How Programming Languages Quietly Run the World with Dr. Ben Zorn
Episode 6, January 3, 2018
How Programming Languages Quietly Run the World with Dr. Ben Zorn
In an era of AI breakthroughs and other exciting advances in computer science, Dr. Ben Zorn would like to remind us that behind every great technical revolution is… a programming language. As a Principal Researcher and the Co-director of RiSE – or Research in Software Engineering – group at Microsoft Research, Dr. Zorn has dedicated his life to making sure the software that now touches nearly everything in our lives is easy, accurate, reliable and secure. Today, Dr. Zorn tells us some great stories about bugs and whales, warns us against the dumb side of “smart” objects, shares about his group’s attempt to scale the Everest of software security, and makes a great case that the most important programming language in the world today is… the spreadsheet.
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Ben Zorn: How do we know where the diseases are in the world? Okay, so you have a Zika outbreak, right? The question is how do scientists know that that might happen? How would they predict? Can we do weather forecasting and that kind of forecasting, but for diseases instead of weather? The hard part is that technically, how do you solve that problem? He drilled that big important question down to this very simple question, can we use a mosquito as a sensor?
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 an era of AI breakthroughs and other exciting advances in computer science, Dr. Ben Zorn would like to remind us that behind every great technical revolution is… a programming language. As a Principal Researcher, and the Co-director of the RiSE or Research in Software Engineering group at Microsoft Research, Dr. Zorn has dedicated his life to making sure the software that now touches nearly everything in our lives is easy, accurate, reliable, and secure. Today, Dr. Zorn tells us some great stories about bugs and whales, warns us against the dumb side of smart objects, talks about his group’s attempt to scale the Everest of software security and makes a solid case that the most important programming language today… is the spreadsheet.
That, and much more on this episode of the Microsoft research podcast.
Host: So, let’s actually start by setting up the framework for what we’re going to talk about today. What exactly do the London Whale and a better mosquito trap have in common?
Ben Zorn: So, they seem very different, but in the end, I think if you think about the world that we’re in now, software plays a key role in our lives, in everything we do. And so, the thing that connects these is that they’re fundamental challenges, big problems, but at the core of solving those problems is the ability to use software to actually attack the problem and make it better. I work in the field of programming languages and we really think every day, we go to work thinking what do we do to make software better? If we make software better, then we can make all the things that depend on software better.
Host: Yeah so, what about the London Whale? What was that situation?
Ben Zorn: One of the things that’s important to understand is much of the finance world runs on spreadsheets, and spreadsheets capture a lot of interesting information, information from banks, information from stocks. The London Whale was one of these traders at JP Morgan and he had a spreadsheet and he was looking at how much volatility there was in a particular stock. And the reason they called him the London Whale is because he would make enormous purchases, like $1 billion dollars, literally.
Host: Hence, whale.
Ben Zorn: Yeah, yeah, the whale. So, he did this and unfortunately in the spreadsheet he used, there was a bug. And so, he thought the volatility of a particular stock was much lower than it really was. So, he bought it thinking it was going to stay stable, when in fact it swung and it went way down and he lost literally billions of dollars. And so, this was a human making a decision, but the decision was basically based on a spreadsheet. And again, we’re back to software. That’s the fundamental thing that links these together, is the bug in the software made him lose all this money and then all the consequences. I mean, the company lost $900 billion in a lawsuit essentially because of that.
Host: Right. So, what about mosquitoes?
Ben Zorn: Okay, yeah, so let me talk about that. I think one of the things I really, really enjoy about working for Microsoft is the ability for people to have a vision and attack that vision with their heart and soul. And, I had an incredible researcher working with me, his name is Ethan Jackson, and he wanted to solve an important problem, and it wasn’t a problem about money, or etc., it was really a much more fundamental problem, which is how do we know where the diseases are in the world? Okay? So, we have a Zika outbreak, right? The question is, how do scientists know that that might happen? How would they predict? So, in his mind, is, can we do weather forecasting and that kind of forecasting, but for diseases instead of weather? The hard part is that technically, how do you solve that problem? He drilled that big important question down to this very simple question is, can we use a mosquito as a sensor? So, can you take a mosquito and look at what it’s eaten in its meal- that blood contains viruses, and the viruses will tell you what diseases are present in the current environment. That took him on this incredible journey where he met with, you know, disease experts. He met with insect biologists, you know, mosquito experts. He worked with field biologists to understand what their process was. You know, how do they go now and find out where the mosquitoes are, what kinds of things are happening with mosquitoes? But the thing that he connected – you can think of this as connecting the dots – He connected mosquitoes to the cloud. So in particular, it’s not just that you catch a mosquito, it’s also that you have to figure out what its DNA in the blood that it ate was, and that requires you to do gene sequencing and it requires you to do it at scale. So, he built a trap. The project is called Premonition. The device that they created was a very, very specialized mosquito trap, and the idea is when you catch things in the trap, you catch these very pristine mosquitoes, and then your sequence their DNA and you send that to the cloud, and in the cloud, you decide what did this mosquito eat? Does it have Zika? Did the animal that it bit have Ebola? And with those answers you can then say well, in this region, we caught a mosquito that has Zika or we caught a mosquito that had Ebola. And in the process of sort of asking this question and finding answers, he had to explore all kinds of interesting problems. In fact, he revolutionized the ability of field biologists to collect data about mosquitoes. This new trap, it tells you things like when this mosquito was caught. So, now they can understand over the period of a day, when certain types of species of mosquitoes come out. He knows the temperature, he knows the sort of environmental conditions around the behavior of the mosquitoes, which they’d never measured. Another thing he did, basically the mosquito trap leverages machine learning. So the trap itself is about five pounds. It has 64 individual cells. Each one has a door, ok, and if a mosquito flies in, the trap can decide whether or not to close the door. So, it can say, if that’s a house fly, I’m not interested. Don’t close the door. But if the mosquito flies in, he can then figure out using machine learning, that insect was the type of mosquito he wanted and he can catch it.
Host: This is like so amazing. It’s too bad it’s a podcast because no one can see my face right now.
Ben Zorn: And let me just say, this is not just some person in a lab having cool ideas. One of the things about this project is it’s an incredible collaboration across Microsoft Research. So, he worked with people in the hardware group. He worked with people doing gene sequencing. Actually, there’s people in Microsoft Research that have expertise in doing it fast, which you absolutely need to do. So, this was a collaboration within the lab, but it was also externally, because we don’t have people that are insect specialists or biology specialists, so –
Host: What was his specialty?
Ben Zorn: So the amazing thing, his specialty is actually Programming Language Formal Methods.
Host: Oh my gosh. Awesome.
Ben Zorn: So, he had this vision, he built this thing, he executed on it. It was an end-to-end solution, and it showed that you can aspire to these kind of high-impact capabilities and we have this kind of environment here to really support that.
Host: I’m still thinking about how they can tell what a mosquito had for lunch, because I mean, it used to be you spilled mustard on your tie, you could tell what you had for lunch. Chet, you ate a hot dog…
Host: When people get excited about going into computer science today, they think maybe this will be my career, they’re often attracted by the kind of buzzy, hot things like machine learning, deep learning, AI, whatever. What role does programming languages play in that, and why would somebody think hey, I’m going to go into research, because your organization is called RiSE, Research In Software Engineering.
Ben Zorn: That’s a great question, and it is true that in the end, what we do is we build the things on which people build incredible solutions. So we work on software, we work on making it easier to build software, making it easier to make the software correct, make it perform well. But I think too, the way to think about it is, almost all the big technological revolutions have had with them accompanied a programming language. So if you go back to the late 70s, the advent of PC’s, one of the things that really sold the PC market was spreadsheets.
Ben Zorn: And it transformed the financial industry as we talked about. But those spreadsheets really re-defined how business people thought about their business, how they thought about the future, how they planned and did the trends. And so, I think at the core of programming languages, this ability to capture something that people want to do… So for example, C++ was fundamental in the growth of object-oriented programming.
Ben Zorn: It was a way to make it so that everyone that wanted to do object-oriented programming could go to C++. There were mechanisms in there. There were sort of frameworks that were built on top and they could start getting their job done. And the same thing with Java. If you want to do something on the web, you know, Java was the language. One of the reasons you know these are successful is because lots and lots of people start programming in them right away, because it opens up a new frontier for new developers, for new business opportunities.
Host: And even laypeople, I mean, WordPress things, you can go into the HTML and –
Host: That’s so interesting. Let’s talk about the spreadsheet again, because this is one of your things that I think is super interesting. And it kind of goes with a question I asked you about, in an era of AI infatuation, the spreadsheet is decidedly kind of un-sexy. Why is it important to programming languages?
Ben Zorn: First of all, in programming languages that have impact, and I have to say, there are hundreds of millions of spreadsheet users. So, by numbers, spreadsheets actually are the most important programming language in the world. And most people don’t think of it as a programming language, but in the essence of spreadsheets, you’re combining data and code, because you’re computing on that data, and presentation, because you want to see the result. You want to see the chart, you want to see the table, etc. So, spreadsheets are brilliant in that it’s very concrete. It’s not like there’s this abstract program and then you feed it some data. With a spreadsheet, you have the data right there and you have the computing right there. So that’s why it’s so accessible. But in the end, it is a program, and as such, you have bugs. You know, which is one of the reasons, say, the London Whale happened. But I think it’s important to understand that spreadsheets, because they’re so successful, are really a mechanism for people who have questions about data. And more and more people want to answer questions about data. I mean it’s like if I have personal data you know about my health, I’d like to be able to ask questions. I don’t want to have to go to somebody to write a program to answer my question. I’d like to ask that question myself. Well, put it in a spreadsheet. If you want to figure out, can I retire now, you put your data in a spreadsheet.
Host: This brings up like a host of questions, not the least of which is the Internet of Things, where you have all of these independently programmed – so let’s say Microsoft is doing software and they do tests and verify it and you know – I’m guessing that’s not the case in a lot of things that are out there.
Ben Zorn: So I’ll talk a little bit about sort of the Internet of Things. One of the things I’ve had incredible fortune, I’m a member of the CCC, which is the Computer Community Consortium, and this is part of the CRA, which is an organization that represents computer science research to the federal government. The CCC is the part of the CRA that actually is tasked with thinking about the future, thinking about trends in computer science. And the part of the CCC that I’ve been most active with is called the taskforce on intelligent infrastructure. And it looks at this question of, if we embed computing into infrastructure, or into say, the Internet of Things, how does that change the world, and how do we think about that world? And it goes to what I was talking about before about how every company now, to get an advantage, instead of saying okay, we’re going to make our toaster better, like mechanically, now it’s like, how can we use software to make our toaster better?
Host: A smart toaster.
Ben Zorn: A smart toaster. You think about, for example, your doorbell. There’s Ring. It’s a big company now, and they sell you a smart doorbell. It’ll show you video of who is at the door. You buy a Tesla, well Tesla is a ton of software, you’re really buying software. Right? Tesla sells you software upgrades, and they sell that to you. So they basically converted selling a car into selling software, right? The Internet of Things is amazing though, and it kind of goes crazy. So, for example, there’s a smart fork. If you look online, there’s a smart fork and it’s like wow, but the fork has a processor in it and it counts how many times you lift it. So, you basically-
Host: Oh, I need this fork.
Ben Zorn: So, here’s the thing. Smart objects, smart Internet of Things, they’re relatively cheap. No one is going to pay $1000 for a smart fork, right? And they’ve got to get to market fast. Usually they’re built on a software stack which is open source. But the biggest problem is, the level of scrutiny that people pay attention to with these things in terms of are they secure, what levels of care are made in creating that software?
Host: Well, moreover, who is the fork talking to?
Ben Zorn: Right.
Host: I mean, are they saying, hey, Ben’s password is… or…
Ben Zorn: So, here’s the problem. That fork, by definition, because it counts, probably talks to some server on the internet.
Host: And then I look at my wristband and say you’ve lifted that fork 100 times. I mean, somebody is talking, right?
Ben Zorn: Right. These things, by definition, are connected because they wouldn’t be smart if they were just by themselves, and you don’t necessarily know what software is running on them. And you don’t necessarily know if somebody has compromised that software. So, for example, yeah, I don’t really want to have to worry if my fork is trying to steal my internet and my wireless password.
Host: Or letting people know you’re not home.
Ben Zorn: That’s right, yeah. Is the fork talking to the doorbell? We didn’t used to have to think, is my fork trying to steal my password? But now we do. Because if you buy that smart fork, there’s a possibility- and we are in a transition with Internet of Things, where there’s sort of two classes right now of quality and software. There’s certified software, like aircraft software on a plane.
Host: It better work.
Ben Zorn: It is carefully checked. You’re pretty confident there. But then, everything else, there’s no checking. There’s no level of certification. One of the things that I’m doing with the CCC is understanding at the federal level, what are the right things for the federal government to be doing in this space. And in fact they are actively working… one of the models they’re looking at is using an underwriter’s lab kind of model, so that instead of saying underwriter’s lab says this electro-compliance won’t short circuit and cause a fire, they’re basically saying this device has reached some level of quality. Which is better than just nothing.
Host: Does that include security though?
Ben Zorn: Yeah, well it goes to questions of best practices. And they’re fundamental questions like how do you update? Let’s say you have a device and then it’s got a bug. We know about Window’s update. We know that we see PC updates frequently. But how many people update their fork?
Host: I have never updated my fork.
Ben Zorn: So the question is like that’s a problem, because if there is a security vulnerability and you don’t update it, then your fork is vulnerable forever.
Host: Can you get a fork patch?
Ben Zorn: Exactly. And in fact, this is not just a hypothetical. One of the things that happened about a year ago was, people had bought video cameras on the web and it turned out that a hacker figured out that many of the passwords on these video cameras could be guessed. So it turns out they actually hacked about 100,000 or more of these cameras. First of all, if you have a web camera and somebody has hacked into it, how would you even know? So that’s the first problem.
Host: There’s so much I don’t know.
Ben Zorn: But the second problem is, the person who hacked this leveraged all of these, 100,000 or more machines to do a Distributed Denial of Service attack. What that means is they had these cameras all send packets to a particular website to make it so that no one else could access it. And with 100,000 things, you can really shut things down. And this was a problem last year. One of the things that happens with Internet of Things, with this emerging presence of lots of devices without security, or with less understanding of how the security works, is that you can have these emerging attacks based on large numbers of devices.
Host: The scenarios you’ve painted are common in that people click agree on an app for convenience, right? They don’t even know what they’re-
Ben Zorn: Right, yes. There’s two kinds of problems. One is a problem where there’s a bug in the software and somebody exploits that bug. It’s doing things that was never intended. There’s another problem which is the software itself, say an app on a phone, has privileges it doesn’t really need. When it says, here’s 10 things I’m going to do if you want to use me, how do you know what things it really needs?
Host: Not only that it’s a binary option, I either say yes or no. Could I do five of those?
Ben Zorn: Right, so I think the good news here is there is an evolving understanding of how to enable – for example, one of the strategies is you say look I’m not going to say you can do it. When you need it, you ask me. Like when I’m about to use something and it says I need to use your camera right now, then you say yes because you’re taking a picture, you understand.
Host: Which I’ve done. Can I access your photos? Okay, because I want to edit that photo.
Ben Zorn: Exactly. So, I think there is hope there in the sense that the understanding of how people interact with software, how you can make software more understandable is evolving. One of the things you can say is that it’s a success story in a sense that people are using these things for so many different activities, so many apps on the phone, so many apps on the computer. The fact that people want to use software for all these purposes, and that we have to understand what that means and how to control that more.
Host: So, if I get a smart fork and I decide I want to upgrade it and they say we don’t support that anymore, are we just…?
Ben Zorn: Well no, this is a real concern. I would basically say, and in fact, the FBI provided a public service announcement saying if you have Internet of Things devices, then you should put it on a separate network. So, this is one of the things they’re telling people, it’s like in your home now, have your network, which is your computers and all your stuff that you’re using that you really need, and then everything else put on a separate network.
Host: But who can do that? I mean, I don’t even…
Ben Zorn: I understand and it is a concern.
Host: You people are technopolists, in a good way I’m hoping.
Ben Zorn: This is an analogy of the Wild West. Right now, we’re just seeing what all the problems that can emerge. Over time I think, for example, wireless routers might actually have these two networks sort of automatically configured in such a way. In fact, even now, I think routers will give you guest networks, but you have to know how to use them and you have to understand the configurations.
Host: You need to be Wyatt Earp in this Wild West.
Ben Zorn: So let me talk a little bit about a strategy that we can go toward that. There’s a project in the group, it’s called Everest…
Host: Which group?
Ben Zorn: In my group, RiSE. What they’re trying to do is think about, not just writing software, but writing software so that it’s fully verified. So what does that mean? Actually, fully is too strong a word, but verified for important properties. So, what does that mean? In particular, what they’ve taken on is there’s a communication infrastructure that connects a web browser and a server, it’s called “https.” You might have seen it.
Host: Yes, I think it’s secure when I go there.
Ben Zorn: Right. You get a little lock that says the communication between your client and the server is encrypted, secure. You can send your bank account numbers or credit card numbers and no one who is listening in can understand that. So that https is actually a lot of software. There’s an implementation of it in the open source called Open SSL and it’s used widely. In fact, a couple of years ago there was a major problem with Open SSL called Heartbleed, which made the news because you know it turned out that people could look in on your computers through this Heartbleed bug. And this was a problem with SSL.
Host: Was it a bug or a hack?
Ben Zorn: It was a bug in the software that then people figured out how to exploit. Exactly. And it was unclear how widely exploited it was because it’s very hard to tell if people have been using it. Anyway, so, Open SSL is an implementation and what the Everest team said was we’re going to build an equivalent version of Open SSL but we’re going to make our version verified for the important properties, like the cryptographic properties. Now, this is using program verification on a scale that’s never been attempted before, because these communication protocols have many layers, they include many different encryption algorithms, and the properties you need to prove include things like you can’t have a memory safety violation, which is the kind of thing that Heartbleed exploited. That’s a very basic property. But the higher-level properties are, if two people are talking on each end of the line, we’re going to guarantee with this proof that there’s no way that an attacker can listen in. It doesn’t matter how the attacker tries, they’re not going be able to hack the software to decrypt these messages. That’s a very challenging problem because it’s a combination of proofs, essentially looking at each line of code and saying what are the possible ways this could go wrong, but at a scale of thousands and thousands of lines of code. And the ability to prove things about thousands of lines of code is actually very difficult. If you think about these proofs, we’re talking about literally hundreds of thousands of formulas all connected together to form the proof, and then saying yes, we can prove that that set of formulas actually is satisfiable. There is a way that this could be true, and no human would be capable of doing this.
Host: No way. So, that Everest is one of the projects that’s come out of RiSE?
Ben Zorn: That’s right, yes. RiSE is a group – I co-manage it with Tom Ball. Research in Software Engineering is a group of researchers and developers. We collaborate on a number of different kinds of projects across a spectrum. So we work on software engineering problems, like how do we build software more effectively? How do we deploy software more effectively? How do we help developers understand where the problems in the code are, or what problems they should may be do a code review for? So that’s one end of the spectrum. The other end of the spectrum is, we think about the formal foundations of software, so we’re trying to ask questions like what does the software mean exactly? How do we translate essentially a program into math, and then use what we know about math to prove what that program is going to do or not do? And unless you get that kind of level of understanding, we’re going to be in a world where we do have these bugs. We do run into problems where somebody deploys software, and things like Open SSL, which is widely deployed, and it’s a problem with devices, because once it gets deployed on, say, routers, all of a sudden, it’s very hard to update. It’s very hard to fix the bug. What you would really like to do instead is verify the software before you deploy it, and that verification requires a deep understanding of what the software is, how to reason about it, how to prove things about it, and the tools. One of the key things about Everest is it builds on top of a tool called Z3, which is a very, very powerful tool used not just by people in my group, but by people all over the world. Thousands of citations to the work, where if you have a problem that you can specify as a sequence of constraints like X is greater than 3, Y is greater than 2, X plus Y is less than 53, it will actually take that and solve it. It will say here is a value for X and Y that will make this thing true, or if it’s not possible to make it true, it will say it’s not satisfiable. So Z3 is a mechanism on which people build that helps people think about complexity of logic at a scale that is unprecedented.
Host: Yeah. You’re here doing this… my mind is going into all the other things that I have. And I know how expensive it is to test software. This isn’t even a question I had on my list but you just prompted me to think, with all these developers out there doing smart objects with their own code, and probably just shipping. Are you guys doing anything to make it less expensive or more easy?
Ben Zorn: Right. I think what you see in the world of software is people want to reuse code. They don’t want to write their code from scratch, right? A great example is cryptography algorithms. When you think about cryptography algorithms, it’s very hard to write that code. It’s actually, performance is critical because encryption and decryption, you know, is something that you don’t really want to do but you have to, so it’s got to be fast. But the problem is that if everyone had to write their own cryptography algorithm, most of them would probably be wrong. Because it’s very, very difficult, you have to be super smart to get it right. So, what you’d rather do is actually do it once, and then verify it, and then use the verified thing. And everybody could use that verified thing. I mean, one of the nice things about open source is once it’s available, there’s no barrier. So, what we’re trying to do with Everest, actually Everest is an open source project, we’re trying to build bigger and bigger components that people can use and reuse instead of trying to have to do it themselves.
Host: What are the unique challenges for software engineers now that maybe they didn’t face 30 or 40 years ago?
Ben Zorn: Oh, wow. Great question. If you think about a software developer say in 1990 or 1995 where you know, they’re thinking about building a desktop app, like it’s on the desktop, it doesn’t talk to anything. You know, it’s the UI, it’s maybe in the logic, etc. But you think about the developer’s life now and how totally different it is. And one of the key things is, you’re building a service. You’re not building something that sits on somebody’s desktop. If it crashes, that one version goes down, but everyone else’s is fine, right? When you build a service, it’s running 24/7, it’s got to always work, and if it crashes, everyone, all your customers all of a sudden don’t have something. So, the developer’s life is much, much more complicated now. But it’s also, I mean, the beauty of the service model is the kinds of things that you can do with a service, it empowers, you know, software dramatically. So, it’s harder for the developer. You’ve got all these new things to think about. You know, there’s the deployment process, how do I make sure that as I deploy it to more and more people that it’s still has the right quality, etc.? But I think at the core of the job is still, is the software right, does it perform well, and is my customer happy?
Host: I would imagine that’s one of your major goals in Microsoft Research RiSE?
Ben Zorn: Absolutely. The whole investment we have – I mentioned we talked about software engineering, so that’s the process of building software. We talked about formal methods, that’s really figuring out what the software should be doing and making sure it’s doing that. And I think another part is actually helping developers. One of the really successful collaborations we’ve had in MSR, in my group, is that we have a really talented individual, Mark Marron who worked on something called Time Travel Debugging, okay?
Host: Okay. Let’s go there.
Host: That’s really inspiring to know, because it feels like a common theme I’m hearing, is that people are talking to other people, seeing how can they bring it expertise from other areas within different groups, even in the research group.
Ben Zorn: Right. No. Absolutely. One of the things I think that’s really exciting, especially with the success of AI is it opens up new collaborations. Interactions with groups that we didn’t use to interact as much with, partly because these questions that I mentioned, but partly because, you know, it’s always exciting. And you know, every time you have this kind of shift in the way people think about the complexity, new problems they can solve, new ways to solve it. One of the things that’s really exciting about the AI technology is it does change what it takes to build these models. If you say well, I need a developer to write the code, that’s one thing. But if you say I need labeled examples, you know, to train, that’s a totally different set of skills and it changes who can do it and how you do it. And so, every time these changes happen it’s a new cycle and we get to do all these fun things again.
Host: Right, right, right. That’s so interesting. Well listen, let me wrap up with asking, because I’m really interested about who comes here.
Ben Zorn: Sure.
Host: What do you look for in somebody that you would like to come here and work with you in RiSE?
Ben Zorn: Well I think there’s a couple things. I think we look for people who are broad thinkers, that they really, like I said, they go to the heart of the problem. One of the things we offer at Microsoft, which is really different than an academic experience is we have incredible depth in the product teams. So you know, the product teams are dealing with real problems every day and sort of thinking in terms of you know, that’s an opportunity. For the people that come here, the researchers that come here, that’s something they just can’t get in an academic world. You know, you want people that embrace that, that basically look as broadly as possible as sort of how they can impact, you know, the world, the company. In the end, like I said, we look for people to build stuff. People who want to think about solving problems, sharing solutions, having people use those solutions and get their hands on those things. And so, the sort of the expansiveness, the willingness to work and learn across disciplines. I mean, one of the things that we have that’s a huge resource, Microsoft research has incredible depth, you know, compared to almost any academic department in the world. If you’re here, and you don’t step across the hallway and start talking to people doing things very different than you, that’s just a missed opportunity.
Ben Zorn: So, I think those are the kinds of things that you know resonate when I look to hire people. Obviously, we have a lot of visibility in the academic community for the things we have done. People come to us with an understanding and the kind of expertise and the kind of strategy that we use to solve important problems. You know, something like Project Everest is a great example where security is incredibly important. You know, it has enormous visibility. It’s an expedition, which is basically a multi-lab effort. So, it’s not just people in RiSE, it’s people in Cambridge.
Host: You have Sherpas?
Ben Zorn: Yeah, right. So it’s a team effort. But I think one of the things about that is it reflects an understanding. This is such an important problem you know. And it’s not just an important problem for Microsoft, it’s an important problem for the world. And in fact, you know understanding, you know, how to do this process and understanding what tools are needed and what can and can’t be done is really going to be very important for the whole software ecosystem in the next 10 years. The fun thing is that every day is a new day. We get to have really exciting collaborations. It’s a dream job. I mean, it’s one of those things where working with the talented people that I work with every day is the best possible thing you could imagine.
Host: Ben Zorn, you’re a Rockstar.
To learn more about Dr. Ben Zorn and the wide, wild world of programming languages, visit Microsoft.com/research.
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