead comment, because that was the reality. No one really had security on because- Well, we heard it earlier this week. It cost you 80 to 100 times the performance. People just weren't doing it because it killed your performance. So, you know, he said there's zero penalty. That's yet to be seen. People are going to have to start doing some benchmark testing. Would have loved to see a live demonstration of something in the security space, but you know, very bold vision, absolutely. Also, we learned some new information about Larry Ellison. He makes his own slides, which is good to know. I mean, he's the kind of guy he's hands on, but really to me, I saw Larry Ellison up there saying, look it, I've been in this industry a long time. Security is broken. I don't know what's going on with it. It's got to be fixed. And his answer is to use the engineered systems, the horsepower of Spark, the horsepower of the Sun acquisitions, the horsepower of all the innovation around engineered systems and get the software and the silicon. Silicon security in memory, silicon security secured. That is a key message. Now, this is a time where we can actually pull it off. More cores, you heard from Intel. So this might be a shift in the security model.  So your thoughts? Well, I think what this is going to do, this is going to, you know, we just heard the fire engines going off. This is going to light a fire in the security industry because they've been saying for a long time, you can't keep up with the zero days. You've got to be more predictive.  You can't change it fast enough. So it's going to be fascinating to see how the security industry responds to this. It's going to be fascinating to see the proof points because the security professionals are trust, but validate they're going to want to see how this really works. We had a great crowd chat. We had some folks in the crowd chat filled on a particular highlighted the big time system sales, 15,267 engineered systems shipped to customers since October 2014. It was like 10,000 since then, 7,000 exadata sold. So like obviously the hardware is working. So the hardware software combination is working. That was a big theme. Also he brought up the security kind of philosophical conversation which should spur a lot of consultants kicking their slides and refreshing their narrative. But he talked about stealing data versus changing data. This is really, really a big deal in my opinion because data in motion is all about real time and getting access to data and changing data whether it's systems configuration data or other data is actually now the new threat. Right, right. Now it's a huge thing. I mean like going back to your point about engineered systems, we're seeing this across the industry. Customers are buying into the notion they want to reduce friction. They want to reduce complexity. Whether it's, you know, the exadata systems whether we're seeing with V blocks, we're seeing it with Flexpod with a bunch of the other. Everybody likes the idea of engineered systems and quite honestly they like the idea of that simplicity that cloud's providing whether it's private or it's public. They also talked, again highlighted the price performance issue again kind of hinting at the earlier comment in Sunday about they will never lose on price to Amazon. So that's a big challenge for the Oracle employees. Again, Larry said stuff on stage and kind of trills down to the employee base don't lose on price. Do you think that's a reality? He made a bold statement today. He said they're going to be, they're dedicated systems meaning nobody else is on that system. Those systems are running maybe 10, 15, 20% utilizations are going to be half the price of what Amazon does for their shared systems. Off the top of my head that mask is hard to figure out but I really want to see it, I want to see it but it's a bold statement. It's a bold statement. They're also talking about multi-tenant cloud as well. That does, how does that jive? Right, now it's, you know, look, Larry's trying to make some very bold statements that like this is don't let price be a barrier. Don't let security be a barrier. Don't let movement of data be a barrier. We're going to help you take care of those things. My favorite sound bites from the keynote here from Larry was let's get rid of the on off switch from security. The always on security message really is a good one. I love the story and I think the consultants, we were talking, the consultants business is going to boom right now. Well, really what it's going to come down to is how much do applications have to change to do this? Because if, as Larry said on Sunday, most people don't turn on their security, if you're going to just move your application, is it still going to work? That's the question I've got. If I move it to a place that has security on when I had security off, does my application still work? They got to hope it does. Yeah, the encryption's always been a tough nut to crack. Obviously, there's always one vulnerability. That's the keys. And as long as the keys are taken care of, the end to end security play flies in my mind. And I think anything pushing down the stack that frees up the application developer will be a winning formula. Application developers right now do have to wrap security around it. What does that mean from your standpoint? Does that take a burden off the application? Do you think it's going to take more time? No, I think the application developers don't want to think about hardware. So if this is there and it can be provided to them as an API, great. This isn't going to all of a sudden make them start thinking about hardware. They haven't wanted to think about hardware. What really was interesting to me was he made a bold statement. He said most of the cloud providers are looking at your data. I don't believe that. I've worked at cloud providers. Those cloud providers will be out of business if they're doing that. That's a bold statement. I don't know that I completely believe it. They have to be letting you keep your keys. They can't see your data. They can't have those kind of breaches. They'll be out of business overnight. That's a philosophical one. Technically, if they can't look at the data, we've heard of Uber people looking at the God, the God switch, looking at the data. So technically, if it's possible, they might look at it data. So is anything possible? Anything's possible. I mean, they talked about an audit service where Oracle can look at your data. They can look at the transactions going on. So again, it gets into semantics. But again, it's trying to push that idea that we're more secure than anybody else. As we're in the middle innings of Oracle Open World, we're getting the meat of the story here. It's an Oracle Cloud on-premise software as the same as the public cloud software. That's their mission and everything in between that's hybrid, all powered by engineered systems. It's a platform play. It's a platform war market. Oracle has a cloud business. They got numbers, they're performing, they're doing well. Again, Larry Ellison's going deep, the deep dive on security. That was the main story from Larry Ellison. Obviously, if you shall stick up, they're standing up there saying, this is the new order, this is the new application market. It's going to be a really interesting story to see this unfold, Brian. Great stuff. We are here live in San Francisco for Oracle Open World's exclusive coverage from Silicon Angles theCUBE. And for more information, go to crowdpages.co slash 0015. That's for putting all the videos. That's for putting all the conversations. That's where the crowd chats are. Go there and get all the information. Go to wikibond.com for research and go to siliconangle.tv for the videos. Thanks for watching. That is the post game wrap up, post keynote conversation here in theCUBE live on Howard Street in San Francisco. Thanks for watching. Stay tuned for more interviews here live on theCUBE. We'll be right back after this short break.


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Today is a very exciting day for one member of our family. After years of watching Mummy and Daddy make YouTube videos, our daughter has now made one herself, with a little help of course. Last week we finally beat Super Mario 3D World on the Wii U. Daddy pointed out that we should do a review of the game because it's topical, and five year old gamer thought that was a great idea. So much so that when she saw Daddy working at his computer on something else today, she asked if she could make a review. So we said, sure, here then is our family review of Super Mario 3D World. The first level is really easy once you do it a couple of times. It's intense, but it's also exciting. Super Mario 3D World has been something of a welcome break from the legend of Zelda in our house in recent months. Last year something clicked inside her brain, and five year old gamer pivoted from obsessing over Disney princesses to obsessing over Nintendo ones instead. She's made everyone in the house try and play Wind Waker with mixed success. I like flower flowers.  So we bought a cheap copy of Super Mario 3D World on eBay for a little variety, and it certainly succeeded. As far as our daughter's concerned, the game has it all. Princesses, fairies, magic, cats. I like the music on the levels where you ride on a dinosaur. It's fun to play as multiplayer, but it's more fun to play by yourself. 3D World is not quite as deep as many Nintendo titles, even other Mario games, but that's not a bad thing for casual players. In fact, one of the big reasons why 3D World went down so well with us was that even Grandma got along with it well enough to be able to keep up. My favourite part of the game is the music for the first castle because it reminds me of Lego Land. We've seen the first level more than any other, largely because it's so easy that our daughter doesn't need to be confined by boring rules of intended play. She can use the game as a digital dollhouse, playing with the characters. Our daughter will intentionally take damage to make her a baby, and then she'll go for a lovely walk with Cat Mario, who has been renamed Geoffrey. The boss fights are really exciting. My favourite boss fight is the first one.  That said, our daughter has also played to the end of the game, technically. In reality, she's found out that by pressing one of the trigger buttons, she can hide in a bubble and make Daddy do all of that tricky platforming nonsense for her. Yes, she's only spectating, but she doesn't seem to mind at all. The problem for Daddy is that this means he's essentially playing single player, but because of the design of the game, he can't adjust the camera angle and he has to constantly try not to accidentally pop his daughter's bubble. This does make things a bit more frustrating for him, but it's his own fault for buying the game in the first place. Playing the game with Daddy is terrific because I like watching the game being played and also I like being played by myself. Such is the appeal of the game that five-year-old gamer will often condescend to allow Mummy to play with her when Daddy's not available, until she reaches such a point in the game that she deems it too tricky and Daddy can quote, do it faster and better and then I'm turfed off. I do rather enjoy being a cat though. Meow. Playing the game with Mummy is fun because I like laughing at her when she gets it wrong. One unexpected side effect of playing the game is that its music is now the soundtrack for our daily lives. Our daughter started humming the music to herself first, and then we all sort of joined in. We find ourselves singing to it absentmindedly, even when we're doing unrelated activities. My favourite enemy in the game is Goomba, because Goombas are like poos, but if they're lying on their face, they look like ghosts with mushrooms. All in all, this game, unsurprisingly, gets our stamp of approval. If there's a small person in your life that's obsessed with princesses, cats or moustaches, this just might be the game your family needs.