My founding principle for our organization is, “people first.” I believe that to build great products, you start with talented people and invest in their work and their individual well-being. The great products they make will in turn bring customers.
One of the best things we get from work is the satisfaction of being part of a group—bringing a divers set of skills together to accomplish something that no individual can do alone. We’re wired to feel good when we act together towards a common goal—Sebastian Junger (author of “The Perfect Storm”) writes in “Tribe” that interdependence and community are required for human happiness. If you played in your school orchestra or soccer team, you know the feeling; I get it with my running buddies when we silently sprint the last half mile, pacing each other to the end of the trail.
In the IBM Private Cloud team we have almost 3,000 people, and a list of clients who represent a significant piece of the financial, government, and commercial world. And it just so happens that we sit at a “tipping point” with customers wanting the advantages of all that cloud offers, plus premiere machine learning technology, in a private cloud environment.
As a team of thousands working in labs from Austin to Zurich we have grown to know each other beyond the sometimes less than energizing interface of email.
I decided to conduct a series of interviews, You in the Private Cloud.. It’s a great way to bring new information forward that increases our collective knowledge.
People who are talented and engaged tend to have interesting lives outside of work—hobbies that test limits and relationships that matter, so I’ll be asking about that as well.
To kick off the series I talked to Kewei Wei last week in Beijing. Kewei is the lead developer for Machine Learning on z Systems in our IBM China Development Lab.
Kewei and I had just come from a meeting with a customer – one of the largest financial institutions in the world. They had just told us they want to be part of the closed beta of our machine learning offering on z Systems – a testament to the tremendous work Kewei and the team have done. We sat down in a quiet part of the office and I asked him what he thought:
Kewei: This is exciting news! We weren’t sure how quickly this customer would move into new technologies. But I believe they were, to a certain extent, feigning reluctance; they’ve been trying all along to find a balance between moving ahead with machine learning and other new technologies, and keeping the stability and security that they absolutely need to maintain. They cannot take risks with financial information, given their global position and their scale. Now we have an opportunity: if we can show them during the closed beta that we have the ability to be both of these things to them—a protector of security and stability, as we always have been, and now also the conduit to state of the art machine learning technology, they’ll take the risk and move forward with us.
You worked on z Systems for 10 years. Then, 3 months ago, out of the blue you’re told you’re leading Machine Learning on z Systems , and you have 90 days to deliver. How was that work day for you?
To be completely honest, my first thought was, “This is impossible”. In ten years in the z world, we’d never done anything like this; our release schedule was more like 3 years. But we did it, and I believe it’s because we were all passionate about machine learning. We know it’s the technology that’s going to make the greatest change for the world, and that’s something we all wanted to be part of. So we put our heart into it. We learned the open source libraries, the skills we needed to deliver the new micro-services structure, and, critically, we learned how to prioritize. With so much to learn, if we hadn’t done that, we wouldn’t have been able to deliver.
Why is machine learning so exciting to you? What would you like to solve with AI?
I’d like to build machine learning AI to help us perform systems facediagnoses and fix defects. That way, we humans could have time to focus on how to make our world better, instead of just making things work correctly.
A fine distinction. Tell me your take on the Private Cloud.
I think it’s a good thing. We’ve been hearing about the importance of public cloud for a long time. Customers are telling us they will not be ready for the move to public cloud in a short period of time. But they’re also telling us they can’t afford to wait years for security to mature in the cloud. They need machine learning now, behind the firewall, to be competitive.
Private Cloud represents the reality of the market—what our clients are asking for. It means we’re helping them move forward, but without having to face some of the perceived risks of some public clouds.
I also believe innovation in machine learning will happen in Private Cloud. The foundation of machine learning is, of course, data, and as of today, the majority of critical data is still in the hands of customers who keep it behind the firewall. And customers know they have to use machine learning in their core business, which is behind the firewall. They’ll invest in private AI, and we’ll get to build that.
In terms of innovation, what do you see in China that might come to the US from China’s hyper-evolved app technology, or from the broad consumer adoption of virtual reality there?
Honestly, looking at from technology perspective, there is nothing new in what China is doing today. I think the key is to move fast. Don’t wait, listen to consumers, be willing to take risks, dare to fail and always move faster than your competitors
Where did you grow up, and how did you come to be an engineer in Beijing?
I’m from Jinzhou—it’s a city of about 3 million people (small, in Chinese terms) in Liaoning Province in the northeast of China. My father was a bus driver and my mother worked for an oil company. I am very proud of them! When I was 18 I came to Beijing and enrolled in University. In one of my very first classes, a professor helped me write a Pascal program to simulate a game of chess. I was shocked that this was possible—and in a way I never stopped being shocked, excited, I mean, by what we can do with programming.
What do you like to do when you’re not programming?
Read! I love history books. I just finished “Zhang Juzheng”, I a biography of a famous Chengxiang –a prime minister- in the Ming Dynasty. I’m looking for a book on European history for my next one. I bought Gibbon’s “The History of the Decline and Fall of the Roman Empire” but a few chapters in I realized I’d better start looking for a thinner version of it.
Realistic. I also love to travel with my wife and my 5-year-old son. I think the most fun thing in life is being in a beautiful place, in the mountains or in a relaxing beach city like Xiamen, with the people you love most.
What do people talk about in China when they talk technology? Are people concerned about security and privacy? Or Artificial intelligence displacing the traditional work of people in the labor market?
What concerns individual consumers far more than security in China is convenience and lower cost. For example, the latest hot business here is food delivery, people love it that we can order a food from a nice restaurant from an app and get it within 30 minutes, for less than we’d pay to eat in the restaurant. Part of the reason it’s so low cost right now is because China’s internet companies are investing without regard to cost: they want to lock in users for long-term return.
It’s almost the inverse of the concerns of government or large enterprise: individuals choose convenience over security every time. For example, you can pay by Alipay or Wechat almost everywhere, including places like vegetable markets where POS probably will never exist. Alipay and Wechat are not as secure as credit cards, but they are far simpler to use. It helps that Alipay and Wechat have committed to compensate consumers if you lose money because of any security defects.
As for AI displacing traditional labor, people in China don’t worry about it much. AI is still a pretty new concept to Chinese. What we know is just AlphaGo or Waston. It still sounds like something far off in the future, not close to our daily lives at all. But AI is starting to draw more and more attention, so this could change soon.
Overall, tech in China is booming, and companies like Alibaba and Huawei are knocking at your door. Why stay at IBM, with those kind of opportunities?
Oh, that’s an easy one: the people. In my opinions you can’t find a better company in the world for talent. I have the greatest people around me, and it’s because of them I had the confidence that I could deliver this project on time.
Kewei, having you on the team has been a blessing: you have been a true IBMer, and delivered machine learning on z Systems in such a short time , an impossible task. Companies would probably not buy our products without people like you. Thank you.
You are welcome. I enjoy it. If I worked somewhere else, I’d have to quit and look for a new job every time I wanted to try something new —but not here. At IBM, we have tremendous chances to try new things we like to do.
Name: Kewei We
Years at IBM: 11
Lives and works in: Beijing, China
Currently working on: Machine Learning Z Systems
Favorite programming language: PL/X
His top 3 beach books for not-so-light reading: “Three Kingdoms” by Luo Guanzhong, “Blood Remuneration Law” by Li Qiang, and “The Shortest History of Europe” by John Hirst
Dinesh Nirmal – Vice President, IBM Analytics Development
Follow me on Twitter: @dineshknirmal