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Kai-Fu Lee: AI Superpowers - China and Silicon Valley | Lex Fridman Podcast #27


small model | large model

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The following is a conversation with Kai Fu Lee.
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He's the chairman and CEO of Cinovation Ventures
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that manages a $2 billion dual currency investment fund
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with a focus on developing the next generation
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of Chinese high tech companies.
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He's the former president of Google China
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and the founder of what is now called
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Microsoft Research Asia,
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an institute that trained many of the artificial
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intelligence leaders in China,
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including CTOs or AI execs at Baidu,
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Tencent, Alibaba, Lenovo, and Huawei.
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He was named one of the 100 most influential people
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in the world by Time Magazine.
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He's the author of seven bestselling books in Chinese
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and most recently, the New York Times bestseller
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called AI Superpowers, China, Silicon Valley,
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and the New World Order.
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He has unparalleled experience
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in working across major tech companies
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and governments and applications of AI,
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and so he has a unique perspective on global innovation
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and the future of AI that I think is important
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to listen to and think about.
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This is the Artificial Intelligence Podcast.
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If you enjoy it, subscribe on YouTube and iTunes,
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support it on Patreon, or simply connect with me
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on Twitter at Lex Friedman.
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And now, here's my conversation with Kaifu Li.
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I immigrated from Russia to US when I was 13.
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You immigrated to US at about the same age.
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The Russian people, the American people,
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the Chinese people each have a certain soul,
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a spirit that permeates throughout the generations.
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So maybe it's a little bit of a poetic question,
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but could you describe your sense
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of what defines the Chinese soul?
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I think the Chinese soul of people today, right,
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we're talking about people who have had centuries of burden
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because of the poverty that the country has gone through,
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and suddenly shined with hope of prosperity
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in the past 40 years as China opened up
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and embraced market economy.
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And undoubtedly, there are two sets of pressures
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on the people, that of the tradition,
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that of facing difficult situations,
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and that of hope of wanting to be the first
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to become successful and wealthy.
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So that's a very strong hunger and a strong desire
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and strong work ethic that drives China forward.
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And is there roots to not just this generation,
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but before that's deeper
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than just the new economic developments?
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Is there something that's unique to China
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that you could speak to that's in the people?
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Yeah, well, the Chinese tradition
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is about excellence, dedication, and results.
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And the Chinese exams and study subjects in schools
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have traditionally started
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from memorizing 10,000 characters,
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not an easy task to start with.
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And further by memorizing
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his historic philosopher's literature poetry.
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So it really is probably
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the strongest rote learning mechanism created
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to make sure people had good memory
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and remember things extremely well.
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That's, I think at the same time,
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suppresses the breakthrough innovation
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and also enhances the speed execution get results.
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And that I think characterizes
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the historic basis of China.
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That's interesting,
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because there's echoes of that in Russian education
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as well as rote memorization.
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So you have to memorize a lot of poetry.
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I mean, there's just an emphasis on perfection in all forms
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that's not conducive to perhaps what you're speaking to,
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which is creativity.
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But you think that kind of education holds back
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the innovative spirit that you might see
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in the United States?
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Well, it holds back the breakthrough innovative spirits
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that we see in the United States,
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but it does not hold back the valuable execution oriented,
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result oriented value creating engines,
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which we see China being very successful.
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So is there a difference between a Chinese AI engineer today
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and an American AI engineer,
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perhaps rooted in the culture that we just talked about
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or the education or the very soul of the people or no?
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And what would your advice be to each
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if there's a difference?
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Well, there's a lot that's similar
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because AI is about mastering sciences,
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about using known technologies and trying new things,
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but it's also about picking from many parts
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of possible networks to use
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and different types of parameters to tune.
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And that part is somewhat rote.
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And it is also, as anyone who's built AI products
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can tell you a lot about cleansing the data
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because AI runs better with more data
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and data is generally unstructured,
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errorful and unclean.
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And the effort to clean the data is immense.
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So I think the better part of American engineering,
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AI engineering process is to try new things,
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to do things people haven't done before
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and to use technology to solve most if not all problems.
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So to make the algorithm work despite not so great data,
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find error tolerant ways to deal with the data.
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The Chinese way would be to basically enumerate
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to the fullest extent all the possible ways
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by a lot of machines, try lots of different ways
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to get it to work and spend a lot of resources
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and money and time cleaning up data.
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That means the AI engineer may be writing
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data cleansing algorithms, working with thousands of people
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who label or correct or do things with the data.
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That is the incredible hard work
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that might lead to better results.
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So the Chinese engineer would rely on
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and ask for more and more and more data
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and find ways to cleanse them and make them work
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in the system and probably less time thinking
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about new algorithms that can overcome data
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or other issues.
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So where's your intuition?
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Where do you think the biggest impact
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in the next 10 years lies?
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Is it in some breakthrough algorithms
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or is it in just this at scale rigor,
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a rigorous approach to data, cleaning data,
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organizing data onto the same algorithms?
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What do you think the big impact in the applied world is?
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Well, if you're really in the company
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and you have to deliver results,
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using known techniques and enhancing data
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seems like the more expedient approach
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that's very low risk and likely to generate
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better and better results.
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And that's why the Chinese approach has done quite well.
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Now, there are a lot of more challenging startups
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and problems such as autonomous vehicles,
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medical diagnosis that existing algorithms
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probably won't solve.
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And that would put the Chinese approach more challenged
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and give them more breakthrough innovation approach,
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more of an edge on those kinds of problems.
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So let me talk to that a little more.
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So my intuition personally is that data
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can take us extremely far.
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So you brought up autonomous vehicles and medical diagnosis.
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So your intuition is that huge amounts of data
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might not be able to completely help us solve that problem.
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Right, so breaking that down further in autonomous vehicle,
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I think huge amounts of data probably will solve
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trucks driving on highways,
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which will deliver a significant value
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and China will probably lead in that.
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And full L5 autonomous is likely to require
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new technologies we don't yet know.
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And that might require academia
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and great industrial research,
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both innovating and working together.
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And in that case, US has an advantage.
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So the interesting question there is,
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I don't know if you're familiar
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on the autonomous vehicle space
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and the developments with Tesla and Elon Musk.
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I am.
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Where they are in fact full steam ahead
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into this mysterious complex world of full autonomy, L5,
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L4, L5, and they're trying to solve that purely with data.
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So the same kind of thing that you're saying
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is just for highway,
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which is what a lot of people share your intuition.
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They're trying to solve with data.
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So just to linger on that moment further,
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do you think possible for them to achieve success
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with simply just a huge amount of this training
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on edge cases and difficult cases in urban environments,
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not just highway and so on?
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I think it would be very hard.
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One could characterize Tesla's approach
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as kind of a Chinese strength approach, right?
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Gather all the data you can
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and hope that will overcome the problems.
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But in autonomous driving,
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clearly a lot of the decisions aren't merely solved
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by aggregating data and having feedback loop.
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There are things that are more akin to human thinking.
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And how would those be integrated and built?
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There has not yet been a lot of success
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integrating human intelligence
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or call it expert systems if you will,
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even though that's a taboo word with the machine learning.
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And the integration of the two types of thinking
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hasn't yet been demonstrated.
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And the question is how much can you push
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a purely machine learning approach?
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And of course, Tesla also has an additional constraint
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that they don't have all the sensors.
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I know that they think it's foolish to use LIDARs,
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but that's clearly a one less very valuable
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and reliable source of input that they're foregoing,
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which may also have consequences.
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I think the advantage of course is capturing data
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that no one has ever seen before.
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And in some cases such as computer vision
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and speech recognition,
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I have seen Chinese companies accumulate data
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that's not seen anywhere in the Western world
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and they have delivered superior results.
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But then speech recognition and object recognition
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are relatively suitable problems for deep learning
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and don't have the potentially need
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for the human intelligence analytical planning elements.
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And the same on the speech recognition side,
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your intuition that speech recognition
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and the machine learning approaches to speech recognition
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won't take us to a conversational system
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that can pass the Turing test,
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which is sort of maybe akin to what driving is.
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So it needs to have something more than just simply
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simple language understanding, simple language generation.
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Roughly right.
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I would say that based on purely machine learning approaches,
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it's hard to imagine it could lead
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to a full conversational experience
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across arbitrary domains, which is akin to L5.
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I'm a little hesitant to use the word Turing test
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because the original definition was probably too easy.
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We probably do that, yeah.
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The spirit of the Turing test
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is what I was referring to. Of course.
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So you've had major leadership research positions
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at Apple, Microsoft, Google.
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So continuing on the discussion of America, Russia,
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Chinese, Seoul and culture and so on.
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What is the culture of Silicon Valley
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in contrast to China and maybe US broadly?
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And what is the unique culture
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of each of these three major companies in your view?
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I think in aggregate, Silicon Valley companies,
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and we could probably include Microsoft in that,
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even though they're not in the Valley,
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is really dream big and have visionary goals
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and believe that technology will conquer all.
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And also the self confidence and the self entitlement
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that whatever they produce,
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the whole world should use and must use.
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And those are historically important, I think.
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Steve Jobs famous quote that he doesn't do focus groups,
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he looks in the mirror and asks the person in the mirror,
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what do you want?
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And that really is an inspirational comment that says,
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the great company shouldn't just ask users what they want,
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but develop something that users will know they want
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when they see it,
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but they could never come up with themselves.
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I think that is probably the most exhilarating description
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of what the essence of Silicon Valley is,
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that this brilliant idea could cause you to build something
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that couldn't come out of the focus groups or AB tests.
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And iPhone would be an example of that.
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No one in the age of Blackberry would write down
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they want an iPhone or multi touch.
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A browser might be another example.
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No one would say they want that in the days of FTP,
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but once they see it, they want it.
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So I think that is what Silicon Valley is best at.
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But it also comes with, it came with a lot of success.
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These products became global platforms
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and there were basically no competitors anywhere.
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And that has also led to a belief
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that these are the only things that one should do,
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that companies should not tread on other companies territory
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so that a Groupon and a Yelp and then OpenTable
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and the Grubhub would each feel,
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okay, I'm not gonna do the other company's business
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because that would not be the pride of innovating
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what each of these four companies have innovated.
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But I think the Chinese approach
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is do whatever it takes to win.
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And it's a winner take all market.
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And in fact, in the internet space,
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the market leader will get predominantly all the value
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extracted out of the system.
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So, and the system isn't just defined
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as one narrow category, but gets broader and broader.
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So it's amazing ambition for success and domination
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of increasingly larger product categories
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leading to clear market winner status
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and the opportunity to extract tremendous value.
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And that develops a practical, result oriented,
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ultra ambitious winner take all gladiatorial mentality.
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And if what it takes is to build what the competitors built,
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essentially a copycat that can be done
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without infringing laws.
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If what it takes is to satisfy a foreign country's need
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by forking the code base and building something
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that looks really ugly and different, they'll do it.
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So it's contrasted very sharply
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with the Silicon Valley approach.
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And I think the flexibility and the speed and execution
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has helped the Chinese approach.
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And I think the Silicon Valley approach
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is potentially challenged if every Chinese entrepreneur
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is learning from the whole world, US and China,
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and the American entrepreneurs only look internally
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and write off China as a copycat.
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And the second part of your question
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about the three companies.
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The unique elements of the three companies perhaps.
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Yeah, I think Apple represents
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while the user please the user
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and the essence of design and brand
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and it's the one company and perhaps the only tech company
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that draws people with a strong, serious desire
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for the product and the willingness to pay a premium
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because of the halo effect of the brand
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which came from the attention to detail
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and great respect for user needs.
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Microsoft represents a platform approach
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that builds giant products that become very strong modes
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that others can't do because it's well architected
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at the bottom level and the work is efficiently delegated
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to individuals and then the whole product is built
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by adding small parts that sum together.
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So it's probably the most effective high tech assembly line
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that builds a very difficult product
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that and the whole process of doing that
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is kind of a differentiation and something competitors
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can't easily repeat.
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Are there elements of the Chinese approach
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in the way Microsoft went about assembling
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those little pieces and dominating,
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essentially dominating the market for a long time
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or do you see those as distinct?
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I think there are elements that are the same.
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I think the three American companies that had
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or have Chinese characteristics and obviously
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as well as American characteristics are Microsoft,
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Facebook and Amazon.
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Yes, that's right, Amazon.
link |
00:18:20.160
Because these are companies that will tenaciously
link |
00:18:23.920
go after adjacent markets,
link |
00:18:27.640
build up strong product offering and find ways
link |
00:18:34.360
to extract greater value from a sphere
link |
00:18:37.960
that's ever increasing and they understand
link |
00:18:41.480
the value of the platforms.
link |
00:18:43.520
So that's the similarity and then with Google,
link |
00:18:47.280
I think it's a genuinely value oriented company
link |
00:18:54.800
that does have a heart and soul
link |
00:18:57.000
and that wants to do great things for the world
link |
00:18:59.800
by connecting information
link |
00:19:01.920
and that has also very strong technology genes
link |
00:19:08.840
and wants to use technology
link |
00:19:13.280
and has found out of the box ways to use technology
link |
00:19:19.120
to deliver incredible value to the end user.
link |
00:19:23.720
If you can look at Google, for example,
link |
00:19:25.240
you mentioned heart and soul.
link |
00:19:28.040
There seems to be an element where Google
link |
00:19:31.840
is after making the world better.
link |
00:19:34.840
There's a more positive view.
link |
00:19:36.920
They used to have the slogan, don't be evil.
link |
00:19:39.280
And Facebook a little bit more has a negative tend to it.
link |
00:19:43.120
At least in the perception of privacy and so on.
link |
00:19:45.760
Do you have a sense of how these different companies
link |
00:19:51.080
can achieve, because you've talked about
link |
00:19:53.040
how much we can make the world better
link |
00:19:54.520
in all these kinds of ways with AI.
link |
00:19:56.760
What is it about a company that can make,
link |
00:19:59.360
give it a heart and soul, gain the trust of the public
link |
00:20:03.200
and just actually just not be evil
link |
00:20:06.120
and do good for the world?
link |
00:20:08.000
It's really hard and I think Google
link |
00:20:10.240
has struggled with that.
link |
00:20:13.120
First, the don't do evil mantra is very dangerous
link |
00:20:16.720
because every employee's definition of evil is different.
link |
00:20:20.800
And that has led to some difficult
link |
00:20:22.600
employee situations for them.
link |
00:20:25.120
So I don't necessarily think that's a good value statement,
link |
00:20:29.560
but just watching the kinds of things Google
link |
00:20:32.320
or its parent company Alphabet does
link |
00:20:35.320
in new areas like healthcare, like eradicating mosquitoes,
link |
00:20:40.480
things that are really not in the business
link |
00:20:42.360
of a internet tech company.
link |
00:20:44.520
I think that shows that there's a heart and soul
link |
00:20:47.200
and desire to do good and willingness
link |
00:20:50.360
to put in the resources to do something
link |
00:20:54.800
when they see it's good, they will pursue it.
link |
00:20:58.280
That doesn't necessarily mean
link |
00:21:00.160
it has all the trust of the users.
link |
00:21:02.480
I realize while most people would view Facebook
link |
00:21:06.360
as the primary target of their recent unhappiness
link |
00:21:09.760
about Silicon Valley companies,
link |
00:21:11.560
many would put Google in that category.
link |
00:21:14.040
And some have named Google's business practices
link |
00:21:16.760
as predatory also.
link |
00:21:19.720
So it's kind of difficult to have the two parts of a body.
link |
00:21:24.240
The brain wants to do what it's supposed to do
link |
00:21:27.440
for a shareholder, maximize profit.
link |
00:21:29.280
And then the heart and soul wants to do good things
link |
00:21:32.000
that may run against what the brain wants to do.
link |
00:21:36.120
So in this complex balancing
link |
00:21:39.000
that these companies have to do,
link |
00:21:40.320
you've mentioned that you're concerned
link |
00:21:42.480
about a future where too few companies
link |
00:21:45.480
like Google, Facebook, Amazon are controlling our data
link |
00:21:49.640
or controlling too much of our digital lives.
link |
00:21:53.360
Can you elaborate on this concern
link |
00:21:54.840
and perhaps do you have a better way forward?
link |
00:21:57.560
I think I'm hardly the most vocal complainer of this.
link |
00:22:02.760
Sure, of course.
link |
00:22:03.760
There are a lot louder complainers out there.
link |
00:22:06.240
I do observe that having a lot of data
link |
00:22:10.760
does perpetuate their strength
link |
00:22:13.600
and limits competition in many spaces.
link |
00:22:18.600
But I also believe AI is much broader
link |
00:22:21.560
than the internet space.
link |
00:22:23.160
So the entrepreneurial opportunities still exists
link |
00:22:26.520
in using AI to empower financial,
link |
00:22:30.600
retail, manufacturing, education applications.
link |
00:22:34.600
So I don't think it's quite a case
link |
00:22:36.440
of full monopolistic dominance
link |
00:22:38.920
that totally stifles innovation.
link |
00:22:43.160
But I do believe in their areas of strength
link |
00:22:45.600
it's hard to dislodge them.
link |
00:22:48.960
I don't know if I have a good solution.
link |
00:22:52.480
Probably the best solution is let
link |
00:22:54.960
the entrepreneurial VC ecosystem work well
link |
00:22:58.320
and find all the places that can create the next Google,
link |
00:23:02.160
the next Facebook.
link |
00:23:03.520
So there will always be increasing number of challengers.
link |
00:23:07.880
In some sense that has happened a little bit.
link |
00:23:10.680
You see Uber, Airbnb having emerged
link |
00:23:14.000
despite the strength of the big three.
link |
00:23:19.440
And I think China as an environment
link |
00:23:21.760
may be more interesting for the emergence
link |
00:23:24.520
because if you look at companies
link |
00:23:26.120
between let's say 50 to $300 billion,
link |
00:23:32.920
China has emerged more of such companies
link |
00:23:35.720
than the US in the last three to four years
link |
00:23:39.320
because of the larger marketplace,
link |
00:23:41.560
because of the more fearless nature of the entrepreneurs.
link |
00:23:46.440
And the Chinese giants are just as powerful
link |
00:23:48.960
as American ones.
link |
00:23:50.240
Tencent, Alibaba are very strong,
link |
00:23:52.360
but ByteDance has emerged worth 75 billion
link |
00:23:56.480
and financial while it's Alibaba affiliated,
link |
00:23:59.600
it's nevertheless independent and worth 150 billion.
link |
00:24:03.400
And so I do think if we start to extend
link |
00:24:07.800
to traditional businesses,
link |
00:24:09.440
we will see very valuable companies.
link |
00:24:12.160
So it's probably not the case that in five or 10 years
link |
00:24:17.600
we'll still see the whole world
link |
00:24:19.160
with these five companies having such dominance.
link |
00:24:22.720
So you've mentioned a couple of times
link |
00:24:26.080
this fascinating world of entrepreneurship in China
link |
00:24:29.240
of the fearless nature of the entrepreneur.
link |
00:24:31.080
So can you maybe talk a little bit about
link |
00:24:33.240
what it takes to be an entrepreneur in China?
link |
00:24:35.520
What are the strategies that are undertaken?
link |
00:24:38.240
What are the ways to achieve success?
link |
00:24:41.120
What is the dynamic of VCF funding
link |
00:24:43.920
of the way the government helps companies and so on?
link |
00:24:46.480
What are the interesting aspects here
link |
00:24:47.880
that are distinct from, that are different
link |
00:24:50.200
from the Silicon Valley world of entrepreneurship?
link |
00:24:55.240
Well, many of the listeners probably still
link |
00:24:59.400
would brand Chinese entrepreneur as copycats.
link |
00:25:03.000
And no doubt 10 years ago,
link |
00:25:05.360
that would not be an inaccurate description.
link |
00:25:09.080
Back 10 years ago,
link |
00:25:10.760
an entrepreneur probably could not get funding
link |
00:25:13.640
if he or she could not describe
link |
00:25:16.000
what product he or she is copying from the US.
link |
00:25:20.440
The first question is who has proven this business model
link |
00:25:23.360
which is a nice way of asking who are you copying?
link |
00:25:27.200
And that reason is understandable
link |
00:25:29.560
because China had a much lower internet penetration
link |
00:25:34.880
and didn't have enough indigenous experience
link |
00:25:40.960
to build innovative products.
link |
00:25:43.240
And secondly, internet was emerging.
link |
00:25:47.640
Link startup was the way to do things,
link |
00:25:49.840
building a first minimally viable product
link |
00:25:52.960
and then expanding was the right way to go.
link |
00:25:55.360
And the American successes have given a shortcut
link |
00:25:59.520
that if you built your minimally viable product
link |
00:26:02.560
based on an American product,
link |
00:26:04.240
it's guaranteed to be a decent starting point.
link |
00:26:06.720
Then you tweak it afterwards.
link |
00:26:08.400
So as long as there are no IP infringement,
link |
00:26:11.280
which as far as I know there hasn't been in the mobile
link |
00:26:14.000
and AI spaces, that's a much better shortcut.
link |
00:26:19.360
And I think Silicon Valley would view that
link |
00:26:21.880
as still not very honorable
link |
00:26:25.120
because that's not your own idea to start with,
link |
00:26:29.160
but you can't really at the same time
link |
00:26:32.560
believe every idea must be your own
link |
00:26:35.120
and believe in the link startup methodology
link |
00:26:38.080
because link startup is intended to try many, many things
link |
00:26:41.840
and then converge when that works.
link |
00:26:44.160
And it's meant to be iterated and changed.
link |
00:26:46.640
So finding a decent starting point
link |
00:26:48.640
without legal violations,
link |
00:26:51.160
there should be nothing morally dishonorable about that.
link |
00:26:55.240
Yeah, so just a quick pause on that.
link |
00:26:56.920
It's fascinating that that's,
link |
00:26:59.760
why is that not honorable, right?
link |
00:27:01.840
It's exactly as you formulated.
link |
00:27:04.600
It seems like a perfect start for business.
link |
00:27:07.600
Is to take, look at Amazon and say,
link |
00:27:12.080
okay, we'll do exactly what Amazon is doing.
link |
00:27:14.480
Let's start there in this particular market
link |
00:27:16.760
and then let's out innovate them from that starting point.
link |
00:27:20.720
Come up with new ways.
link |
00:27:22.200
I mean, is it wrong to be,
link |
00:27:25.200
except the word copycat just sounds bad,
link |
00:27:27.080
but is it wrong to be a copycat?
link |
00:27:28.760
It just seems like a smart strategy,
link |
00:27:31.600
but yes, it doesn't have a heroic nature to it
link |
00:27:35.760
that like Steve Jobs, Elon Musk,
link |
00:27:40.720
sort of in something completely,
link |
00:27:42.200
coming up with something completely new.
link |
00:27:43.880
Yeah, I like the way you describe it.
link |
00:27:45.280
It's a nonheroic, acceptable way to start the company
link |
00:27:50.440
and maybe more expedient.
link |
00:27:52.800
So that's, I think, a baggage for Silicon Valley
link |
00:27:58.920
that if it doesn't let go,
link |
00:28:00.760
then it may limit the ultimate ceiling of the company.
link |
00:28:05.120
Take Snapchat as an example.
link |
00:28:07.200
I think, you know, Evan's brilliant.
link |
00:28:09.840
He built a great product,
link |
00:28:11.520
but he's very proud that he wants to build his own features,
link |
00:28:15.440
not copy others.
link |
00:28:16.800
While Facebook was more willing to copy his features
link |
00:28:20.960
and you see what happens in the competition.
link |
00:28:23.440
So I think putting that handcuff on the company
link |
00:28:27.440
would limit its ability to reach the maximum potential.
link |
00:28:31.560
So back to the Chinese environment,
link |
00:28:33.840
copying was merely a way to learn from the American masters.
link |
00:28:38.400
Just like we, if we learned to play piano or painting,
link |
00:28:43.440
you start by copying.
link |
00:28:44.520
You don't start by innovating
link |
00:28:45.960
when you don't have the basic skill sets.
link |
00:28:48.160
So very amazingly, the Chinese entrepreneurs
link |
00:28:51.000
about six years ago started to branch off
link |
00:28:56.120
with these lean startups built on American ideas
link |
00:28:59.480
to build better products than American products.
link |
00:29:02.120
But they did start from the American idea.
link |
00:29:04.960
And today WeChat is better than WhatsApp,
link |
00:29:08.560
Weibo is better than Twitter,
link |
00:29:10.520
Zhihu is better than Quora and so on.
link |
00:29:12.920
So that I think is Chinese entrepreneurs going to step two.
link |
00:29:18.520
And then step three is once these entrepreneurs
link |
00:29:21.560
have done one or two of these companies,
link |
00:29:23.720
they now look at the Chinese market and the opportunities
link |
00:29:27.400
and come up with ideas that didn't exist elsewhere.
link |
00:29:30.600
So products like Ant Financial,
link |
00:29:34.200
under which includes Alipay, which is mobile payments,
link |
00:29:38.280
and also the financial products for loans built on that.
link |
00:29:44.320
And also in education, VIPKID,
link |
00:29:48.560
and in social video, social network, TikTok,
link |
00:29:54.880
and in social eCommerce, Pinduoduo,
link |
00:29:58.640
and then in ride sharing, Mobike,
link |
00:30:01.680
these are all Chinese innovated products
link |
00:30:05.600
that now are being copied elsewhere.
link |
00:30:08.680
So an additional interesting observation
link |
00:30:13.000
is some of these products
link |
00:30:14.240
are built on unique Chinese demographics,
link |
00:30:17.240
which may not work in the US,
link |
00:30:19.360
but may work very well in Southeast Asia, Africa,
link |
00:30:23.120
and other developing worlds
link |
00:30:25.160
that are a few years behind China.
link |
00:30:27.800
And a few of these products maybe are universal
link |
00:30:31.000
and are getting traction even in the United States,
link |
00:30:33.720
such as TikTok.
link |
00:30:35.320
So this whole ecosystem is supported by VCs
link |
00:30:42.040
as a virtuous cycle,
link |
00:30:43.480
because a large market with innovative entrepreneurs
link |
00:30:47.640
will draw a lot of money
link |
00:30:49.360
and then invest in these companies.
link |
00:30:51.520
As the market gets larger and larger,
link |
00:30:54.480
the China market is easily three, four times larger than the US,
link |
00:30:58.440
they will create greater value and greater returns
link |
00:31:01.120
for the VCs, thereby raising even more money.
link |
00:31:05.400
So at Sinovation Ventures, our first fund was 15 million,
link |
00:31:09.960
our last fund was 500 million.
link |
00:31:12.000
So it reflects the valuation of the companies
link |
00:31:16.520
and our us going multi stage and things like that.
link |
00:31:19.840
It also has government support,
link |
00:31:22.000
but not in the way most Americans would think of it.
link |
00:31:25.360
The government actually leaves the entrepreneurial space
link |
00:31:28.720
as a private enterprise, sort of self regulating,
link |
00:31:32.400
and the government would build infrastructures
link |
00:31:35.400
that would around it to make it work better.
link |
00:31:38.520
For example, the Mass Entrepreneur Mass Innovation Plan
link |
00:31:42.160
builds 8,000 incubators,
link |
00:31:44.120
so the pipeline is very strong to the VCs.
link |
00:31:47.560
For autonomous vehicles,
link |
00:31:48.920
the Chinese government is building smart highways
link |
00:31:52.600
with sensors, smart cities
link |
00:31:54.640
that separate pedestrians from cars
link |
00:31:57.240
that may allow initially an inferior
link |
00:32:00.440
autonomous vehicle company to launch a car
link |
00:32:03.640
without increasing with lower casualty
link |
00:32:07.000
because the roads or the city is smart.
link |
00:32:10.880
And the Chinese government at local levels
link |
00:32:13.160
would have these guiding funds acting as LPs,
link |
00:32:16.720
passive LPs to funds.
link |
00:32:18.800
And when the fund makes money,
link |
00:32:21.400
part of the money made is given back
link |
00:32:23.880
to the GPs and potentially other LPs
link |
00:32:26.720
to increase everybody's return
link |
00:32:30.480
at the expense of the government's return.
link |
00:32:33.080
So that's an interesting incentive
link |
00:32:35.800
that entrusts the task of choosing entrepreneurs to VCs
link |
00:32:41.080
who are better at it than the government
link |
00:32:43.240
by letting some of the profits move that way.
link |
00:32:46.080
So this is really fascinating, right?
link |
00:32:48.720
So I look at the Russian government as a case study
link |
00:32:51.800
where, let me put it this way,
link |
00:32:54.240
there's no such government driven
link |
00:32:57.840
large scale support of entrepreneurship.
link |
00:33:00.840
And probably the same is true in the United States,
link |
00:33:04.000
but the entrepreneurs themselves kind of find a way.
link |
00:33:07.640
So maybe in a form of advice or explanation,
link |
00:33:11.640
how did the Chinese government arrive to be this way
link |
00:33:15.560
so supportive on entrepreneurship
link |
00:33:17.720
to be in this particular way so forward thinking
link |
00:33:21.520
at such a large scale?
link |
00:33:23.120
And also perhaps, how can we copy it in other countries?
link |
00:33:28.280
How can we encourage other governments,
link |
00:33:29.800
like even the United States government,
link |
00:33:31.600
to support infrastructure for autonomous vehicles
link |
00:33:33.800
in that same kind of way, perhaps?
link |
00:33:36.040
Yes, so these techniques are
link |
00:33:41.040
the result of several key things,
link |
00:33:44.440
some of which may be learnable,
link |
00:33:46.040
some of which may be very hard.
link |
00:33:48.040
One is just trial and error
link |
00:33:50.520
and watching what everyone else is doing.
link |
00:33:52.920
I think it's important to be humble
link |
00:33:54.680
and not feel like you know all the answers.
link |
00:33:56.920
The guiding funds idea came from Singapore,
link |
00:33:59.480
which came from Israel.
link |
00:34:01.440
And China made a few tweaks and turned it into a,
link |
00:34:06.120
because the Chinese cities and government officials
link |
00:34:09.320
kind of compete with each other
link |
00:34:11.360
because they all want to make their city more successful
link |
00:34:14.680
so they can get the next level in their political career.
link |
00:34:20.280
And it's somewhat competitive.
link |
00:34:22.280
So the central government made it a bit of a competition.
link |
00:34:25.160
Everybody has a budget.
link |
00:34:26.800
They can put it on AI or they can put it on bio
link |
00:34:29.840
or they can put it on energy.
link |
00:34:32.160
And then whoever gets the results,
link |
00:34:34.120
the city shines, the people are better off,
link |
00:34:36.160
the mayor gets a promotion.
link |
00:34:37.960
So the tools is kind of almost like an entrepreneurial
link |
00:34:41.680
environment for local governments
link |
00:34:44.840
to see who can do a better job.
link |
00:34:47.480
And also many of them try different experiments.
link |
00:34:52.480
Some have given award to very smart researchers.
link |
00:34:58.480
Just give them money and hope they'll start a company.
link |
00:35:00.840
Some have given money to academic research labs,
link |
00:35:05.840
maybe government research labs
link |
00:35:08.080
to see if they can spin off some companies
link |
00:35:10.760
from the science lab or something like that.
link |
00:35:14.080
Some have tried to recruit overseas Chinese
link |
00:35:17.120
to come back and start companies.
link |
00:35:19.000
And they've had mixed results.
link |
00:35:21.000
The one that worked the best was the guiding funds.
link |
00:35:23.400
So it's almost like a lean startup idea
link |
00:35:25.880
where people try different things
link |
00:35:27.560
and what works sticks and everybody copies.
link |
00:35:30.600
So now every city has a guiding fund.
link |
00:35:32.880
So that's how that came about.
link |
00:35:34.600
The autonomous vehicle and the massive spending
link |
00:35:40.400
in highways and smart cities, that's a Chinese way.
link |
00:35:46.080
It's about building infrastructure to facilitate.
link |
00:35:49.520
It's a clear division of the government's responsibility
link |
00:35:52.880
from the market.
link |
00:35:55.400
The market should do everything in a private freeway,
link |
00:36:00.560
but there are things the market can't afford to do
link |
00:36:02.920
like infrastructure.
link |
00:36:04.480
So the government always appropriates large amounts
link |
00:36:08.680
of money for infrastructure building.
link |
00:36:11.960
This happens with not only autonomous vehicle and AI,
link |
00:36:16.840
but happened with the 3G and 4G.
link |
00:36:20.800
You'll find that the Chinese wireless reception
link |
00:36:25.320
is better than the US because massive spending
link |
00:36:28.560
that tries to cover the whole country,
link |
00:36:30.600
whereas in the US it may be a little spotty.
link |
00:36:33.040
It's a government driven because I think they view
link |
00:36:36.880
the coverage of cell access and 3G, 4G access
link |
00:36:44.120
to be a governmental infrastructure spending
link |
00:36:47.080
as opposed to capitalistic.
link |
00:36:49.880
So that's, of course, the state owned enterprises
link |
00:36:52.240
are also publicly traded,
link |
00:36:54.280
but they also carry a government responsibility
link |
00:36:57.760
to deliver infrastructure to all.
link |
00:37:00.240
So it's a different way of thinking
link |
00:37:01.920
that may be very hard to inject into Western countries
link |
00:37:05.440
to say starting tomorrow, bandwidth infrastructure
link |
00:37:09.320
and highways are gonna be governmental spending
link |
00:37:13.880
with some characteristics.
link |
00:37:16.120
What's your sense, and sorry to interrupt,
link |
00:37:18.280
but because it's such a fascinating point,
link |
00:37:21.680
do you think on the autonomous vehicle space
link |
00:37:25.600
it's possible to solve the problem of full autonomy
link |
00:37:30.160
without significant investment in infrastructure?
link |
00:37:34.120
Well, that's really hard to speculate.
link |
00:37:36.440
I think it's not a yes, no question,
link |
00:37:39.000
but how long does it take question?
link |
00:37:42.000
15 years, 30 years, 45 years.
link |
00:37:45.200
Clearly with infrastructure augmentation,
link |
00:37:49.040
whether it's road, the city or whole city planning,
link |
00:37:52.360
building a new city, I'm sure that will accelerate
link |
00:37:56.480
the day of the L5.
link |
00:37:58.320
I'm not knowledgeable enough,
link |
00:38:01.280
and it's hard to predict even when we're knowledgeable
link |
00:38:03.920
because a lot of it is speculative.
link |
00:38:07.160
But in the US, I don't think people would consider
link |
00:38:10.440
building a new city the size of Chicago
link |
00:38:13.280
to make it the AI slash autonomous city.
link |
00:38:15.960
There are smaller ones being built, I'm aware of that.
link |
00:38:18.880
But is infrastructure spend really impossible
link |
00:38:22.040
for US or Western countries?
link |
00:38:23.720
I don't think so.
link |
00:38:25.760
The US highway system was built,
link |
00:38:28.920
was that during President Eisenhower or Kennedy?
link |
00:38:31.960
Eisenhower, yeah.
link |
00:38:33.160
So maybe historians can study
link |
00:38:37.240
how the President Eisenhower get the resources
link |
00:38:40.280
to build this massive infrastructure
link |
00:38:42.800
that surely gave US a tremendous amount of prosperity
link |
00:38:47.560
over the next decade, if not century.
link |
00:38:50.800
If I may comment on that then,
link |
00:38:53.080
it takes us to artificial intelligence a little bit
link |
00:38:55.440
because in order to build infrastructure,
link |
00:38:58.080
it creates a lot of jobs.
link |
00:39:00.520
So I'll be actually interested if you would say
link |
00:39:03.400
that you talk in your book about all kinds of jobs
link |
00:39:06.560
that could and could not be automated.
link |
00:39:08.920
I wonder if building infrastructure is one of the jobs
link |
00:39:13.080
that would not be easily automated.
link |
00:39:15.760
Something you could think about
link |
00:39:17.040
because I think you've mentioned somewhere in the talk
link |
00:39:19.920
or that there might be, as jobs are being automated,
link |
00:39:24.280
a role for government to create jobs
link |
00:39:26.200
that can't be automated.
link |
00:39:28.160
Yes, I think that's a possibility.
link |
00:39:31.040
Back in the last financial crisis,
link |
00:39:34.280
China put a lot of money
link |
00:39:37.840
to basically give this economy a boost
link |
00:39:41.200
and a lot of it went into infrastructure building.
link |
00:39:45.480
And I think that's a legitimate way at the government level
link |
00:39:49.920
to deal with the employment issues
link |
00:39:54.360
as well as build out the infrastructure
link |
00:39:57.040
as long as the infrastructures are truly needed
link |
00:39:59.840
and as long as there is an employment problem,
link |
00:40:02.160
which no, we don't know.
link |
00:40:04.920
So maybe taking a little step back,
link |
00:40:07.840
if you've been a leader and a researcher in AI
link |
00:40:12.840
for several decades, at least 30 years,
link |
00:40:16.200
so how has AI changed in the West and the East
link |
00:40:21.000
as you've observed, as you've been deep in it
link |
00:40:23.080
over the past 30 years?
link |
00:40:25.080
Well, AI began as the pursuit
link |
00:40:27.840
of understanding human intelligence
link |
00:40:30.280
and the term itself represents that,
link |
00:40:34.160
but it kind of drifted into the one sub area
link |
00:40:37.520
that worked extremely well, which is machine intelligence.
link |
00:40:40.840
And that's actually more using pattern recognition techniques
link |
00:40:45.080
to basically do incredibly well on a limited domain,
link |
00:40:51.280
large amount of data,
link |
00:40:52.760
but relatively simple kinds of planning tasks
link |
00:40:57.120
and not very creative.
link |
00:40:58.680
So we didn't end up building human intelligence.
link |
00:41:02.440
We built a different machine
link |
00:41:04.560
that was a lot better than us, some problems,
link |
00:41:08.080
but nowhere close to us on other problems.
link |
00:41:11.720
So today, I think a lot of people still misunderstand
link |
00:41:16.320
when we say artificial intelligence
link |
00:41:18.040
and what various products can do,
link |
00:41:20.720
people still think it's about replicating
link |
00:41:22.960
human intelligence,
link |
00:41:24.200
but the products out there really are closer
link |
00:41:27.600
to having invented the internet or the spreadsheet
link |
00:41:31.680
or the database and getting broader adoption.
link |
00:41:35.360
And speaking further to the fears,
link |
00:41:37.640
near term fears that people have about AI,
link |
00:41:40.360
so you're commenting on the sort of general intelligence
link |
00:41:45.080
that people in the popular culture from sci fi movies
link |
00:41:48.080
have a sense about AI,
link |
00:41:49.600
but there's practical fears about AI,
link |
00:41:52.000
the narrow AI that you're talking about
link |
00:41:54.840
of automating particular kinds of jobs
link |
00:41:57.280
and you talk about them in the book.
link |
00:41:59.440
So what are the kinds of jobs in your view
link |
00:42:01.560
that you see in the next five, 10 years
link |
00:42:04.480
beginning to be automated by AI systems algorithms?
link |
00:42:09.280
Yes, this is also maybe a little bit counterintuitive
link |
00:42:13.040
because it's the routine jobs
link |
00:42:15.280
that will be displaced the soonest
link |
00:42:18.360
and they may not be displaced entirely,
link |
00:42:20.880
maybe 50%, 80% of a job,
link |
00:42:24.080
but when the workload drops by that much,
link |
00:42:26.320
employment will come down.
link |
00:42:28.760
And also another part of misunderstanding
link |
00:42:31.520
is most people think of AI replacing routine jobs
link |
00:42:35.720
than they think of the assembly line, the workers.
link |
00:42:38.760
Well, that will have some effect,
link |
00:42:41.000
but it's actually the routine white collar workers
link |
00:42:44.240
that's easiest to replace
link |
00:42:46.200
because to replace a white collar worker,
link |
00:42:49.280
you just need software.
link |
00:42:50.720
To replace a blue collar worker,
link |
00:42:53.120
you need robotics, mechanical excellence,
link |
00:42:57.200
and the ability to deal with dexterity
link |
00:43:01.880
and maybe even unknown environments, very, very difficult.
link |
00:43:05.640
So if we were to categorize the most dangerous
link |
00:43:10.600
white collar jobs,
link |
00:43:12.400
they would be things like back office,
link |
00:43:15.640
people who copy and paste
link |
00:43:17.920
and deal with simple computer programs and data
link |
00:43:22.200
and maybe paper and OCR,
link |
00:43:25.600
and they don't make strategic decisions.
link |
00:43:29.040
They basically facilitate the process.
link |
00:43:32.040
These softwares and paper systems don't work.
link |
00:43:34.600
So you have people dealing with new employee orientation,
link |
00:43:40.520
searching for past lawsuits and financial documents,
link |
00:43:45.200
and doing reference check.
link |
00:43:47.920
So basic searching and management of data.
link |
00:43:50.960
That's the most endangered being lost.
link |
00:43:52.800
In addition to the white collar repetitive work,
link |
00:43:56.440
a lot of simple interaction work can also be taken care of
link |
00:44:00.240
such as telesales, telemarketing, customer service,
link |
00:44:04.840
as well as many physical jobs
link |
00:44:07.280
that are in the same location
link |
00:44:09.520
and don't require a high degree of dexterity.
link |
00:44:12.200
So fruit picking, dishwashing, assembly line inspection
link |
00:44:17.840
are jobs in that category.
link |
00:44:20.320
So altogether, back office is a big part.
link |
00:44:25.400
And the blue collar may be smaller initially,
link |
00:44:29.840
but over time, AI will get better.
link |
00:44:32.520
And when we start to get to over the next 15, 20 years,
link |
00:44:36.880
the ability to actually have the dexterity
link |
00:44:39.120
of doing assembly line, that's a huge chunk of jobs.
link |
00:44:42.600
And when autonomous vehicles start to work,
link |
00:44:45.600
initially starting with truck drivers,
link |
00:44:47.440
but eventually to all drivers,
link |
00:44:49.360
that's another huge group of workers.
link |
00:44:52.000
So I see modest numbers in the next five years,
link |
00:44:55.600
but increasing rapidly after that.
link |
00:44:58.080
On the worry of the jobs that are in danger
link |
00:45:01.240
and the gradual loss of jobs,
link |
00:45:04.080
I'm not sure if you're familiar with Andrew Yang.
link |
00:45:06.680
Yes, I am.
link |
00:45:07.840
So there's a candidate for president of the United States
link |
00:45:10.600
whose platform Andrew Yang is based around,
link |
00:45:14.400
in part around job loss due to automation.
link |
00:45:17.720
And also in addition,
link |
00:45:19.600
the need perhaps of universal basic income
link |
00:45:22.600
to support jobs that are,
link |
00:45:25.280
folks who lose their job due to automation and so on.
link |
00:45:28.600
And in general, support people
link |
00:45:30.400
under complex, unstable job market.
link |
00:45:34.360
So what are your thoughts about his concerns,
link |
00:45:36.760
him as a candidate, his ideas in general?
link |
00:45:40.080
I think his thinking is generally in the right direction,
link |
00:45:44.680
but his approach as a presidential candidate
link |
00:45:48.480
may be a little bit ahead of the time.
link |
00:45:51.040
And I think the displacements will happen,
link |
00:45:56.120
but will they happen soon enough
link |
00:45:57.800
for people to agree to vote for him?
link |
00:46:00.480
The unemployment numbers are not very high yet.
link |
00:46:03.800
And I think he and I have the same challenge.
link |
00:46:07.600
If I want to theoretically convince people this is an issue
link |
00:46:11.560
and he wants to become the president,
link |
00:46:13.920
people have to see how can this be the case
link |
00:46:17.520
when unemployment numbers are low.
link |
00:46:19.720
So that is the challenge.
link |
00:46:21.400
And I think I do agree with him on the displacement issue,
link |
00:46:27.080
on universal basic income.
link |
00:46:30.280
At a very vanilla level, I don't agree with it
link |
00:46:33.920
because I think the main issue is retraining.
link |
00:46:38.360
So people need to be incented
link |
00:46:41.520
not by just giving a monthly $2,000 check or $1,000 check
link |
00:46:45.480
and do whatever they want
link |
00:46:47.160
because they don't have the know how
link |
00:46:50.960
to know what to retrain to go into what type of a job.
link |
00:46:56.840
And guidance is needed.
link |
00:46:58.640
And retraining is needed
link |
00:47:00.440
because historically when technology revolutions,
link |
00:47:03.160
when routine jobs were displaced, new routine jobs came up.
link |
00:47:06.880
So there was always room for that.
link |
00:47:09.400
But with AI and automation,
link |
00:47:11.840
the whole point is replacing all routine jobs eventually.
link |
00:47:15.320
So there will be fewer and fewer routine jobs.
link |
00:47:17.840
And AI will create jobs, but it won't create routine jobs
link |
00:47:22.640
because if it creates routine jobs,
link |
00:47:24.840
why wouldn't AI just do it?
link |
00:47:26.880
So therefore the people who are losing the jobs
link |
00:47:30.360
are losing routine jobs.
link |
00:47:32.280
The jobs that are becoming available are non routine jobs.
link |
00:47:35.680
So the social stipend needs to be put in place
link |
00:47:39.280
is for the routine workers who lost their jobs
link |
00:47:42.040
to be retrained maybe in six months, maybe in three years,
link |
00:47:46.120
takes a while to retrain on the non routine job
link |
00:47:48.560
and then take on a job that will last
link |
00:47:51.360
for that person's lifetime.
link |
00:47:53.360
Now, having said that,
link |
00:47:55.280
if you look deeply into Andrew's document,
link |
00:47:57.120
he does cater for that.
link |
00:47:58.200
So I'm not disagreeing with what he's trying to do.
link |
00:48:03.280
But for simplification, sometimes he just says UBI,
link |
00:48:06.320
but simple UBI wouldn't work.
link |
00:48:08.720
And I think you've mentioned elsewhere
link |
00:48:10.560
that the goal isn't necessarily to give people enough money
link |
00:48:15.720
to survive or live, or even to prosper.
link |
00:48:19.080
The point is to give them a job that gives them meaning.
link |
00:48:22.760
That meaning is extremely important.
link |
00:48:25.560
That our employment, at least in the United States
link |
00:48:28.560
and perhaps it carries across the world,
link |
00:48:31.120
provides something that's, forgive me for saying,
link |
00:48:34.520
greater than money.
link |
00:48:35.600
It provides meaning.
link |
00:48:36.880
So now, what kind of jobs do you think can't be automated?
link |
00:48:43.280
Can you talk a little bit about creativity
link |
00:48:45.080
and compassion in your book?
link |
00:48:46.640
What aspects do you think it's difficult to automate
link |
00:48:49.640
for an AI system?
link |
00:48:51.920
Because an AI system is currently merely optimizing.
link |
00:48:56.440
It's not able to reason, plan,
link |
00:48:59.240
or think creatively or strategically.
link |
00:49:02.040
It's not able to deal with complex problems.
link |
00:49:04.400
It can't come up with a new problem and solve it.
link |
00:49:08.800
A human needs to find the problem
link |
00:49:11.480
and pose it as an optimization problem,
link |
00:49:14.760
then have the AI work at it.
link |
00:49:16.640
So an AI would have a very hard time discovering a new drug
link |
00:49:22.360
or discovering a new style of painting
link |
00:49:26.440
or dealing with complex tasks such as managing a company
link |
00:49:31.440
that isn't just about optimizing the bottom line,
link |
00:49:34.440
but also about employee satisfaction, corporate brand,
link |
00:49:38.000
and many, many other things.
link |
00:49:39.840
So that is one category of things.
link |
00:49:43.400
And because these things are challenging, creative, complex,
link |
00:49:47.360
doing them creates a high degree of satisfaction
link |
00:49:51.160
and therefore appealing to our desire for working,
link |
00:49:54.480
which isn't just to make the money, make the ends meet,
link |
00:49:57.360
but also that we've accomplished something
link |
00:49:59.560
that others maybe can't do or can't do as well.
link |
00:50:03.320
Another type of job that is much numerous
link |
00:50:06.320
would be compassionate jobs, jobs that require compassion,
link |
00:50:10.240
empathy, human touch, human trust.
link |
00:50:13.600
AI can't do that because AI is cold, calculating,
link |
00:50:17.760
and even if it can fake that to some extent,
link |
00:50:21.920
it will make errors and that will make it look very silly.
link |
00:50:25.120
And also, I think even if AI did okay,
link |
00:50:28.320
people would want to interact with another person,
link |
00:50:32.000
whether it's for some kind of a service or a teacher
link |
00:50:35.920
or a doctor or a concierge or a masseuse or a bartender.
link |
00:50:40.920
There are so many jobs where people just don't want
link |
00:50:44.440
to interact with a cold robot or software.
link |
00:50:49.400
I've had an entrepreneur who built an elderly care robot
link |
00:50:52.480
and they found that the elderly really only use it
link |
00:50:55.240
for customer service.
link |
00:50:56.880
And not, but not to service the product,
link |
00:50:59.480
but they click on customer service
link |
00:51:01.840
and the video of a person comes up
link |
00:51:04.120
and then the person says,
link |
00:51:05.960
how come my daughter didn't call me?
link |
00:51:08.080
Let me show you a picture of her grandkids.
link |
00:51:10.240
So people yearn for that people, people interaction.
link |
00:51:14.000
So even if robots improved, people just don't want it.
link |
00:51:17.840
And those jobs are going to be increasing
link |
00:51:20.120
because AI will create a lot of value,
link |
00:51:22.840
$16 trillion to the world in the next 10 years.
link |
00:51:26.640
Next 11 years, according to PWC.
link |
00:51:29.520
And that will give people money to enjoy services,
link |
00:51:34.640
whether it's eating a gourmet meal or tourism and traveling
link |
00:51:39.680
or having concierge services,
link |
00:51:41.480
the services revolving around every dollar
link |
00:51:45.600
of that $16 trillion will be tremendous.
link |
00:51:48.080
It will create more opportunities
link |
00:51:50.080
that are to service the people who did well
link |
00:51:52.800
through AI with things.
link |
00:51:56.240
But even at the same time,
link |
00:51:58.280
the entire society is very much short
link |
00:52:01.720
in need of many service oriented,
link |
00:52:04.240
compassionate oriented jobs.
link |
00:52:06.200
The best example is probably in healthcare services.
link |
00:52:10.360
There's going to be 2 million new jobs,
link |
00:52:14.320
not counting replacement,
link |
00:52:15.400
just brand new incremental jobs
link |
00:52:17.520
in the next six years in healthcare services.
link |
00:52:20.560
That includes nurses, orderly in the hospital,
link |
00:52:25.000
elderly care and also at home care is particularly lacking.
link |
00:52:31.480
And those jobs are not likely to be filled.
link |
00:52:34.840
So there's likely to be a shortage.
link |
00:52:36.840
And the reason they're not filled
link |
00:52:38.600
is simply because they don't pay very well
link |
00:52:41.600
and that the social status of these jobs are not very good.
link |
00:52:47.520
So they pay about half as much
link |
00:52:49.720
as a heavy equipment operator,
link |
00:52:52.160
which will be replaced a lot sooner.
link |
00:52:55.600
And they pay probably comparably
link |
00:52:57.560
to someone on the assembly line.
link |
00:52:59.880
And so if we ignoring all the other issues
link |
00:53:03.480
and just think about satisfaction from one's job,
link |
00:53:07.160
someone repetitively doing the same manual action
link |
00:53:10.520
at an assembly line,
link |
00:53:11.640
that can't create a lot of job satisfaction,
link |
00:53:14.640
but someone taking care of a sick person
link |
00:53:17.680
and getting a hug and thank you
link |
00:53:19.600
from that person and the family,
link |
00:53:22.000
I think is quite satisfying.
link |
00:53:24.680
So if only we could fix the pay for service jobs,
link |
00:53:28.720
there are plenty of jobs that require some training
link |
00:53:31.880
or a lot of training
link |
00:53:33.400
for the people coming off the routine jobs to take.
link |
00:53:36.960
We can easily imagine someone
link |
00:53:40.320
who was maybe a cashier at the grocery store
link |
00:53:43.480
as stores become automated,
link |
00:53:45.640
learns to become a nurse or an at home care.
link |
00:53:49.160
I also do want to point out the blue collar jobs
link |
00:53:52.760
are going to stay around a bit longer.
link |
00:53:54.720
Some of them quite a bit longer.
link |
00:53:58.120
AI cannot be told go clean an arbitrary home.
link |
00:54:02.200
That's incredibly hard.
link |
00:54:03.920
Arguably it's an L5 level of difficulty, right?
link |
00:54:07.560
And then AI cannot be a good plumber
link |
00:54:10.080
because plumber is almost like a mini detective
link |
00:54:12.840
that has to figure out where the leak came from.
link |
00:54:15.640
So yet AI probably can be an assembly line
link |
00:54:20.200
and auto mechanic and so on.
link |
00:54:22.800
So one has to study which blue collar jobs are going away
link |
00:54:26.760
and facilitate retraining for the people
link |
00:54:29.240
to go into the ones that won't go away
link |
00:54:31.120
or maybe even will increase.
link |
00:54:32.960
I mean, it is fascinating that it's easier
link |
00:54:35.000
to build a world champion chess player
link |
00:54:39.480
than it is to build a mediocre plumber.
link |
00:54:42.040
Yes, right.
link |
00:54:43.160
Very true.
link |
00:54:44.000
And to AI and that goes counterintuitive
link |
00:54:46.160
to a lot of people's understanding
link |
00:54:48.000
of what artificial intelligence is.
link |
00:54:50.120
So it sounds, I mean, you're painting
link |
00:54:52.480
a pretty optimistic picture about retraining
link |
00:54:55.400
about the number of jobs
link |
00:54:57.000
and actually the meaningful nature of those jobs
link |
00:54:59.560
once we automate the repetitive tasks.
link |
00:55:02.080
So overall, are you optimistic about the future
link |
00:55:08.160
where much of the repetitive tasks are automated?
link |
00:55:11.640
That there is a lot of room for humans
link |
00:55:13.840
for the compassionate, for the creative input
link |
00:55:17.360
that only humans can provide?
link |
00:55:20.080
I am optimistic if we start to take action.
link |
00:55:23.400
If we have no action in the next five years,
link |
00:55:27.640
I think it's going to be hard to deal
link |
00:55:30.760
with the devastating losses that will emerge.
link |
00:55:34.200
So if we start thinking about retraining,
link |
00:55:37.120
maybe with the low hanging fruits,
link |
00:55:39.360
explaining to vocational schools
link |
00:55:41.800
why they should train more plumbers than auto mechanics,
link |
00:55:46.640
maybe starting with some government subsidy
link |
00:55:49.680
for corporations to have more training positions.
link |
00:55:53.600
We start to explain to people why retraining is important.
link |
00:55:58.160
We start to think about what the future of education,
link |
00:56:00.760
how that needs to be tweaked for the era of AI.
link |
00:56:04.560
If we start to make incremental progress
link |
00:56:06.760
and the greater number of people understand,
link |
00:56:08.960
then there's no reason to think we can't deal with this
link |
00:56:12.360
because this technological revolution
link |
00:56:14.360
is arguably similar to what electricity,
link |
00:56:17.280
industrial revolutions, and internet brought about.
link |
00:56:20.440
Do you think there's a role for policy,
link |
00:56:22.680
for governments to step in,
link |
00:56:24.640
to help with policy to create a better world?
link |
00:56:28.000
Absolutely, and the governments don't have to believe
link |
00:56:32.280
an employment will go up,
link |
00:56:34.040
and they don't have to believe automation will be this fast
link |
00:56:37.560
to do something.
link |
00:56:39.440
Revamping vocational school would be one example.
link |
00:56:42.520
Another is if there's a big gap
link |
00:56:44.760
in healthcare service employment,
link |
00:56:47.480
and we know that a country's population is growing older,
link |
00:56:51.840
more longevity, living older,
link |
00:56:54.280
because people over 80 require five times as much care
link |
00:56:57.560
as those under 80,
link |
00:56:59.680
then it is a good time to incent training programs
link |
00:57:03.480
for elderly care to find ways to improve the pay.
link |
00:57:07.600
Maybe one way would be to offer as part of Medicare
link |
00:57:11.720
or the equivalent program for people over 80
link |
00:57:14.600
to be entitled to a few hours of elderly care at home,
link |
00:57:18.760
and then that might be reimbursable,
link |
00:57:22.160
and that will stimulate the service industry
link |
00:57:26.720
around the policy.
link |
00:57:28.920
Do you have concerns about large entities,
link |
00:57:33.400
whether it's governments or companies,
link |
00:57:35.480
controlling the future of AI development in general?
link |
00:57:39.240
So we talked about companies.
link |
00:57:41.000
Do you have a better sense that governments
link |
00:57:44.360
can better represent the interests of the people
link |
00:57:49.480
than companies, or do you believe companies
link |
00:57:52.320
are better at representing the interests of the people?
link |
00:57:54.960
Or is there no easy answer?
link |
00:57:56.840
I don't think there's an easy answer
link |
00:57:58.120
because it's a double edged sword.
link |
00:58:00.200
The companies and governments can provide better services
link |
00:58:03.760
with more access to data and more access to AI,
link |
00:58:06.760
but that also leads to greater power,
link |
00:58:09.440
which can lead to uncontrollable problems,
link |
00:58:13.600
whether it's monopoly or corruption in the government.
link |
00:58:17.760
So I think one has to be careful
link |
00:58:21.400
to look at how much data that companies and governments have
link |
00:58:25.040
and some kind of checks and balances would be helpful.
link |
00:58:30.400
So again, I come from Russia.
link |
00:58:34.040
There's something called the Cold War.
link |
00:58:36.840
So let me ask a difficult question here
link |
00:58:39.240
looking at conflict.
link |
00:58:40.720
Steven Pinker written a great book
link |
00:58:42.160
that conflict all over the world is decreasing in general.
link |
00:58:45.440
But do you have a sense that having written
link |
00:58:49.680
the book AI Superpowers,
link |
00:58:51.800
do you see a major international conflict
link |
00:58:54.440
potentially arising between major nations,
link |
00:58:57.840
whatever they are, whether it's Russia, China,
link |
00:59:00.400
European nations, United States or others
link |
00:59:04.120
in the next 10, 20, 50 years around AI,
link |
00:59:07.720
around the digital space, cyberspace?
link |
00:59:10.200
Do you worry about that?
link |
00:59:12.120
Is that something we need to think about
link |
00:59:15.520
and try to alleviate or prevent?
link |
00:59:19.600
I believe in greater engagement.
link |
00:59:22.680
A lot of the worries about more powerful AI
link |
00:59:26.720
are based on a arms race metaphor.
link |
00:59:33.280
And when you extrapolate into military kinds of scenarios,
link |
00:59:41.560
AI can automate and autonomous weapons
link |
00:59:46.560
that needs to be controlled somehow
link |
00:59:48.800
and autonomous decision making
link |
00:59:51.640
can lead to not enough time to fix international crises.
link |
00:59:57.560
So I actually believe a Cold War mentality
link |
01:00:00.880
would be very dangerous
link |
01:00:02.480
because should two countries rely on AI
link |
01:00:05.560
to make certain decisions
link |
01:00:07.400
and they don't even talk to each other,
link |
01:00:10.040
they do their own scenario planning,
link |
01:00:12.120
then something could easily go wrong.
link |
01:00:15.120
I think engagement, interaction, some protocols
link |
01:00:18.960
to avoid inadvertent disasters is actually needed.
link |
01:00:25.120
So it's natural for each country to want to be the best,
link |
01:00:29.120
whether it's in nuclear technologies or AI or bio.
link |
01:00:34.800
But I think it's important to realize
link |
01:00:37.720
if each country has a black box AI
link |
01:00:41.360
and don't talk to each other,
link |
01:00:43.280
that probably presents greater challenges to humanity
link |
01:00:49.280
than if they interacted.
link |
01:00:51.480
I think there can still be competition,
link |
01:00:53.760
but with some degree of protocol for interaction,
link |
01:00:57.080
just like when there was a nuclear competition,
link |
01:01:02.160
there were some protocol for deterrence
link |
01:01:04.880
among US, Russia, and China.
link |
01:01:08.000
And I think that engagement is needed.
link |
01:01:10.880
So of course, we're still far from AI
link |
01:01:13.520
presenting that kind of danger.
link |
01:01:16.000
But what I worry the most about
link |
01:01:18.400
is the level of engagement seems to be coming down.
link |
01:01:23.000
The level of distrust seems to be going up,
link |
01:01:26.360
especially from the US towards other large countries
link |
01:01:30.240
such as China and of course, and Russia, yes.
link |
01:01:33.400
Is there a way to make that better?
link |
01:01:34.680
So let's beautifully put level of engagement
link |
01:01:37.240
and even just basic trust and communication
link |
01:01:40.680
as opposed to sort of making artificial enemies
link |
01:01:48.880
out of particular countries.
link |
01:01:53.360
Do you have a sense how we can make it better?
link |
01:01:57.160
Actionable items that as a society we can take on?
link |
01:02:01.720
I'm not an expert at geopolitics,
link |
01:02:05.000
but I would say that we look pretty foolish as humankind
link |
01:02:10.800
when we are faced with the opportunity
link |
01:02:13.200
to create $16 trillion for humanity,
link |
01:02:19.520
and yet we're not solving fundamental problems
link |
01:02:26.040
with parts of the world still in poverty.
link |
01:02:29.520
And for the first time,
link |
01:02:31.320
we have the resources to overcome poverty and hunger.
link |
01:02:34.600
We're not using it on that,
link |
01:02:35.960
but we're fueling competition among superpowers.
link |
01:02:38.800
And that's a very unfortunate thing.
link |
01:02:41.880
If we become utopian for a moment,
link |
01:02:44.760
imagine a benevolent world government
link |
01:02:52.240
that has this $16 trillion and maybe some AI
link |
01:02:56.120
to figure out how to use it to deal with diseases
link |
01:02:59.280
and problems and hate and things like that.
link |
01:03:02.640
World would be a lot better off.
link |
01:03:04.840
So what is wrong with the current world?
link |
01:03:07.600
I think the people with more skill than I
link |
01:03:11.040
should think about this.
link |
01:03:13.920
And then the geopolitics issue with superpower competition
link |
01:03:16.920
is one side of the issue.
link |
01:03:19.360
There's another side which I worry maybe even more,
link |
01:03:24.040
which is as the $16 trillion all gets made by US and China
link |
01:03:29.360
and a few of the other developed countries,
link |
01:03:32.040
the poorer country will get nothing
link |
01:03:34.280
because they don't have technology
link |
01:03:36.880
and the wealth disparity and inequality will increase.
link |
01:03:42.440
So a poorer country with a large population
link |
01:03:45.880
will not only benefit from the AI boom
link |
01:03:48.520
or other technology booms,
link |
01:03:50.360
but they will have their workers
link |
01:03:52.360
who previously had hoped they could do the China model
link |
01:03:56.040
and do outsource manufacturing or the India model
link |
01:03:58.840
so they could do the outsource process or call center.
link |
01:04:02.640
Well, all those jobs are gonna be gone in 10 or 15 years.
link |
01:04:05.800
So the individual citizen may be a net liability,
link |
01:04:12.080
I mean, financially speaking to a poorer country
link |
01:04:15.040
and not an asset to claw itself out of poverty.
link |
01:04:19.800
So in that kind of situation,
link |
01:04:22.640
these large countries with not much tech
link |
01:04:26.400
are going to be facing a downward spiral
link |
01:04:30.080
and it's unclear what could be done.
link |
01:04:33.120
And then when we look back
link |
01:04:34.720
and say there's $16 trillion being created
link |
01:04:37.600
and it's all being kept by US, China
link |
01:04:39.720
and other developed countries, it just doesn't feel right.
link |
01:04:43.360
So I hope people who know about geopolitics
link |
01:04:46.920
can find solutions that's beyond my expertise.
link |
01:04:50.880
So different countries that we've talked about
link |
01:04:53.160
have different value systems.
link |
01:04:55.200
If you look at the United States,
link |
01:04:56.920
to an almost extreme degree,
link |
01:04:58.960
there is an absolute desire for freedom of speech.
link |
01:05:03.400
If you look at a country where I was raised,
link |
01:05:05.160
that desire just amongst the people
link |
01:05:06.960
is not as elevated as it is to basically fundamental level
link |
01:05:15.040
to the essence of what it means to be America, right?
link |
01:05:17.560
And the same is true with China,
link |
01:05:19.160
there's different value systems.
link |
01:05:21.480
There's some censorship of internet content
link |
01:05:26.840
that China and Russia and many other countries undertake.
link |
01:05:31.280
Do you see that having effects on innovation,
link |
01:05:36.760
other aspects of some of the tech stuff,
link |
01:05:38.880
AI development we talked about,
link |
01:05:40.920
and maybe from another angle,
link |
01:05:42.520
do you see that changing in different ways
link |
01:05:46.200
over the next 10 years, 20 years, 50 years
link |
01:05:49.560
as China continues to grow as it does now
link |
01:05:53.000
in its tech innovation?
link |
01:05:55.720
There's a common belief
link |
01:05:57.200
that full freedom of speech and expression
link |
01:06:01.040
is correlated with creativity,
link |
01:06:03.040
which is correlated with entrepreneurial success.
link |
01:06:08.520
I think empirically we have seen that is not true
link |
01:06:13.200
and China has been successful.
link |
01:06:15.600
That's not to say the fundamental values are not right
link |
01:06:19.600
or not the best,
link |
01:06:20.840
but it's just that perfect correlation isn't there.
link |
01:06:25.880
It's hard to read the tea leaves on opening up or not
link |
01:06:30.560
in any country,
link |
01:06:31.720
and I've not been very good at that in my past predictions,
link |
01:06:37.000
but I do believe every country
link |
01:06:40.840
shares a lot of fundamental values for the longterm.
link |
01:06:47.440
So China is drafting its privacy policy
link |
01:06:54.480
for individual citizens,
link |
01:06:57.240
and they don't look that different
link |
01:07:00.000
from the American or European ones.
link |
01:07:03.240
So people do want to protect their privacy
link |
01:07:07.600
and have the opportunity to express
link |
01:07:10.680
and I think the fundamental values are there.
link |
01:07:14.200
The question is in the execution and timing,
link |
01:07:17.920
how soon or when will that start to open up?
link |
01:07:21.760
So as long as each government knows
link |
01:07:25.520
ultimately people want that kind of protection,
link |
01:07:29.200
there should be a plan to move towards that
link |
01:07:32.240
as to when or how and I'm not an expert.
link |
01:07:36.280
On the point of privacy to me, it's really interesting.
link |
01:07:39.040
So AI needs data to create
link |
01:07:42.520
a personalized awesome experience, right?
link |
01:07:45.520
I'm just speaking generally in terms of products.
link |
01:07:48.560
And then we have currently, depending on the age
link |
01:07:51.360
and depending on the demographics of who we're talking about,
link |
01:07:54.000
some people are more or less concerned
link |
01:07:55.840
about the amount of data they hand over.
link |
01:07:59.040
So in your view, how do we get this balance right
link |
01:08:04.280
that we provide an amazing experience
link |
01:08:07.120
to people that use products?
link |
01:08:09.920
You look at Facebook, the more Facebook knows about you,
link |
01:08:13.440
yes, it's scary to say, the better it can probably,
link |
01:08:19.360
better experience it can probably create.
link |
01:08:21.200
So in your view, how do we get that balance right?
link |
01:08:25.160
Yes, I think a lot of people have a misunderstanding
link |
01:08:30.400
that it's okay and possible to just rip all the data out
link |
01:08:35.080
from a provider and give it back to you.
link |
01:08:38.240
So you can deny them access to further data
link |
01:08:41.160
and still enjoy the services we have.
link |
01:08:44.080
If we take back all the data,
link |
01:08:46.240
all the services will give us nonsense.
link |
01:08:48.360
We'll no longer be able to use products that function well
link |
01:08:52.360
in terms of right ranking, right products,
link |
01:08:56.160
right user experience.
link |
01:08:57.880
So yet I do understand we don't want to permit misuse
link |
01:09:02.880
of the data from legal policy standpoint.
link |
01:09:07.520
I think there can be severe punishment
link |
01:09:11.160
for those who have egregious misuse of the data.
link |
01:09:16.200
That's I think a good first step.
link |
01:09:19.600
Actually China in this side on this aspect
link |
01:09:22.680
has very strong laws about people who sell
link |
01:09:25.480
or give data to other companies.
link |
01:09:27.960
And that over the past few years,
link |
01:09:30.080
since that law came into effect,
link |
01:09:33.560
pretty much eradicated the illegal distribution,
link |
01:09:38.760
sharing of data.
link |
01:09:40.560
Additionally, I think giving,
link |
01:09:45.440
I think technology is often a very good way
link |
01:09:50.120
to solve technology misuse.
link |
01:09:52.760
So can we come up with new technologies
link |
01:09:56.200
that will let us have our cake and eat it too?
link |
01:09:58.880
People are looking into homomorphic encryption,
link |
01:10:01.960
which is letting you keep the data,
link |
01:10:04.360
have it encrypted and train on encrypted data.
link |
01:10:07.360
Of course, we haven't solved that one yet,
link |
01:10:09.080
but that kind of direction may be worth pursuing.
link |
01:10:13.400
Also federated learning,
link |
01:10:15.160
which would allow one hospital
link |
01:10:17.240
to train on its hospital's patient data fully
link |
01:10:20.000
because they have a license for that.
link |
01:10:22.400
And then hospitals would then share their models,
link |
01:10:24.800
not data, but models to create a super AI.
link |
01:10:28.040
And that also maybe has some promise.
link |
01:10:30.560
So I would want to encourage us to be open minded
link |
01:10:34.160
and think of this as not just the policy binary, yes, no,
link |
01:10:39.640
but letting the technologists try to find solutions
link |
01:10:42.800
to let us have our cake and eat it too,
link |
01:10:44.840
or have most of our cake and eat most of it too.
link |
01:10:48.400
Finally, I think giving each end user a choice is important
link |
01:10:52.920
and having transparency is important.
link |
01:10:55.400
Also, I think that's universal,
link |
01:10:57.400
but the choice you give to the user
link |
01:11:00.560
should not be at a granular level
link |
01:11:02.320
that the user cannot understand.
link |
01:11:04.720
GDPR today causes all these popups of yes, no,
link |
01:11:09.120
will you give this site this right
link |
01:11:10.560
to use this part of your data?
link |
01:11:12.360
I don't think any user understands
link |
01:11:15.000
what they're saying yes or no to.
link |
01:11:17.000
And I suspect most are just saying yes
link |
01:11:18.960
because they don't understand it.
link |
01:11:20.760
So while GDPR in its current implementation
link |
01:11:25.600
has lived up to its promise of transparency and user choice,
link |
01:11:30.360
it implemented it in such a way
link |
01:11:33.000
that really didn't deliver the spirit of GDPR.
link |
01:11:39.080
It fit the letter, but not the spirit.
link |
01:11:41.560
So again, I think we need to think about
link |
01:11:43.760
is there a way to fit the spirit of GDPR
link |
01:11:48.000
by using some kind of technology?
link |
01:11:50.600
Can we have a slider that's an AI trying to figure out
link |
01:11:54.640
how much you want to slide between
link |
01:11:57.520
perfect protection security of your personal data
link |
01:12:01.520
versus a high degree of convenience
link |
01:12:04.080
with some risks of not having full privacy?
link |
01:12:08.120
Each user should have some preference
link |
01:12:10.080
and that gives you the user choice.
link |
01:12:12.000
But maybe we should turn the problem on its head
link |
01:12:14.840
and ask can there be an AI algorithm that can customize this?
link |
01:12:18.840
Because we can understand the slider,
link |
01:12:21.120
but we sure cannot understand every popup question.
link |
01:12:25.080
And I think getting that right
link |
01:12:27.200
requires getting the balance between
link |
01:12:29.720
what we talked about earlier,
link |
01:12:30.760
which is heart and soul
link |
01:12:32.720
versus profit driven decisions and strategy.
link |
01:12:37.120
I think from my perspective,
link |
01:12:40.200
the best way to make a lot of money in the long term
link |
01:12:43.080
is to keep your heart and soul intact.
link |
01:12:46.760
I think getting that slider right in the short term
link |
01:12:50.640
may feel like you'll be sacrificing profit,
link |
01:12:54.080
but in the long term,
link |
01:12:55.760
you'll be gaining user trust
link |
01:12:57.600
and providing a great experience.
link |
01:12:59.520
Do you share that kind of view in general?
link |
01:13:02.000
Yes, absolutely.
link |
01:13:03.240
I sure would hope there is a way
link |
01:13:07.200
we can do long term projects
link |
01:13:09.600
that really do the right thing.
link |
01:13:12.000
I think a lot of people who embrace GDPR,
link |
01:13:15.240
their heart's in the right place.
link |
01:13:16.960
I think they just need to figure out how to build a solution.
link |
01:13:20.680
I've heard utopians talk about solutions
link |
01:13:23.360
that get me excited,
link |
01:13:24.480
but I'm not sure how in the current funding environment
link |
01:13:27.880
they can get started.
link |
01:13:29.320
People talk about,
link |
01:13:30.600
imagine this crowdsourced data collection
link |
01:13:36.440
that we all trust.
link |
01:13:37.880
And then we have these agents
link |
01:13:40.720
that we ask the trusted agent to...
link |
01:13:45.720
That agent only, that platform,
link |
01:13:48.880
so a trusted joint platform
link |
01:13:51.280
that we all believe is trustworthy,
link |
01:13:55.120
that can give us all the closed loop personal suggestions
link |
01:14:03.080
by the new social network, new search engine,
link |
01:14:06.200
new eCommerce engine that has access
link |
01:14:08.600
to even more of our data,
link |
01:14:10.360
but not directly, but indirectly.
link |
01:14:12.400
So I think that general concept
link |
01:14:14.640
of licensing to some trusted engine
link |
01:14:18.520
and finding a way to trust that engine
link |
01:14:20.640
seems like a great idea.
link |
01:14:22.360
But if you think how long it's gonna take
link |
01:14:24.240
to implement and tweak and develop it right,
link |
01:14:27.760
as well as to collect all the trusts
link |
01:14:29.920
and the data from the people,
link |
01:14:31.360
it's beyond the current cycle of venture capital.
link |
01:14:34.960
So how do you do that is a big question.
link |
01:14:38.120
You've recently had a fight with cancer,
link |
01:14:41.840
stage four lymphoma and in a sort of deep personal level,
link |
01:14:48.240
what did it feel like in the darker moments
link |
01:14:51.080
to face your own mortality?
link |
01:14:54.840
Well, I've been the workaholic my whole life
link |
01:14:57.880
and I've basically worked nine, nine, six,
link |
01:15:01.400
nine a.m. to nine p.m. six days a week, roughly.
link |
01:15:04.640
And I didn't really pay a lot of attention
link |
01:15:07.920
to my family, friends, and people who loved me.
link |
01:15:10.680
And my life revolved around optimizing for work.
link |
01:15:14.480
While my work was not routine,
link |
01:15:16.920
my optimization really what made my life
link |
01:15:23.240
basically very mechanical process.
link |
01:15:25.640
But I got a lot of highs out of it
link |
01:15:28.360
because of accomplishments
link |
01:15:30.960
that I thought were really important and dear
link |
01:15:34.400
and the highest priority to me.
link |
01:15:36.720
But when I faced mortality
link |
01:15:38.560
and the possible death in matter of months,
link |
01:15:41.960
I suddenly realized that this really meant nothing to me,
link |
01:15:45.600
that I didn't feel like working for another minute,
link |
01:15:48.560
that if I had six months left in my life,
link |
01:15:51.000
I would spend it all with my loved ones
link |
01:15:54.280
and thanking them, giving them love back
link |
01:15:57.480
and apologizing to them that I lived my life the wrong way.
link |
01:16:01.960
So that moment of reckoning
link |
01:16:05.960
caused me to really rethink that why we exist in this world
link |
01:16:11.520
is something that we might be too much shaped by the society
link |
01:16:17.960
to think that success and accomplishments is why we live.
link |
01:16:22.040
But while that can get you
link |
01:16:26.320
periodic successes and satisfaction,
link |
01:16:29.680
it's really in the facing death
link |
01:16:33.200
you see what's truly important to you.
link |
01:16:35.840
So as a result of going through the challenges with cancer,
link |
01:16:41.960
I've resolved to live a more balanced lifestyle.
link |
01:16:45.720
I'm now in remission, knock on wood,
link |
01:16:48.920
and I'm spending more time with my family.
link |
01:16:52.440
My wife travels with me.
link |
01:16:54.800
When my kids need me, I spend more time with them.
link |
01:16:58.000
And before I used to prioritize everything around work.
link |
01:17:02.680
When I had a little bit of time,
link |
01:17:03.960
I would dole it out to my family.
link |
01:17:06.240
Now, when my family needs something, really needs something,
link |
01:17:09.880
I drop everything at work and go to them.
link |
01:17:12.640
And then in the time remaining, I allocate to work.
link |
01:17:15.880
But one's family is very understanding.
link |
01:17:19.000
It's not like they will take 50 hours a week from me.
link |
01:17:23.160
So I'm actually able to still work pretty hard,
link |
01:17:27.120
maybe 10 hours less per week.
link |
01:17:29.280
So I realized the most important thing in my life
link |
01:17:32.720
is really love and the people I love.
link |
01:17:36.280
And I give that the highest priority.
link |
01:17:38.680
It isn't the only thing I do,
link |
01:17:40.680
but when that is needed, I put that at the top priority
link |
01:17:45.880
and I feel much better and I feel much more balanced.
link |
01:17:50.080
And I think this also gives a hint
link |
01:17:53.080
as to a life of routine work, a life of pursuit of numbers.
link |
01:17:58.080
While my job was not routine, it was in pursuit of numbers,
link |
01:18:02.920
pursuit of can I make more money?
link |
01:18:04.960
Can I fund more great companies?
link |
01:18:07.360
Can I raise more money?
link |
01:18:08.920
Can I make sure our VC is ranked higher and higher
link |
01:18:12.080
every year?
link |
01:18:13.360
This competitive nature of driving for bigger numbers
link |
01:18:18.800
and better numbers became a endless pursuit
link |
01:18:25.200
that's mechanical.
link |
01:18:26.640
And bigger numbers really didn't make me happier.
link |
01:18:31.880
And faced with death, I realized bigger numbers
link |
01:18:34.680
really meant nothing.
link |
01:18:36.360
And what was important is that people who have given
link |
01:18:41.040
their heart and their love to me
link |
01:18:42.840
deserve for me to do the same.
link |
01:18:45.640
So there's deep, profound truth in that,
link |
01:18:48.400
that everyone should hear and internalize.
link |
01:18:52.000
I mean, that's really powerful for you to say that.
link |
01:18:55.420
I have to ask sort of a difficult question here.
link |
01:19:03.060
So I've competed in sports my whole life,
link |
01:19:06.020
looking historically, I'd like to challenge some aspect
link |
01:19:11.780
of that a little bit on the point of hard work.
link |
01:19:15.220
That it feels that there are certain aspects
link |
01:19:18.900
that is the greatest, the most beautiful aspects
link |
01:19:22.020
of human nature is the ability to become obsessed,
link |
01:19:27.740
of becoming extremely passionate to the point where yes,
link |
01:19:31.460
flaws are revealed and just giving yourself fully to a task.
link |
01:19:37.460
That is, in another sense, you mentioned love
link |
01:19:40.800
being important, but in another sense,
link |
01:19:42.380
this kind of obsession, this pure exhibition of passion
link |
01:19:46.660
and hard work is truly what it means to be human.
link |
01:19:50.380
What lessons should we take that's deeper?
link |
01:19:53.140
Because you've accomplished incredible things.
link |
01:19:54.820
You say it chasing numbers,
link |
01:19:57.300
but really there's some incredible work there.
link |
01:20:00.980
So how do you think about that when you look back
link |
01:20:04.980
in your 20s, your 30s, what would you do differently?
link |
01:20:10.020
Would you really take back some of the incredible hard work?
link |
01:20:14.860
I would, but it's in percentages, right?
link |
01:20:19.980
We're both computer scientists.
link |
01:20:22.380
So I think when one balances one's life,
link |
01:20:25.620
when one is younger, you might give a smaller percentage
link |
01:20:30.260
to family, but you would still give them high priority.
link |
01:20:33.720
And when you get older, you would give a larger percentage
link |
01:20:36.340
to them and still the high priority.
link |
01:20:38.500
And when you're near retirement, you give most of it to them
link |
01:20:42.460
and the highest priority.
link |
01:20:43.820
So I think the key point is not that we would work 20 hours
link |
01:20:49.140
less for the whole life and just spend it aimlessly
link |
01:20:52.700
with the family, but that's when the family has a need,
link |
01:20:56.740
when your wife is having a baby,
link |
01:21:00.260
when your daughter has a birthday or when they're depressed
link |
01:21:05.180
or when they're celebrating something
link |
01:21:07.540
or when they have a get together or when we have family time
link |
01:21:11.400
that it's important for us to put down our phone and PC
link |
01:21:14.860
and be a hundred percent with them.
link |
01:21:18.340
And that priority on the things that really matter
link |
01:21:23.740
isn't going to be so taxing that it would eliminate
link |
01:21:29.140
or even dramatically reduce our accomplishments.
link |
01:21:32.020
It might have some impact, but it might also have
link |
01:21:35.180
other impact because if you have a happier family,
link |
01:21:37.940
maybe you fight less.
link |
01:21:39.380
If you fight less, you don't spend time taking care
link |
01:21:43.100
of all the aftermath of a fight.
link |
01:21:45.620
So it's unclear that it would take more time.
link |
01:21:48.220
And if it did, I'd be willing to take that reduction.
link |
01:21:53.260
And it's not a dramatic number, but it's a number
link |
01:21:56.340
that I think would give me a greater degree of happiness
link |
01:22:00.140
and knowing that I've done the right thing
link |
01:22:03.260
and still have plenty of hours to get the success
link |
01:22:08.260
that I want to get.
link |
01:22:09.900
So given the many successful companies that you've launched
link |
01:22:14.460
and much success throughout your career,
link |
01:22:17.340
what advice would you give to young people today looking,
link |
01:22:25.440
or it doesn't have to be young,
link |
01:22:26.780
but people today looking to launch
link |
01:22:28.500
and to create the next $1 billion tech startup
link |
01:22:32.360
or even AI based startup?
link |
01:22:34.280
I would suggest that people understand
link |
01:22:39.800
technology waves move quickly.
link |
01:22:42.720
What worked two years ago may not work today.
link |
01:22:45.920
And that is very much case in point for AI.
link |
01:22:49.700
I think two years ago, or maybe three years ago,
link |
01:22:53.200
you certainly could say I have a couple
link |
01:22:55.320
of super smart PhDs and we're not sure
link |
01:22:58.880
what we're gonna do, but here's how we're gonna start
link |
01:23:01.920
and get funding for a very high valuation.
link |
01:23:05.200
Those days are over because AI is going
link |
01:23:08.480
from rocket science towards mainstream,
link |
01:23:11.520
not yet commodity, but more mainstream.
link |
01:23:14.400
So first the creation of any company
link |
01:23:19.400
to a venture capitalists has to be creation
link |
01:23:22.720
of business value and monetary value.
link |
01:23:26.200
And when you have a very scarce commodity,
link |
01:23:29.800
VCs may be willing to accept greater uncertainty.
link |
01:23:35.040
But now the number of people who have the equivalent
link |
01:23:38.560
of PhD three years ago, because that can be learned
link |
01:23:42.840
more quickly, platforms are emerging,
link |
01:23:46.080
the cost to become a AI engineer is much lower
link |
01:23:49.580
and there are many more AI engineers.
link |
01:23:51.700
So the market is different.
link |
01:23:53.960
So I would suggest someone who wants to build an AI company
link |
01:23:57.440
be thinking about the normal business questions.
link |
01:24:01.480
What customer cases are you trying to address?
link |
01:24:06.120
What kind of pain are you trying to address?
link |
01:24:08.600
How does that translate to value?
link |
01:24:10.680
How will you extract value and get paid
link |
01:24:14.680
through what channel and how much business value
link |
01:24:18.120
will get created?
link |
01:24:19.920
That today needs to be thought about much earlier upfront
link |
01:24:24.520
than it did three years ago.
link |
01:24:26.720
The scarcity question of AI talent has changed.
link |
01:24:30.500
The number of AI talent has changed.
link |
01:24:32.800
So now you need not just AI, but also understanding
link |
01:24:37.640
of business customer and the marketplace.
link |
01:24:41.840
So I also think you should have a more reasonable
link |
01:24:48.000
valuation expectation and growth expectation.
link |
01:24:52.360
There's gonna be more competition.
link |
01:24:54.080
But the good news though, is that AI technologies
link |
01:24:57.840
are now more available in open source.
link |
01:25:00.740
TensorFlow, PyTorch and such tools are much easier to use.
link |
01:25:06.640
So you should be able to experiment and get results
link |
01:25:11.760
iteratively faster than before.
link |
01:25:14.240
So take more of a business mindset to this,
link |
01:25:18.540
think less of this as a laboratory taken into a company,
link |
01:25:23.540
because we've gone beyond that stage.
link |
01:25:26.140
The only exception is if you truly have a breakthrough
link |
01:25:29.740
in some technology that really no one has,
link |
01:25:32.340
then the old way still works.
link |
01:25:34.660
But I think that's harder and harder now.
link |
01:25:37.140
So I know you believe as many do that we're far
link |
01:25:41.140
from creating an artificial general intelligence system.
link |
01:25:45.420
But say once we do, and you get to ask her one question,
link |
01:25:50.420
what would that question be?
link |
01:25:57.640
What is it that differentiates you and me?
link |
01:26:02.180
Beautifully put, Kaifu, thank you so much
link |
01:26:04.260
for your time today.
link |
01:26:05.760
Thank you.