Episode 49, November 7, 2018
In 1998, Microsoft Research opened a small lab in Beijing to expand its research efforts and draw on the immense high-tech talent pool in China. No one expected that only twenty years later, Microsoft Research Asia would become the dynamic organization it is today, with innovative research contributing to nearly every part of Microsoft’s business. Dr. Hsiao-Wuen Hon has watched it grow from the beginning and this year, celebrates the lab’s 20th anniversary as Managing Director, Corporate Vice President and Chairman of Microsoft’s Asia-Pacific R&D Group.
On today’s podcast, Dr. Hon gives us a brief history of Microsoft Research Asia, from its humble beginnings to its significant role in the AI boom today, talks about Microsoft Research Asia’s unique talent pipeline, shares his vision for the complementary roles of machine intelligence and human wisdom, and explains why, he believes, the more progress we make in AI, the better we understand ourselves.
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Hsiao-Wuen Hon: We want the researchers to really think about how far they can push technology. How far they can push the state-of-the-art. And so, this is why we encourage people to take risks and we even go as far as to tell them, if you think too much about technology, most likely you will make too small a step, and that’s not good enough in research. Because if the most thing we do are incremental, then I think research will fail its purpose.
Host: You’re listening to the Microsoft Research Podcast, a show that brings you closer to the cutting-edge of technology research and the scientists behind it. I’m your host, Gretchen Huizinga.
Host: In 1998, Microsoft Research opened a small lab in Beijing to expand its research efforts and draw on the immense high-tech talent pool in China. No one expected that only twenty years later, MSR Asia would become the dynamic organization it is today, with innovative research contributing to nearly every part of Microsoft’s business. Dr. Hsiao-Wuen Hon has watched it grow from the beginning and this year, celebrates the lab’s 20th anniversary as Managing Director, Corporate Vice President and Chairman of Microsoft’s Asia-Pacific R&D Group.
On today’s podcast, Dr. Hon gives us a brief history of MSR Asia, from its humble beginnings to its significant role in the AI boom today, talks about MSR Asia’s unique talent pipeline, shares his vision for the complementary roles of machine intelligence and human wisdom, and explains why, he believes, the more progress we make in AI, the better we understand ourselves. That and much more on this episode of the Microsoft Research Podcast.
Host: Hsiao-Wuen Hon, welcome to the podcast today, it’s great to have you in person in the studio, all the way from China.
Hsiao-Wuen Hon: Thank you, Gretchen, it’s nice to be here.
Host: So, you’re the Corporate Vice President of Microsoft, Chairman of Microsoft’s Asia-Pacific R&D Group and the Managing Director of Microsoft Research Asia. What has inspired you to do the work you do and to take on this giant set of tasks?
Hsiao-Wuen Hon: I actually think I have the best job in Microsoft… in the world. The reason is, every day when I wake up, I will explore the future possibility. I will do this experiment, that experiment, try this idea, try that idea. I do know not all of them will work. Actually, many of them will fail. I mean, that’s the nature of the game because you really try to explore the unknown. But it’s really the process. And I understand, people like to get a good result. They want to get rewards, they want it to really have impact, and results even. We’re all for that. But I think the feeling of, every day you wake up, you know, you will explore something new, and then, if someone even pays you to do those kinds of work… And a lot of time they even encourage you to take more risk, to think bigger, to actually do more risky projects, that process itself is so enjoyable.
Host: So, you’ve been with Microsoft for a really long time. You started in 1995?
Hsiao-Wuen Hon: Yes.
Host: And that’s not long after Bill Gates started Microsoft Research in 1991. Were you with the research organization when you started?
Hsiao-Wuen Hon: Yes.
Host: What was the vision for a research division, in general, then, and how have you seen the enterprise, writ large, evolve over the years since you’ve been there?
Hsiao-Wuen Hon: If you actually go back to 1991, Microsoft still, compared to today, is a tiny company. But even then, Microsoft already, in the young software industry, is already the undisputed leader. And I think it’s really Bill’s foresight that we really need to continue to move the state-of-the-art, the technology landscape, in the general software area. So, I think he set up the MSR. He wanted that future computers can listen, can understand human language, can actually recognize objects, understand the world, can do the conversation. And I think at that time – I mean, if you remember there’s two AI winters – that’s really, the first winter, right? And so, I think it’s really very gutsy and the foresight of Bill to actually start the research. And I remember when I joined MSR, we had less than forty people. And today we’ve grown to the size of a thousand people. Of course, Microsoft has also grown a lot.
Hsiao-Wuen Hon: And I think the whole industry has also grown a lot. So, I think, certainly it’s a good journey.
Host: So, then the research division was here?
Hsiao-Wuen Hon: Yes.
Host: And you were here?
Hsiao-Wuen Hon: Yes. So, that’s my organization today in China, Microsoft Research Asia. The reason we have Microsoft Research Asia is because we want to expand the company. We want to expand the MSR. So, I remember when I joined, I think, Rick, our big boss in MSR, and Bill, had a conversation. And then we immediately knew, we cannot just have the research lab in the US because we know we won’t hire enough, and also, we don’t believe all the smart and the most passionate people doing research will all come to US to work for Microsoft. So, we basically go to where they are. This is why we start international expansion. And then in ‘97 we did our Europe lab in Cambridge. In ‘98 we actually did the China lab in the Asia Pacific area and then the rest is history. I think the key is, at that time, no one thinks we are even close or willing to invest to actually do those kind of AI, technology development or research. So, this is why I think we should really be very, very thankful to Bill’s foresight, also the willingness to actually invest. Big time.
Host: Put money behind it.
Hsiao-Wuen Hon: Even though Bill knew it will take a long time. And I think Bill probably think it will take more than twenty, thirty years. I don’t think he would predict we’d really have the AI boom today. And today, you just cannot escape a day without any AI news or activity, right? So, I think people thought about that, but at that time, people think about just science fiction. And then the reason they call AI winter, it’s very few people want to invest in it, including government.
Host: Right. And interestingly too, I think most research institutions embedded in industry were applied research. As opposed to, “let’s let some scientific minds have some free reign here, and really think out for that long time.”
Hsiao-Wuen Hon: Yes, you are absolutely right. And I think the company is there to make money.
Hsiao-Wuen Hon: So, typically, most companies can only invest in something on a short-term basis, which it’s actually the right thing. And I think university, government, funding agency can do very long-term research. That’s how our society works. And I think Bill, I think that he recognized the industry and also companies, when they are successful, they need to participate in building this so-called state-of-the-art, advanced, state-of-the-art technology. Because very simple: look at the high-tech world. I think it is because of fundamental technology got advanced. So, the pie… becomes bigger and bigger. People can build the better applications. So, in return, have all this positive feedback cycle. So, every company will benefit. And I think this is why, when we built MSR, the three-core mission was defined very clearly. The first one is advance the state-of-the-art. And that’s really just similar to academic research happening in university. You also encourage the researcher to actually publish all they have done and then share with the whole world. That’s really a very important aspect because in all the science and engineering advancement in our history, we always talk about, you’re standing on the shoulders of the giants, everyone can do further. So, I think that it’s very important for industry, for companies, commercial companies to participate in this state-of-the-art building. And then the second mission, of course, is called technology transfer. Because of course, Microsoft wants to benefit from all the great research results we have done to improve our products. So that will make our products more competitive. And then the third one is incubation, which is also extremely important in our industry, because the breakthroughs really happen in a much, much faster-pace than in any other industry. So, Microsoft will want to make sure we always stay on top of that. And then a better way to do that is to invest and also to invent the future. And I think so the incubation become third part of our core mission.
Host: Let’s talk about Microsoft Research Asia. It’s celebrating a milestone anniversary this year: twenty years in China. Let’s talk a little bit about the expectations for MSR Asia twenty years ago and why you believe this particular lab of MSR has been good for Microsoft, good for China and, actually, even good for the world.
Hsiao-Wuen Hon: So, twenty years ago, the reason we go to China is because we want to expand MSR. And then we know China has a huge number of raw talent, right? On top of that, I think STEM attracts a lot of young kids to start in this area. So, twenty years ago, our first, I would say, milestone, really came from the mission we set up, like first mission, advance the state-of-the-art. I think, to a large extent, we contributed a big part to the effort to bring China to the world-class research landscape. I think really, the first, significant paper published in the world-class journal or conference, really came from our collaboration work with the university faculty and students. But twenty years ago, really the first breakthrough, right, from zero to the landscape, I think we contributed a big part to that effort. And we certainly feel very proud of. And also, not just that, not just really technical landscape and particularly you mentioned how this is good for the world, I think in terms of the academic exchange and the interaction between China and the US, by and large, because we are a US-based company and they get to develop their partnership with university, faculty and student. And now again, China represents, in terms of the graduate student in US, is the biggest source, right? And also, the interaction between the top universities in the US, top universities in China. Now it’s almost on the day-to-day basis and I think we also feel very honored to actually play a big role, to make these efforts known today. And I think we all know, particularly in the science and engineering world of innovation, that more global collaboration and interaction are a good thing for everyone. And they’re talking about Microsoft, of course we benefit from it, right? Our almost all major Microsoft products, over the year until today, all have the MSRA contribution. And then on the incubation part, we also have several technologies inside Microsoft that are totally started and responsible by MSR to actually start the effort.
Host: That’s an amazing track record for twenty years. Anywhere on the planet. That’s just amazing. And so much of it comes from the talent that you get. Talk about MSRA’s particular approach to the talent pipeline. You talk about incubation, you talk about your internship and you talk about your training. Tell us about that.
Hsiao-Wuen Hon: Yes, we always say, in Microsoft, our biggest asset is people, right? And in research, it’s actually more so. How do you generate the basic research result? Hire the best talent. And in China, it’s a little bit different. When we went to China twenty years ago, they don’t really have established researchers in computer science for us to hire. So, we need to help to foster the future talent for computer science research. So, this is why, from day one, we know we need to engage with universities to help, to bring up the students, to prepare them for the future computer science research. Even here today, we have a very, very distinct internship program. Typically, when people think about interns, it’s for people to work in just summer, three, maybe four months, in the lab. In our internships, we always say it’s all year long internship program.
Hsiao-Wuen Hon: One of the reasons we can do that is, many of our senior researchers, including myself, we take professorships in the top universities in China. Because of that, we actually can take on the PhD students. That means, after the students finish the coursework, they will spend two, or even three, years with us to actually do their PhD work supervised by us. So, we actually have interns work in our lab for a long time, and the number is also mind-boggling. We actually have more interns than the full-time employees. Our ratio is about 1.5 to 1, in terms of intern-to-employee ratio. So, the talent fostering is always a big part of our operation. And I think, of course, that, in turn, generates a lot of good results. So, it’s about three years ago we decided to do an MSRA alumni network. So, today we have an alumni network that has more than 5,000 people. Of course, a big part of it is our interns. And then, because unique, the timing and also the way we do this thing, it also totally coincides with the development of the China IT industry. And then you look at the number. We have 10+ alumni which act as the CXO, mostly as CTO, for the public trading IT companies. And then on the academic front, we have 30+ professors, established professors. in the Chinese universities. We also have 50+ founders for the startups in China. And then five of them already reach the “unicorn” status. So, it’s actually, for so many influential people coming out of one organization in China, or even in the whole world, probably is unheard of. So, I think truly it’s a win-win-win situation for Microsoft, for industry, for China. And I think just like today, just like diversity and inclusion area, you’ve got to take a broader view. Not just for yourself because you will only improve or make true progress if the entire ecosystem, entire platform, has the right mix and the presenting of the talent you want, right? Whether it’s diversity, whether it’s the best research talent. If you don’t take this view, I don’t think you will go very far.
Host: Let’s talk about the unique focus of Microsoft Research Asia.
Hsiao-Wuen Hon: So, I guess I can answer this question in the sort of philosophical way. I know people want a good result. I think Microsoft also is a results-driven company and then also it’s easy to report when you actually have a good result and make a good story in the press. But the real day-to-day work in research doesn’t really happen that way. If the researcher will say, well, the reason I do Project A is because I think Project A can generate a great result so I can get a reward, I would say this is probably already the wrong thing to think about. I think the right thing to think about is, we are an organization, we encourage people to focus most of their time on what do they think the future technology will be? And don’t yet think about application yet right? So sometimes we call this speculative research. Once I make progress, there will always be a lot of people who can think about how to apply these technologies to make money, to actually go for the real-world impact. So, we really want the people to change the status quo of technology. Not necessarily status quo of the market share, or number of users, or applications. We have plenty of business people and product people to think about that. We want the researchers to really think about how far they can push technology. How far they can push the state-of-the-art. And so, this is why we encourage people to take risks and we even go as far as to tell them, if you think too much about technology, most likely you will make too small a step, and that’s not good enough in research. Because if the most thing we do are incremental, then I think research will fail its purpose.
Host: So earlier we talked about the AI winter and the AI spring that some people are saying is a result of a number of factors in high tech that are all converging at the same time. Talk a little bit about this AI spring.
Hsiao-Wuen Hon: So, I think early on we mentioned, even myself, I actually experienced two AI winters. And then now, like everyone can notice now, AI is a hot topic that no one can escape from. So, this is why some people call, right now it’s an AI spring. But there are also people, particularly some researchers, who worry is there too much hype? And too much expectation? And then, we might not be able to deliver. We’ll cause another AI winter. So, some people say, maybe now is the AI autumn! But I think that it will happen. I think Microsoft has the right word: digital transformation. Even though the AI technology we have today still has some limitations, but this can do a lot with so-called data-driven intelligence. And that will actually power a lot of the digital transformation for just about everything we do in business, everything we do in life. So that transformation is real. And it’s happening. It’s already happening for a couple years, and it will actually continue at least for the foreseeable future. So that’s, certainly, very exciting in business. But in terms of technology, most of AI today is a black box. You can solve the what problem, but cannot solve the why problem. This, today, is still a very hard problem. We actually barely scratch the surface. We haven’t made even any significant progress yet. But we need to continue to push the technology as a researcher. I use the word AI+HI. So, it’s always that AI helps the human intelligence, helps humans to solve problems together. So, we build AI systems to actually help us to solve, but the algorithms always come from us. So, who is master? It’s actually very clear. And of course, we need to make sure only the master will use the AI in the right way. Not actually use the AI to do any harmful stuff. So that’s really how I think about it.
Host: I like this idea that you just mentioned. The co-evolution of human and machine intelligence. So, could you talk a little bit about why you think co-evolution of intelligence is an important thing to address today?
Hsiao-Wuen Hon: Yeah, I do have a talk I gave, particularly in China, talking about co-evolution of AI and HI, human intelligence. Actually, this is based on my personal experience. When I started AI 20 years ago, I also think of AI very differently than today. And the more discoveries you make in in AI, the more progress you make in AI, lets me, at the same time also, understand our self better, myself better, my intelligence better. And I think the human intelligence, it’s actually built on creativity, not really necessarily built on memorizing a lot of the data. We do see data. We need to be inspired by looking at data. But we cannot look at lots of data or memorize a lot of data. So, in a sense, we invented computers to help us do things we know how to do, so it will free us to think about harder problems, to actually come up with the algorithms for other harder problems. And we also realize our creativity, particularly problem solving, not to mention wisdom… I mean I don’t think I’m qualified to define wisdom… I mean give people wise advice… I think that’s also what humans so uniquely possess. If you ask me this question ten years ago, I probably would not articulate it that way, because I think of intelligence… we used to think of someone who can memorize or someone who can compute very fast, very accurately, think about the one form of the unique intelligence. But today, no one is trying to compete with a calculator, not even talk about a computers. Or, memory, right? I already moved for three years. I still have not remembered my home phone number. So, I think the way we think about intelligence really changes once we make more discoveries. And then the other part I also mentioned, human intelligence is mostly not to do with big data but with small data. Think about Einstein, a hundred plus years ago. He had no equipment to observe. He just hypothesized. We don’t know he hypothesized. And then a hundred years later, we use the modern equipment, we can barely observe those waves. You cannot argue, Einstein certainly has NO big data. Probably has zero data, right? So just like your creativity, right? A lot of times, you just come up with ideas, people ask you, where do you come from? You cannot explain. On the other hand, today’s AI is all based on a huge amounts of data. We cannot comb through so much data, but we can come up with algorithms, to let the computer look through the data. Then, a lot of times, even that is still not enough. You still need to do your predictions and guess, and the creativity, all combined, you actually can make big progress. So, I think of the co-evolution, there’s another aspect: we should also feel lucky. Not feel threatened. We are the first generation of humankind who live together with AI. Something we created, right? So, we can use that as a tool to help us, to solve problems, to inspire us to think about problems in a new way. Also inspire to think about ourselves differently. The reason I’m so optimistic is, we are the master, right? We invent them. Since they are not a real lifeform, I don’t think there’s a moral issue to say, “We are the master!”
Host: Well, it’s fascinating because you know, you listen to the popular press, you listen to some of the big, sort of, naysayer voices out there. That are, “We’re doomed. We’ve created our demise.” And yet, maybe they’re looking at it the wrong way and thinking about it too largely and it’s more, like they say here, “augment, not replace.”
Hsiao-Wuen Hon: The machine has no life. We have the life, right? So, this is why if there’s a machine that does all these harmful things, I guarantee there’s a lifeform designer behind that. There’s got to be a human behind that. Machine has no life. And then no DNA, right? We have the DNA to tell us we need to survive, we need to fight for our genes to continue, so this is why we love our kids, we need to continue our genes… Machines, I mean, come on, the machines get programmed by humans, right? It’s not that there’s a bio-gene telling them they need to fight for survival, fight for resources, right? I mean this is why, philosophically, I am not saying there’s no bad machines. But the source of bad machines has got to be a human behind that.
Host: The bad human.
Hsiao-Wuen Hon: A bad human designer. So, we better regulate the human but not worry about the machine.
Host: Yeah, and maybe it’s not a bad designer but somebody who designed for a good purpose and it got taken on by somebody with bad intentions…
Hsiao-Wuen Hon: But still people…
Host: Absolutely, human actors.
Hsiao-Wuen Hon: Only good or bad. All at the end, all attributed to people.
Host: It’s human. You are, to many of our listeners, an inspiration, especially when it comes to your career in high tech. Among your titles is corporate vice president, chairman, distinguished scientist, managing director, IEEE fellow. But you didn’t start there. Much like Microsoft Research Asia, you started small. What was your path to where you are today?
Hsiao-Wuen Hon: Yeah, I think when I grew up, for whatever reason, I just loved math. But at the same time, I also liked application. Or you can say I liked to see real-world impact. So, this is why, looking back, it’s actually not surprising I end up here. So, I got a Double E undergraduate degree. And I really liked abstract math, so, I got to study computer science at CMU. Got my PhD. After PhD, typically when you got a PhD, you can go to academic. I liked academic. But I also think I want to see application. I want to see the impact. And the impact, at that time, I decided well, impact, hmmm, doing computer science… If I can see that technology can benefit, can be used by millions – at that time I think about millions – today, I also think about billions, right? Billions of people. So, this is why I ended up joining Microsoft. And also, going back to your first question, Microsoft started research. That’s such an exciting thing. I mean not just products. I don’t think I would be happy just doing products and not actually push the technology envelope to explore all this future possibility, right? So, the combination of research and then product impact, not directly, indirect, because I’m not responsible for product, but if I see my technology, whether it’s computer vision, or speech, or assistive technology being used by millions and billions of people, I think that I feel I really do something tangible for humankind. So, if I look, really look back, I think two things: one is, it’s not surprising I ended up here, but second, I also say I need to be very thankful. Microsoft gave me such a wonderful opportunity for me to fulfill not only my goal, also gave me a job I actually find fun to do every day, and get up, every morning knowing I will explore this and that, and will try this and try that. And then the process itself, a lot of time, is enjoyable already. So enjoyable already. Not to mention, if I can have a good result along the way, it sounds like a wonderful life.
Host: Hsiao-Wuen Hon, thank you so much for joining us today. It’s been inspiring.
Hsiao-Wuen Hon: Thank you.
To learn more about Dr. Hsiao-Wuen Hon and the latest innovations from MSR Asia, visit Microsoft.com/research.