Episode 83: Alan Cohen of DCVC on Investing in Deep Tech For Humanity

Informing your decisions with intelligence analysis and insight brought to you by the team@ooda loop.com.

Hello, I'm Bob Gourley, the Chief Technology Officer of OODA llc. Today on the oodacast, Alan Cohen. Alan is a partner at one of my favorite venture capital firms, bcvc. They're one of my favorite firms for several reasons. One is they invest in companies that do good things for enterprises and help enterprises become more efficient and focused on their missions. But if you look broadly at their portfolio, they're also investing in things that are just great for humanity. For example, I've seen them invest in startups that are doing fantastic things when it comes to pharmaceuticals and discovery of new drugs and ways to manufacture very helpful drugs. They have also invested in other medical companies focused on real patient outcomes. They've invested in cybersecurity firms that are really disrupting the cybersecurity equation. Physical security too. They have invested in and led to market great companies that are changing the risk equation when it comes to physical security. They've also invested in some of the most interesting space and aerospace firms out there. So I like DCVC a lot. As for Alan, I've known him for about two decades. He has led some of the largest enterprise firms out there and has helped small firms grow to be very large over his career. For example, he was a VP at Cisco during their high growth era. He's also been an advisor to companies like Box and MobileIron. He's led marketing at Nicera. He helped lead marketing and growth at Illumio. He's been an advisor and a set on boards for Cohesity, netscope, Illumio, Element AI and many others. At dcvc, he tracks innovation across multiple sectors of the economy and sits on the boards of many of their portfolio companies. For example, one I want to talk about is Evolve and this fits in this category I just mentioned of a company that's changing the risk equation in physical security. Greetings Alan. Welcome to the oodacast.

Glad to be here. Longtime fan, finally made it onto the show.

Well Alan, you know I've known you for quite a while and learned a lot more about you recently looking over your LinkedIn profile frankly. But as I knew you as someone who helped these great tech firms accelerate in the market, helped people understand what they do and then why we would want to engage with these tech firms. But looking over your bio I see frankly it all started in a very interesting place. You were an English major in your undergrad and I wanted to ask you about that. Why did you pursue an English degree for your undergrad degree because it's just fascinating to me.

Well, I would, I would love to tell you, Bob, there was any strategy, but as we talk, you'll find that there's no thread between my career and any strategy. I grew up in New York in Brooklyn and three kids in a two bedroom apartment. And for me, reading and literature and then ultimately school was kind of my way out. We had fairly modest upbringing, but fiction in particular was a way to really expand my horizon. And I just always thought I was going to be a novelist and so might as well study English. That's, you know, for, for me, I've just always have a great appeal for great narratives. It's probably the best way to phrase it. And you know, whatever I've done in my career, it's been around great narratives and you know, I mean, you get to borrow money from the government to study great narratives in college and graduate school. So that's, that's what got me started in that way.

You know, it's interesting because as I look at your career now, it in itself is a great narrative because you start with this English degree. You also got a master's in English from University of Vermont. And then it was very much a career in the technology disciplines, helping companies grow and create and succeed. And throughout that, I just have to imagine that English has helped you succeed in this space.

Well, it definitely has. So if you think about the tech space, now that I've been in pretty heavily for the last 30 plus years, you're surrounded by a lot of really smart people called engineers. And engineers kind of reinvent laws of science, build amazing things, can't always actually explain to people why they would care about it. And so for me, I was able to carve out a little bit of a niche helping these really brilliant people explain to the market, explain to customers, explain to investors why you should actually care about it and what benefit you would get from participating in some fashion, whether as an investor or employee or a customer. And so I think that love of narratives is just, has always kind of played that role and in tech, in, I suppose, let's say if I worked in the advertising world, I would be kind of a general commodity. There were a lot of people great at narratives and brand and things like that. But in the technical and engineering world, I was more of a scarcity. So I was a scarcer commodity. And even somebody with middling talent like me could actually make a pretty decent living among people who were not inclined to know how to do that.

See, I want to talk about so many of these tech firms that you've been with and are with now and helping to lead. But this has to me a big message. And it's like for the youth today, so many of us are saying that we need more STEM trained people. And I believe that's true. There's some real shortages there. We need to keep investing in science and technology and engineering. It's critically important. But that's not all we need. We need the people who can conceptualize and visualize and we need poets and artists and actors and English majors, people who can communicate. And I think it's so critically important. So I guess the issue now is how do you find balance?

Well, I think in anything, if you are an athlete and you're right handed, you know, some of your training is tie your right hand behind your back and use your left hand so you actually become much more ambidextrous. So my entry into tech really was as a product manager. And while I couldn't go toe to toe and do the packet walkthrough through an ASIC and you know, as the engineers I work with, I did understand how customers would take advantage of our products and how they would want to interact with it. So I think for a lot of people that who would like to pursue liberal arts and then go into tech, you have to have an appreciation for the technology itself. I always say don't hire a marketing leader who can't do a demo with your product because at the end of the day they are a human being. Well, a little bit later we can talk about now the machines interact with each other. I suppose you have to market one AI to another AI that's coming. Everybody's quite done that yet. But you're effectively trying to get human beings to interact and take advantage of technology. And if their experience of it and their understanding of the efficacy isn't there, they're not very good adopters. I mean, they could be forced to use it. I worked for IBM for part of my career and for a long period of time you could buy computers from IBM or you can buy from IBM. That defined a period of time between 1960 and 1980. But for most part, the tech industry changes very quickly and is hyper competitive. So you are always competing for your next sale, your next couple of minutes of interaction with an end user. So my entry into tech was through that. I have a really good friend, Matt Glenn, and he's the chief product officer of Allumio. He's much more technical than I am. But he started in documentation and think about that, somebody opening up a doc memory. We used to have docs before we had wikis and all these other things. And how does this server, how does this router, how does this network work? And if you can't explain to them there and they can't figure it out, then I'll tell you a lot about the adoption of the product later. So getting to the coal face between people and technology was kind of the intersection for me. Cool.

Let's talk a little bit more about your career. And currently you're at DC vc, but prior to that you worked at a lot of great tech firms. You mentioned IBM, Cisco, Cisco twice, I guess, right?

Yeah, I worked at Cisco twice. I was recruited there, left, helped build a company to compete with them, got acquired, left again, joined Martin Casado and Steve Mulaney and the team at Niceera competed with Cisco again. However that time got eaten by VMware and then joined Allumio, a cybersecurity startup that competed with all my prior employer and competed successfully with all my prior employers and then made my way into venture later. So I've been on every side of the networking battle humanly possible between the mid-90s and the mid point in this decade.

Yeah. And a lot of these firms I know very well and many of them that you just mentioned remind me of the old Asmonov quote that any sufficiently advanced technology is indistinguishable from magic. A lot of These firms like VMware at the time, a lot of us knew about virtual kind of technologies, but to productize it the way they did it was just magic. And then Niceera, a lot of us knew that you assumed you could do better in networking, but to create this virtual networking capability, it was like magic. It's what the enterprises needed. So in many of the companies you would buy is also.

Yeah, no, yeah, no, just. I mean it is. And I think you know, a lot of this I really kind of attribute back to my time at Airspace, which was the first hyper successful wireless LAN startup. So those of us who remember when you used to stick a card into a laptop to try to connect to a wireless network in the early 2000s when wireless LANs were getting started, people didn't trust them, they didn't think they were secure. But the networking industry was defined by people who use wires and plug things in and the ipconfig clear and cli. And along comes the democratization of wireless through WI fi and through cellular, particularly in the enterprise, through WI Fi intel puts the Centrino chip on every laptop as part of the upgrade cycle. And all of those WI FI enabled computers needed something to connect to. So we were among a wave of leaders that were there not to actually create demand, but to satisfy demand, which is a very important principle in any technology. It is always dramatically easier and more valuable satisfy demand than it is to create demand for something. And we get into this market and we recognize none of our customers actually know how any of this stuff works. You say, oh minus 85 dBM, you know, signal to noise ratio is that good or bad thing? And they're like, I don't know what that means. So we created, and I was product manager created the first heat maps. Green, yellow, red. That tells you how it is, what, what, what access points are the top talkers, how do things move around. So we had to visualize a. Something conceptual which, like the rf, you can't see it. It's right. And, and you know, that's how we were able to be successful. And that for me, really even more than working at IBM and building E Commerce and joining Cisco during the, you know, that first big wave of the Internet in the 90s really taught me firsthand how you have to kind of marry people's imagination and their ability to actually use things. And I've always loved mobility and wireless because of that.

Another that's very interesting is Allumio, I find. And what they do is they provide security in a way that lets you monitor things in the smallest possible way. Micro segmentation and so helps enterprises take full advantage of the cloud finally in a way where you can know what the configuration is and control it and restart as necessary. Did I say that about right?

Yeah, no, that's pretty good actually. If you, this OODA loop, you know, doesn't. OODA broadcast, doesn't work out. I'm sure we could probably get your job over there. But you know, what Allumio figured out is before kind of the term zero trust became as common as it is today in cybersecurity is that pretty much everything was going to be untrusted. In fact, Google has a great architecture they call BeyondCore, which is just assuming every network is the Internet and you have. And if you're out there on the open Internet, which is the freeway of networking, how do you deal with it? From a. Privacy, security, intellectual property protection. So Allumio created a model that said only things that were allowed to talk to each other were able to connect and then able to do that at great scale. So Some of the largest Allumio customers literally have hundreds of thousands of devices that are protected by Allumio. And then you have the N way problem of how many thousands and tens of thousands of policies would it take to do that? And they abstracted it. So what Alluvio actually did was use big data and forms of machine learning to solve that problem. So you could take a company like a Salesforce or one of their other large customers and micro segmentate, segment a dynamic and giant computing environment. So they were, you know, to me, and once again, how do I understand how it's doing that? So how do I visualize it? They have a capability called illumination. So how do I see that it's working? And so I think there was this great president in the 80s that said the trust would verify. Right? And I think that's what Allumio does.

And this kind of gets us to. I want to talk about other firms in the D.C. vC portfolio, but would you first tell us a bit about DC VC and what makes you guys unique? I mean, I have my view, which is I like you guys because I see you investing in companies that are doing hard things where we need solutions and that can be for the enterprise. But also I see you investing in health care, pharmaceuticals, agriculture, space, aerospace, anything where there's a hard, hard problem. It seems like you guys are trying to find some solution. And I also see that you use the term deep tech and I wanted to ask your view about that too. So what is DC VC and what.

Do you mean by deep tech? My founders, my partners, Zach Bogan, Matt Ako started DC VC about a decade ago with really a large movement into what was then the big data movement. Literally. I think Zach helped create the big data drinking club in San Francisco. These were all people who were data scientists that were really trying to use massive data sets to write software to solve really complex computing problems. And so born out of that moment, in the last five or six years, they've really focused on a series of changes in our economy. Whether it's industrial transformation, whether it is supply chain resiliency, whether it is more equitable distribution of goods and services. And we could talk about that in terms of healthcare or, or it's reduction of carbonization in the environment. Deep tech is when you take all this power of AI and machine learning and data science and you marry it with hard science, molecular science, chemical science, biological science, physical science. We're large investors in space and that's where deep tech comes from. And I believe Matt is the kind of OG progenitor of that term, I think about 20 years. He came up with it because the technology is not simply just applying a simple software layer and manipulating some bits and moving them around to a visual spreadsheet. It's literally changing the processes and sometimes the molecular structure of physical goods and services. And to do that in a much more effective and efficient way. So we do that. So deep tech is how we do things. But we do this in pursuit of really kind of three things. One, making our society more resilient, whether it's in defense, health care, agriculture, making them much more effective from a climate footprint. So not spewing all kinds of stuff into the water and the air that we have to this very thin little atmosphere. Talks about it. And I think, you know, one of my partners went to space last Monday on Blue Origin with William Shatner. And then finally making these goods and services much more equitable so more people can take advantage of that. And we've seen a lot of that in our healthcare AI portfolio, whether it's things like caption health and we'll talk about the portfolio companies or new investment we've made in company called Proprio, which was really unraveling the black box of surgery. So most technology investment and most technology spending goes on a fairly small piece of the economy. The tech economy worldwide is about $4 trillion. I came up in that economy and so did my partners. And DC vc, the Data Collective, which is what the DC stands for, started in that space. But it's the other $85 trillion of the economy that has not had fundamental change sometimes in decades, sometimes in hundred years. That's where, you know, DCVC is particularly focused on.

Cool.

Does that make sense?

Yeah, it makes a lot of sense. I want to talk about all that, but you just let that fly by. You said, and one of my partners went into space with William Shatner on Blue Origin. Wait a minute.

What?

You know somebody who's been in space?

I do. He's one of 600 people now who have looked at the earth from the darkness of space down. So Chris Boshausen, who was a NASA employee and then co founder of Planet Labs, which is the leading small satellite LEO satellite data as a service company, he's been one of our partners for five years. He was selected for the second. The Bezos brothers got to go on the first Blue Origin. So he went up with three other people, one of them being Captain Kirk, William Shatner last Monday for a quick 15, 20 minute ride into outer space and drifted. Chris is a Great example of the kind of. I mean, he wanted. I mean, I point you, there's all kinds of social media. He grew up in a town of 1800 people in Australia. He wanted to be an astronaut, but he's colorblind, so he didn't qualify it. So he came into the United States, worked for NASA and that's determination. He wanted to be in space, he got into space.

That's awesome. And that launch makes another point that we were discussing a little bit earlier where I was talking about your English degree and how it has helped you so much and how we need more than just scientists working science at the after landing. Listening to William Shatner talk about his journey in a way that, frankly, I think his years of art helped him express the meaning of this and what he saw looking down and looking up. And it just underscored for me that we need people like that to express the impact of these kind of technologies.

So. Yeah, well, a little beyond my capabilities. His speech about the death and blackness of space and then looking at the precious thin atmosphere and the absolute beauty of the world from looking down. But I think we have an inherent mission at DCVC and we share this with a lot of people. We're not exactly unique here, realizing that, you know, life is a precious amount of time and we live on a precious resource in, you know, the Earth and we live in a precious society, the United States, which is the last great hope for mankind, I think is what Abraham Lincoln called it about 150 years ago. And when you take those responsibilities seriously and you map it to the right incentives, right, because ultimately we take money from people and we put it to work and they expect to be rewarded for that. And we've done a pretty good job this year on that in particular. But in general we do that creates a very interesting mix, a vortex of possibility. So I like. Matt has this phrase I've stolen. I'm sure I gave it to him. We do impossible on the cheap.

Another one of the phrases I've heard him use is we're going to cancel the apocalypse. Now somebody needs to cancel the apocalypse. And I'm glad you guys are there for us, frankly.

Well, and you know, and it's interesting and let me use an object lesson I love. And this is one of the reasons I joined dcpc. There were two companies that I got involved with, one as an investor and one as a board member, which was why I joined Venture. After a career of taking half a billion dollars of venture money for my startups, like I knew how to ask for it, but actually giving it the other way is a whole different discipline. There's two companies that I think everybody in the world needs to know about. One is a company called Pivot Bio. Pivot Bio is a company that has created a series of organic microbes that pull nitrogen from the soil to provide fertilizer for staple crops. Corn, wheat, sorghum, for example. You don't have to use any chemical fertilizer. I think folks know that agriculture between meat production and then crops are very significant contributor to greenhouse gases, including nitrous oxide, carbon, obviously carbon dioxide and methane, certainly in the case of cattle production. Pivot Bio is the brainchild of a fellow named Carson10, who's the grandson of a Texas corn farmer, went to Berkeley and started working on this problem. I think we kind of met him as he was coming through the dorms. He has built a technology that is used by farmers to augment and ultimately replace their chemical fertilizer. It's highly cost effective. It doesn't burn out the soil. It doesn't run off nitrogen into either the atmosphere or into the water system. And more importantly, the outcomes of the growers are anywhere from 10 to 15% more output per acre. So the farmer makes more money and is a better steward of the land. And if you've met farmers, they are great stewards of the land. They are not short term thinkers in any kind of way. And so when Matt uses the term cancel or I'd say at least move back the clock on the apocalypse. There are other things that could cause the apocalypse. That is one that does it in a really big way. The other one for me that's very important is coming. I'm the chairman of which is Evolve, which is a physical security that uses machine learning and sensors to understand when somebody walks through it, whether they have a baby Glock or an iPhone in their pocket and can scan several thousand people an hour, up to 3,500 people an hour can walk through it without emptying their pockets.

Where would this kind of technology be used?

Well, tell me where you live and I'll tell you where to use it. So you could use it in the Smithsonian. You could use it. About 12% of Major League Baseball, NFL and Major League Soccer have purchased our system in the last nine months. So it could be the Chicago White Sox or the Chicago Cubs. It could be the Tennessee Titans, it could be the Columbus Crew in soccer, it could be the San Francisco Giants, it could be Citi Field, it could be the Boston. I'm sorry, the New England Patriots. It could be the Museum of Modern Art in New York. It could be the Natural History Museum. It could be Lincoln Center. It could be the.

So it is like, say, my. My neighborhood, elementary school, middle school, high school, places like that.

So it's the. You know, we're. We're just getting started in schools. Spartanburg Middle and High School is a customer of ours, as is the Mecklenburg Schools in Northern Virginia. So. Yeah. And what it does is it actually knows whether somebody has a weapon or not or something that's close enough to a weapon that would. And it will understand one is it on that person, and it'll understand even what part of your body or your bag that it's in. So it's an amazing technology. And by the way, it doesn't have any bias because it doesn't look at people. It looks for weapons. It's a fantastic technology. So the ability to reduce the threat of weapons violence in our society is another way of canceling or sending back the apocalypse as well. And for me, if we can keep people safer and we could actually make farmers more profitable and not tax our natural resources to do it. Kind of the stuff that gets you out of bed in the morning.

Yeah. And so a couple others I've been tracking that you guys have been investing in for years include, like, Planet. Planet Labs, which, to me, that was. I'm sure I get this wrong. I should just ask you how to describe it. But I always thought of them as taking the most advanced technologies possible. You know, it's after the iPhone revolution. Take those kind of sensors, put them on small satellites, get them up into space, and then collect data every single day and analyze that data and then be able to tell people the impact of what they're doing or give them information for improving fisheries or improving agriculture, or helping business. Analytics. Did I get that about right with Planet?

No. Yeah. I mean, a simple way to think about it is Planet takes highly accurate and detailed photographs and collects data, basically snapshots the Earth several times a day. It can see anywhere on Earth. And to your point, the Planet team was helping basically, firefighters during some of the fires in Northern California out west, because it sees everything on one hand. On the other hand, it actually couldn't tell you when the North Koreans have a missile on the launch pad. Right. So it's a really, really interesting company, and it's really fulfilled the data analytics side of the opportunity for space. But we don't stop there. We actually have multiple companies. We just have a company rocket lab that went public, which is the small satellite. We'll get you up there with Rocket Lab. And we have another company, Capella Space, that uses sar, which is imagine Acoustic radio versus because Planet is an amazing company, but if it's cloudy, you can't see it. The acoustic radio technology actually will see through the clouds. I'm sorry, I was just going to.

Say I saw some examples of their product. Meanwhile, as a former intelligence officer decades ago, I was seeing examples of the very best stuff that the government could provide. Man, the old government stuff is horrible compared to what we're seeing out of Capella and others. Just, it's incredible the amount of advancements that have been made.

Well, they have some pretty decent technology and the government doesn't all make it to the COVID of, you know, the CNN news site every day. So I'm fairly confident in our government's capabilities. But it, you know, whether it's Planet through the data and then obviously companies like Rocket Lab through the launch, it's really the beginning of the democratization of space and it is the kind of new frontier for my partner Chris. Obviously he's one of only 600 people ever to look at the earth from space. But that's going to change irrespective of how you feel about it. Not everybody loves all of this activity in space. It's going to happen just as sure as people are going to move around the country or change careers because it is a frontier that people want to tackle. But it can play a very strong role in dealing with climate change, understanding how our planet is, the weather patterns have changed it and obviously our physical security or our business activity. We're seeing a huge change in the world. That same technology, machine learning, optics, can be also used for understanding people's health. We have a company Caption Health that I'm on the board of is the first company approved by the FDA to do an ultrasound of the heart to provide an echo. A high quality thing about this said simply a high quality picture of your heart and your aorta and all your valves to know if things are okay in there. The AI allows somebody who's not a sonographer or a doctor, it could be a med tech, or we're working with the Marine Corps and the Navy and something that's called the charm study, to allow a corpsman or corps woman to actually do an accurate scan of your heart, which could be done out in the field, could be done in a tent, hospital, or it could be done on an aircraft carrier. By doing that, more people's hearts can be scanned or their lungs. And, and we have 40 million people who have had Covid. So you want to take an eye on it. Not everybody can drive to or afford that care. In this case, the technology going from outer space to inner space, the inner space of your body. This similar sets of technologies and capabilities can make tens, if not hundreds of millions of people have access to better care at a much more reduced price. And they're all on that same continuum. Right. From the concept of video and analytics and machine learning in space down to your aorta. And that's. To me, that's obviously extremely exciting. Yeah.

I have a very close family member who needed to get some heart imaging done. She had plenty of insurance coverage. That wasn't an issue. Greatest hospitals in the world are here in the northern Virginia area. That's not an issue. But it took forever to get scheduled and then the results were pretty quick. On the grand scheme of things.

Sure.

Where near as instantaneous as you're describing. And still it was, you know, you have to wait and go into some industrial age kind of system to get your heart imaged. Whereas once these kind of sensors are deployed and widely used, this is going to potentially help millions get fast imaging their heart.

Well, fast imaging and regular imaging. So I mean, if you think about it, you go in for a checkup Once a year, Dr. Puts on a stethoscope, maybe takes a blood sample, you know, taps around a little. It's pretty interesting point in time, but it doesn't really tell you very much. So I think, you know, one of the things a lot of this technology is going to be able to support is more regular inspection of our health on a regular basis. And you know, I'm wearing an Apple watch today, right. It's got an, you know, it's got a pulse oximeter and it's got a little EKG device and it's got a pulse. Like increasingly you'll be able to have continuous data points. And if you really want, I mean, if you think about it, when you, when you, when somebody's really sick, they bring you into a hospital for continuous observation because you want it. Because. Because a point in time isn't always the right thing. Now if you have a heart attack, they know they have to deal with it or something, or something bad happens. These technologies can also be used more in preventative and lead up to understanding before something like. Well, the problem is you don't want somebody to have a heart attack. You want to understand when their arteries are hardening or when their heart is not. The ejection fraction isn't correct. So to me, okay, so we've put all our effort into cyber looking for signatures and bad actors. Well, why can't you do the same thing with people's bodies? And so it's, you know, it's time for us, I think, to put a lot of this technology to work in much more productive outcomes for human beings, as opposed to how to figure out how to get, you know, cells on a spreadsheet, cut and paste from one application to another.

Right. Alan, I want to ask about another one. That's okay. Primer. I met Primer through you guys, and I like Primer for a couple reasons. One is their CEO and founder is also named Gorley. Now, no real relation, but I'm sure I'm proud there's a Goerli there somewhere. And Primer to me is pretty cool because it can take massive numbers of documents and not just summarize them, but extract meaning from that body of work in ways that are very helpful to analysts. And, you know, analysts in my community, the intel community, need this kind of thing because there's not enough analysts to track every issue in the world. And there's far more data than we ever imagined. So you have to have tools like Primer to make sense of what you've already got. And I know there's also a need for this in other industries as well. Journalism, insurance. Any place where there's a lot of data that needs to be understood by use of AI. Is that kind of Primer in a nutshell?

Yeah, I think that's right. So Primer uses a array of machine learning, whether it's deep learning or nlp, to effectively craft meaning from data. That's what you're trying to do, right? Or the old days, we'd say extract signal from noise. And what Primer is doing is giving you the world's greatest analyst who would create a report for you, effectively why they called it Primer, something that you can read and in real time pull out enormous amounts of information. I was an analyst earlier in my career on Capitol Hill, and you would read all these reports and all these papers, and you would sit through congressional hearings, and then I have to write a summary for my boss, and that would get passed up and other summaries would get munched together. And ultimately that's how you were creating intelligence. And that's. It's. Primer is a great example on how to do that, not just for national security, but it's your point for other industries. If anything, we Live in a world where the speed and volume of data coming at us is somewhat overwhelming. Some of it's good, some of it's just junk. Right. And some of it, as we understand it, is actually misinformation. So it's going to take tools like primer and machine learning to be able to work through that so you can extract really intelligent signal. One of my favorite books when I lived in D.C. was Robert Kennedy's Thirteen Days, and it describes how they avoided groupthink in the Cuban missile crisis. Think about this. What could be more tense than a nuclear standoff between the United States and Russia as they're kind of bringing ships into Cuba and they're assembling missile silos, and we were doing flybys with U2s and other spy planes to kind of capture information. And the way the groups of intelligence analysts and government officials came together and argued and worked through this, including taking some time, not just reacting all of the time, is, I think, a great lesson on how decision making, and in this case, problem solving and game theory, came to play in probably one of the most strategic negotiations of our lifetime. And one of the things that we have to learn is that computer systems don't blink. They're really fast, but they're not necessarily good at game theory and decision making. I think when you see technologies like Primer and others and then human in the loop alongside of AI, we're kind of entering a new phase, whether it's in healthcare, whether it is in national defense, whether it's even in things like personal finance, that you have to start to kind of recreate or create kind of a syntactic and intelligent mesh of all these technologies to really optimize outcomes. That's what I love about technologies like Primers, because I think it's a building block for better decision making across a bunch of industries. Not just a tool that can parse massive amounts of information. You can train computer vision to do facial recognition, but it takes real work to avoid bias. Yeah, yeah. And so, you know, we're at a point where, you know, and I think this is very much part of dtec, where this massive amount of data is available. But it's. But. But using it is actually getting more and more complicated.

Yeah. Let's talk also about automation, if you don't mind, because there's a lot out now about robots. And you go on YouTube, you watch all these great videos of dancing robots and robots that can do parkour and robots that are real and available in the industry today. You guys have Invested in some robotics companies. Like one is that I liked was Agility robots, Agility Robotics. What I liked about that and see if I'm hitting on the right thing here, this, the robots I saw with Agility seem to do simple things very, very well. I don't think I would buy one of their robots if I wanted it to do parkour or, you know, these other things like that. I would buy their robots if I wanted to restock a shelf or you know, get the big boxes down and you know, take the small boxes out.

Of the big box.

Simple use cases like that I think will be extremely disruptive and are very much needed in our supply chain and our overall economy.

Yeah, so I mean if you've seen digit from Agility Robotics, rather than say our robotic overlords are here, I'd say our robotic coworkers are starting to arrive. So what's really unique and the team from Agility, like many people in robotics, have a very strong Carnegie Mellon heritage, which is one of the national treasures at university for the robotics field in the world and certainly in the United States. This is a class of robots that, to your point where you'll see often in supply chain type of situations that were designed to work alongside human beings, not to replace human beings, were not designed and not just from a safety point of view, but from an efficacy point of view. And so they were built and designed and are being very successfully deployed in real world situations today without having to retrofit warehouses, factories, parts of the supply chain to use them. Because if you were to design a new warehouse and think about like an Amazon, you design it basically to be robot first and human second. Well, that's going to probably take a little while for the rest of the, you know, the economy. And if you think about the shipping companies and the logistics companies and the warehouses and the wholesale distributors, we're going to be working side by side. And it comes at an interesting time that, you know, we were, you were talking about waiting, you were talking about the supply chain to get a heart scan. Right. You know, there are, there's a, I think a 25,000 sonographer gap in the United States. And there we're on our way to a 30,000 person surgical gap. But if you talk to people in the supply chain, they can't find workers either. They can't find people to drive tractors. So it's very interesting, you know, situation in our economy. So we are going to get used to working side by side with robotics and I'm not sure it'll all be neat and easy. I grew up in Brooklyn. I imagine some of those robots are going to get tagged or knocked down, you know, along the way. But, but that's, but, but they, they provide whether it's in gap areas or actually in hazardous areas. Right. Because you know, if you think about most warehouse work, it's kind of back breaking, taxing work. You know, you don't, you don't, you don't, you don't stock shelves in a warehouse with 50 pound pallet, you know, packages into your 50s, 60s and 70s. You don't want to be doing that kind of work. Your body will actually break down. So very, very exciting. What we see in agility and some of these initiatives.

Well, just to share a personal story, Alan, early in my youth, high school years, I did work in a factory. And my job in the factory was I took a big box down and in that big box there were shoes. And I took the shoes and put them in shoe boxes and then put all those back in the big box and put the big box back up on the shelf. And I did that for about three days. And then I realized that, you know what, I'm going to have to get an education because I just, I can't do this. It's going to kill me and others more physically fit than me. I mean, maybe you're into that thing.

No, no. When I was in high school, I worked one summer. There's a Jetro warehouse in Brooklyn on the docks. I worked in the refrigerated case. Right. This is a wholesale cash and carry warehouse for small stores and groceries in New York City. Wearing a big coat. Think about the conditions of people who work and food processing, whether it's in meat or frozen goods, like, you know, there are people doing those jobs, but they're better done by somebody who's not going to have their life shortened or injured or you know, get, develop a terrible case of arthritis later in life through all that exposure to that cold or that heat. So, you know, I, you know, obviously we were all highly conscious that the goal is not to kill jobs. I think that's a big way. The issue is like, look at the really tough jobs that are better done by automation and robotics. And I think that's where companies like agility play a very strong role.

Alan, other companies that excite you in your portfolio that we ought to talk about.

How many hours do you have for a DCV commercial?

Yeah, we could do this all day. I tell you, this is interesting stuff.

Yeah, no, when I look around, I Mean, there's just enormous interest across our portfolio. We have a bunch of companies in the therapeutics area. Our Bio fund invested in a company called Appcellara, which is the monoclonal antibody that Eli Lilly, our partner, brought to market to deal with the symptoms of COVID that was created very quickly. It's an mRNA. So one thing I would advise your listeners, if they're interested in this area, everybody needs to read Walter Isaacson's book the Code Breaker about Jennifer Dudna and the race to create rna. We have a bunch of companies that are figuring out how to synthesize therapeutics at a speed that's unheard of. And everybody should remember what happened during warp speed. We actually created a highly effective vaccine in a year to deal with multiple vaccines, to deal with a worldwide epidemic, the SARS COVID 19 virus. The ability to do this this quickly was not available. And if it wasn't for the computational power to do that, we have another company in a similar vein, Recursion Pharmaceutical, that uses artificial intelligence to create a range of therapeutics and pharmaceutical products to help people's health and doing it at a really rapid pace. So I think the impacts for people's wellness and their longevity is very much being aided by people. Half in the scientific world, people you think about sitting on a lab bench and synthesizing proteins, and half of the people in the computing world that are building the AI and machine learning models to be able to do that. This is one of the most exciting parts of our society. I don't know when, but I think we have a bunch of companies that are working on much earlier detection of cancer. Companies like Freenom just they're in the middle of a 12,000 person trial to prove in their technology. For some of us older gentlemen who've been through the pleasure of a colonoscopy, the ability earlier in life to detect correctal and other cancers that you would find in a, you know, through Kalinovsky would have had to go through that lovely experience of drinking that fluids and giving them back and going to a hospital and being under for a couple of hours while they, you know, just amazing advances. And I feel privileged that we get to work with the people that are doing this and co invest alongside other great investors that build these companies.

Yeah, it's just amazing everything you're reviewing here. And I want to capture this book that you mentioned, Isaacson's the Code breakers.

Which is about, yeah.

Doctor researcher who helped.

What did she do?

She figured out MRNA and its magic.

What did she do well there she was, she was one of the lead researchers, Jennifer Dudner, and she's at Berkeley, but she worked with actually in the Code Breaker talks about the French scientists that she worked with to really kind of understand, you know, just as people figured out what DNA was, figuring out what RNA is and then figure out how to apply it in a range of therapeutics, there was a bunch of people working on it. What's delightful about this book is it was a race. It is almost like reading. I'm a huge fan of basketball and you know, I have been fortunate. The last couple years I've been able to watch the Golden State warriors, which is a company with an amazing narrative and how that team was put together. But the competition that goes on in our sports leagues are just above the rim. The competition around RNA and biological fields is world class. So the book doesn't just highlight the biography of Jennifer Dubner and her career and her contributions leading to the Nobel Prize. It it's Isaacson is an amazing cartographer for the entire field, all of the players, all their flaws and their color of who they are as people and helps you understand how this came about. And this is one of the most important scientific building blocks in medicine that we and pharmaceuticals that we have today. And everybody should really understand it because it is a source of not only national pride and competitiveness, but it is potentially going to be the part of the technological curve that is going to end some of the most malignant diseases that we live with. I'm not real sure about immortality, but certainly mortality with more productive years is probably a good start.

Thanks, Alan. And that's definitely capture a link to that book in our show notes and just downloaded it to my Kindle, so I appreciate it. Awesome, awesome, Alan, thanks for all the time today. This has been great.

Yeah, it's really delightful to be here. I hope I didn't completely chew your ear off. As you might guess, I'm relatively happy with what I do. This part of my career. It is. This probably is an exciting a time as in tech probably since the 70s and the birth of the personal computer, because these new fields are just opening up in front of us and the STEM fields interacting with the computing and technology fields are really going to, I think, hopefully. I shouldn't even say hopefully. I firmly believe they're going to power a much more dynamic and productive society and maybe help us avoid some of the things that are kind of a little bit out there on the horizon. Scaring the hoot out of us.

Yeah. One other Question I have for you, and that is as you study things prior to an investment, there's a due diligence piece that you do. Can you describe that? Due diligence? How do you, I know you're not just saying I want to pick a winner, but how do you pick winners? How do you do due diligence and know that you have a team that has some chance of success?

Well, I think you just actually said something that goes a bit to the, to the picking part. I mean inevitably investing in teams means investing in people and really taking the time to get to know people, including the people around our firm that help us in due diligence. So we have a secret weapon though I'm about to give it away, called the DCVC Equity Partner Group. So we have a group of 50 people around our funds that are, have skin in the game with us who help us do amazing due diligence and help us make, make interrupt interpretations. So when we want to due diligence an area, we don't just use our own expertise. We usually one or two clicks away from some of the top people in the field and they sometimes they'll even co invest alongside of us or they'll get involved in these companies along the way. So it's very hard to kind of armchair a quarterback because on paper, you know, you don't see bad investments in bad teams, but you really try to do that. And then the hard part is playing that multidimensional chess game and not just understanding what the next three years are. You're going to say, is it, how long is it going to take to, for one of these technologies to come to market? What is it going to take to invest in it? How much capital is it going to need? How is it going to need to evolve over time? And are you heading toward an open stream and open water or are you moving to a little cul de sac? Right. And then we spend a lot of time, I'd love to say, just discussing, but yelling and arguing and pushing very hard on ourselves. I think the hardest thing about being an investor is avoiding confirmation bias. So the things that make you successful in your career frequently are also the things that trip you up in thinking about new things. So I always like to say I have this level of experience, but at any problem, only 50% of it is actually relevant. The hard part is understanding what 50% works. I think that's what Tony Soprano used to say, remember when Is the lowest form of conversation. So you have to be careful about nostalgia as an investment and even if I had a successful experience earlier in my career, it may actually be blinding me. For what you don't want to do is just look for repeat patterns. And so you try to build intellectual muscles and discipline to have the best thinkers around you, really think carefully through things and avoid your own confirmation bias and things that you might find appealing or comfortable, but may be absolutely wrong. Then you pray, because you're going to be wrong part of the time. You just try to pray that you're right more than you are wrong.

Alan, this is great advice. Great advice to end this on. I really, really appreciate that.

Okay, awesome. Thanks for having me.

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