Speaker 1:
From the library of the New York Stock Exchange at the corner of Wall and Broad Streets in New York City, you're inside the ICE House, our podcast from Intercontinental Exchange on markets, leadership, and vision and global business, the dream drivers that have made the NYSE an indispensable institution of global growth for over 225 years. Each week, we feature stories of those who hatch plans, create jobs, and harness the engine of capitalism right here, right now at the NYSE and at ICE's exchanges and clearinghouses around the world, and now welcome inside the ICE House. Here's your host, Josh King of Intercontinental Exchange.
Josh King:
As we approach the halfway point of the year, it feels like we can already chalk up 2023 as the year that artificial intelligence went mainstream. The year kicked off with the frenzy around the launch of ChatGPT by OpenAI. That announcement was soon followed by Google, Microsoft, and China's Baidu rushing out their own platforms to market. The fervor led to discussions in every office on Wall Street and Main Street about how ChatGPT's bot along with the dozens of other AI platforms and its tailwind could be folded into day-to-day operations.
The buzz around artificial intelligence often feels like a blockbuster movie with equal parts suspense, excitement, anticipation, anxiety, and fear. That actually makes some sense because most folks were introduced to the concept of AI by a Hollywood movie, and depending on your age, you're likely thinking about Ex Machina, iRobot, The Matrix, Terminator or Stanley Kubrick's 2001: A Space Odyssey. We consumed a lot of movies in the King household and Kubrick was a house favorite, and even 55 years later, the HAL 9000 fits the public's understanding of AI. Let's take a listen.
HAL:
Good afternoon, Mr. Amer. Everything is going extremely well. Let me put it this way, Mr. Amer. The 9000 series is the most reliable computer ever made. No 9000 computer has ever made a mistake or distorted information. So I am constantly occupied. I am putting myself to the fullest possible use, which is all I think that any conscious entity can ever hope to do.
Josh King:
Thank you, HAL. The emotions around artificial intelligence seem to have peaked with the ChatGPT fervor of 2023 and, with time, I guess so will the public's fear of it. We've passed the time imagining of how AI will change the world to an era talking about how it can be safely implemented and developed. The fact is AI's use continues to grow as it has for decades and will continue for decades to come.
Our guest today, BigBear.ai CEO Mandy Long, is leading the efforts of the company that debuted here with an IPO back in 2021 to help clients bring to bear the power of AI on the challenges facing them from the high seas to the data cloud. Our conversation with BigBear.ai CEO Mandy Long on the current state of AI, the future of the sector and commercializing cutting edge innovation, it's all coming up right after this.
Speaker 4:
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Josh King:
Our guest today, Mandy Long, was appointed CEO of BigBear.ai. That's NYSE ticker symbol BBAI. In October, 2022, she joined the company from IBM where she held a number of leadership positions over her tenure, including VP of IBM's IT automation, Vice President IBM integration and application platforms and other roles. Prior to joining IBM, Mandy held the position of Vice President of Product Management at both Modernizing Medicine and Experian Health. Welcome, Mandy, inside the ICE House and to the New York Stock Exchange.
Mandy Long:
Thank you. Happy to be here. Thank you for having me.
Josh King:
So despite seeing the normalization in ChatGPT talk, what are some of the most exciting applications of AI that you're currently seeing that are, to use your phrase, moving beyond the theoretical into everyday use?
Mandy Long:
The thing that's exciting about where we are right now is that we are still in the early days of understanding how this powerful technology is going to be applied, and as you said, outside of the theoretical sense and in the production environment. That's most of where I've spent my career is taking complex and early stage emerging tech and applying it in the real world because the last mile associated with that is often the most difficult because you introduce the human factor, and humans are humans and we are complex creatures and have our own needs.
In terms of where I see the most emerging right now, I think particularly in the context of BigBear.ai is really the rapid maturation of not only computer vision, but its application in terms of performance and ability to be able to play a role in the human, in the loop environment. What I mean by that is a lot of our work in the CV realm is focused on the maritime use case. We sit on autonomous surface vessels and we support the war fighter in reducing the risk associated with human life loss in really high stakes environments. What we're seeing now as a result of the leapfrogs that have happened in compute capacity is that we can do more than ever at the edge, and we really are becoming the eyeballs of the services that are protecting our country.
Josh King:
We're going to get into a lot of that a little later in our conversation, Mandy. As I mentioned in the intro, a lot of media interest in AI seems to be driven more by fear than excitement. What are some of the biggest misconceptions about AI that you've encountered in your work?
Mandy Long:
I think a fear is a good way to describe it, and in many ways, I would say though it's fear of change. What we're going through right now is the fourth industrial revolution, and the way that people live and work will change forever as a result of the technology that is finding its footing in our day-to-day lives. A lot of the misconceptions that I see are really associated with how these models are trained and what their capacity is to be able to contribute. A lot of that has been on the back of some of what's happened in 2023.
In introducing the interaction between the average everyday individual who may not live in a technical seat to being able to interact with these models, it's overwhelming to realize that we have technical capabilities that can, in many ways, generate and or represent human language.
For the population that doesn't understand the depths of a lot of how these models get trained, I think that there is an inaccurate feeling that this idea of thought or the ability to go off script is possible. The reality is not the case. These models even at scale are still derivative of trained on large data sets, trained on the data that we or the technology that we've created has generated itself, and they're an interpretation of those things.
From a handler standpoint, which is a technologist, a lot of where we sit is in the creation of and management of these models, they're still in controlled environments. They still will be in controlled environments. The higher stakes you get, not only I think in the defense sector but also in a previous sector I worked in in medical devices, freeform here. We're applying these things in our use cases still and we have not made the launch in a production environment into completely federated learning.
Josh King:
AI can mean a lot of different things, and we've seen it as a catchall for relatively undefined field and industry. I remember when your company went public two years ago long before the current buzz and noting that it was part of the business' public identity. How does BigBear.ai differentiate itself from other companies in the AI space? Give us just a quick elevator pitch before we get into more detail later.
Mandy Long:
The biggest thing that I spend a lot of time talking about as we meet with customers and partners and the market in general is that what makes us different is that we're not an all you can eat buffet of AI. We do very specific things, and it's one of the reasons why our mission is focused around delivering clarity for the world's most complex decisions. We live in the edge cases. We work on the stuff that most other companies cannot work on. They don't have the subject matter expertise, nor do they have the access associated with being able to train models that can be applied in these environments.
So the way that I boil it down for folks is that we do work in three markets. We work in supply chains and logistics, we work in autonomous systems, and we work in cybersecurity. Within those buckets, we're not an all you can eat. We're not a do everything. We are laser focused on the critical path. So we deliver technology for the edge cases that others do not address.
Josh King:
Can you talk about the acquisitions that make up BigBear.ai and how they were brought together prior to going public in late 2021?
Mandy Long:
Certainly, and you're right, A common misconception that I bump into in my new spot and role is that we're a new company, we're an emerging technology company, and in many ways, that couldn't be farther from the truth. A lot of the capabilities that we have have been around for not five years, seven years. We're talking 10 years, 20 years, and used in and by some of the largest organizations that exist in the world.
A couple examples. So the pro model acquisition, which is one that we brought in just a little over a year ago, has an extraordinarily robust and market leading capability in discrete-event simulation, which is I think in many ways the prior term for the buzzword now, which is digital twins. So how do you create a high efficiency simulation environment to be able to support decision making? If you're a complex manufacturer or you are working in some of the disruption that's happened in the global supply chains, it's very expensive to guess.
What our capabilities do and have been used for years is to take the guesswork out of it because we can build N, number of simulations and models, and make recommendations for how to deploy capital. If you're doing it at the scale that most of our clients are doing it at, we sit in the critical path.
Josh King:
Talking about sitting in the critical path, before we get into more recent activities of Big Bear, I wanted to hear how you found your way to that critical path from swimming in Olympic trials to swimming among these tech giants on the cutting edge of computing. Was technology something that you were interested in when you were growing up in Chicago?
Mandy Long:
I came up in tech by accident. As an undergrad, I was an economics major and I, for the longest time, thought that I would go into banking. I graduated in 2008, which was not the year to go into banking. I got an interview with a company that didn't really have a website, that I didn't know much about, and I got on a plane and I flew to Madison, Wisconsin and I walked into the doors of Epic. I think that the universe lined up for me in a major way because as a person who my roots are in creative and I love solving difficult problems and problems that matter, I found my home in healthcare and I spent you over a decade working in some of the most challenging environments and the environments that matter. So while I would say I wasn't born a technologist, I've certainly become one.
Josh King:
Talking about not being born a technologist, you said that your father often took you to his corporate events and conferences. How did that exposure and his guidance help you along in your career?
Mandy Long:
My dad has been one of my greatest champions, and even from when I was young, I think what I learned in those environments was that I had to get really comfortable really quickly with the fact that I was never going to fit into the traditional mold, and I had to get very comfortable with myself and the skillsets that I brought to the table in recognizing that while I might not look like, act like, speak like a lot of the folks who sat in those roles, it didn't diminish what I could bring to the table. It was really a privilege to have a parent who was committed to, in many ways, try to make me swim in the deep end. No question, but it's how I learned. I think he recognized that really early. So that was how I learned.
Josh King:
We talked about your dad. Let's talk about your mom. She was a senior manager at EY, but also modeled this strong separation of work and home life that a lot of us struggle with. How have you been able to find that balance with your children or do they end up schlepping to conferences with you?
Mandy Long:
They have. I want to be honest. That has definitely happened. My mom was this amazing ... She made this extraordinary choice. I have two siblings, where she was a senior partner at EY, she was making her way, and she made a choice to be a full-time mom and advocate for us. What I saw in that was that my mom was always present. So it was whether I was doing the swimming events or whether I was picking up a new activity or whether my siblings were doing different things, we went to colleges all over the country, my mom has been this constant foundational presence in my life that she has made supporting me a key priority for her.
I think that has something that has fed into how my husband and I parent. So we have four very young kids. My youngest just actually turned five yesterday. We have identical twin boys and they're seven, and then my oldest daughter is nine. I think that the thing that I have come back to over and over and over again is that I'm going to be a mom first, but I think because of the way that the world has changed with COVID, I don't have to choose whether or not I'm also going to be a CEO.
What it means for me is that, to your point, yes, sometimes my kids are there more often than not, as today I'm working from home because my husband and I are doing the trade off because he's traveling and I'm here, is that my kids sometimes join me for calls. They've joined me for all hands, and I get to fit in the minutes, which is something that I've really come to love is that I think before, I had this hypothesis that the way that it had to be done was that I had to build these solid walls. I was going to leave in the morning, I was going to do my thing at work, I was going to wear that hat, and then I was going to come home and then I was going to be mom. Frankly, that's just not how I want to do it, nor is it what works for me and my husband. So instead, I'm a mom all the time and I get the privilege of being a mom in the minutes between calls and seeing a lot of the things that I think I would otherwise miss if I was in an office all day.
Josh King:
We talked about your first gig at Epic. That opportunity took you to IBM to work with Watson, which, of course, is named for the person who brought the company public in 1910. It was one of the most well-known AI platforms. I just want to hear Watson and a man named Bob from a meeting that they had back in 2016.
Speaker 8:
Bob Dylan, to improve my language skills, I've read all your lyrics.
Bob Dylan:
You've read all of my lyrics.
Speaker 8:
I can read 800 million pages per second.
Bob Dylan:
That's fast.
Speaker 8:
My analysis shows your major themes are that time passes and love fades.
Bob Dylan:
That sounds about right.
Speaker 8:
I have never known love.
Bob Dylan:
Maybe we should write a song together.
Speaker 8:
I can sing.
Bob Dylan:
You can sing?
Speaker 8:
Doo bee bop bee bop bee doo. Doo bee doo bee doo. Doo doo. Doo bee doo.
Josh King:
Mandy, The NYSE's president Lynn Martin began her career at IBM and often talks about the mark that that environment had on her career success. How did your experience at IBM shape your leadership style and what were the lessons you learned during that time that shaped how you run Big Bear?
Mandy Long:
I will forever be a proud IBMer. While I'm not there anymore, the five years that I spent as a part of that organization I think fundamentally changed the way that I thought about the application of this kind of technology. I was recruited into Watson Health and I spent several of those years at the beginning working on the absolute bleeding edge of what could be done in computer vision and AI as applied to healthcare. More specifically, I had the privilege of working on and had a product for the Watson Health Imaging Business, which is a medical device business, and building out computer vision associated with things like looking at mammography and chest CT and chest X-ray and looking for things like breast cancer and prostate cancer and lung cancer.
It is a humbling thing to realize that and really start to wrap your head around the reality of the role that you're playing as a technologist in supporting clinicians and making decisions that affect people's lives. That was frankly a life-altering moment for me was having the responsibility of the teams that were building that type of tech. Then I brought that even further when I became Head of Product for Watson for Oncology and Watson for Genomics, and those are some of the names that most of the folks in the public know.
IBM was way out front in talking about the role that artificial intelligence is going to be able to play in medicine. I think that while we absorbed the bumps and bruises associated with being a first mover, it didn't change the reality of what we were seeing, which was that healthcare was and is going to be fundamentally different because of AI. As a parent and as a mother of two kids who have special needs, I need AI to play a role in the healthcare system because the healthcare system is still fundamentally broken and it is particularly broken for those who cannot advocate for themselves.
So talk about a way to come into IBM. It was amazing to be able to go around the world and to talk about the technology that we were doing and to do it on behalf of, I think, one of the greatest organizations that exists. Then I have the privilege of moving into IBM software, which is another remarkable part of the portfolio. I played a role in their leadership team in their automation business, which is one of their big bets. So I went from living in verticalized technology in the application of AI, so very use case, narrow, where we're focused on this disease and this thing, and I made the jump to horizontal.
So I went into broader automation technologies that were being applied to every sector. I think when I reflect now on what prepared me for this role, I think it was that I saw and lived global, at scale, horizontal and vertical technology with the use of AI in production with incredibly critical use cases and incredibly complex clients. When I look at what we have at Big Bear and what brought me here because the one area that I really hadn't touched, if we're being honest, is the defense and intelligence community. So that was a domain jump for me, but I still felt really prepared because for my whole career, I've been learning new domains, whether it's sub-segments of the healthcare industry or IT or what's being done in the integration business on a global basis.
I'm not afraid of learning the new domains because what I've come to realize in doing complex software and complex technology is that most often, while the vernacular might be different, the problems are the same. They're often rooted in the ability to communicate, the ability to process information at scale and the ability to arm decision makers with the right info.
Josh King:
So Mandy, you were announced as CEO late last year and, according to our research, were charged with turning around the company. What needed to be turned around?
Mandy Long:
Big Bear was definitely in, I think, unequivocally a pretty difficult position. I have worked in turnarounds and high growth, and so that made me comfortable coming to the table in it, but most of what needed to actually be turned around had nothing to do with the foundational capabilities of BigBear.ai, which is a champagne problem. Most of the circumstances that I walked into with difficult situations, you have angry customers, you're maybe in a lot of marketing and a little technology. These are the problems that we all know about. None of those were present here.
In the time that I've been in the seat, I have gotten exactly zero escalation calls around unhappy customers. I don't know a single other CEO who can say that because we do the right thing and our customers love us and trust us to work on the edges. We work on the hard stuff, and we're not afraid to do it and we'll do what it takes to get it done well. We had definitely gotten ahead of our skis in terms of scaling. I had one of my team members, I think, put it really beautifully, which is, "We just bought too big of shoes," and that was, I think, the root of what was putting us in a tough position was we had scale, we had bought too big of shoes, we had scaled maybe before we were ready in terms of the business that we needed to deliver on, and then a lot has happened in the capital markets.
So what I've been focused on is one was get us in a position from a liquidity standpoint where we're like, "We can just put that behind us," which we've done, but the bigger area, which is really the fun part is we have a formidable technology portfolio that nobody knows about. So most of my work in this turnaround and the team's work in it has a lot less to do with building and a lot more to do with educating. So that's a lot of where I'm focused on today.
Josh King:
So I want to talk a little bit more about the fun part as we head into the break. You saw quick success upon taking the office. An article from January of this year wrote, and I'm going to quote it, "Barely 90 days into her tenure as BigBear.ai's CEO, Mandy Long can already boast a handful of significant victories." Mandy talk about some of your top strategic priorities that you've implemented and your vision for the company since you came on board.
Mandy Long:
Yeah, and that is a very nice headline, so thank you for sharing that. I put three things in place when I walked in the building, and they have continued to be the most important priorities for us as we go forward. I am an outcomes person and I believe that we should put people in a position where they figure out how. As long as we know where we want to get to, the path can change and we can pivot, but we need to know where we're going, and that was focused on three things.
The first was make lemonade or repeatable patterns, do more of what we're good at because we are good at a lot of things. The second was good housekeeping, and some of that's not sexy or fancy or whatever it is, but we have to do adulting. We have to make good decisions as it relates to spend. We have to make good decisions around where we're going to invest and scale, and we have to live in the reality that we are the stewards of the business. No one's showing up telling us how to do this. It's on us.
The third was find rare Earth because a lot of what's been buried in the business through the consolidation of the different entities and the noise in the market is that I think we lost a lot of what actually made the company special, and what was interesting was that we didn't lose it and it went away. We lost it and it was just over there and no one was paying attention to it. So the find rare earth initiative for us has actually been already bearing fruit, but we do those three things. I think if you talk to anybody within the company, those are the three things. We talk about them every time we do an all hands, we talk about them in all of our executive leadership calls. Everything we do is rooted in those three things.
Josh King:
Practically all companies, if you're being disrupted, but the risk must be significantly higher for a company like yours. How has BigBear.ai adapted to changes in the AI industry over the past couple years to ensure that you're going to stay at the forefront of innovation?
Mandy Long:
So the team has done a spectacular job of working with our customers to continue to understand their needs and to build solutions that are focused on actual validated needs. I think a lot of what companies can get sucked into is what's the hot topic of the day, what's the external report saying, but there's nothing that's going to get better than the relationship with the end users, and we have a lot of those.
So what Big Bear has done and will continue to do is that we work directly ... We're going to talk to the people who use it, and that's where we're going to understand where the pain is and we're going to build technology around that. We have a very large innovation ecosystem just within our business. We have team members who nights and we ... I love it. Go solve the problem, figure out if you have something, and then if we cross the threshold of what's possible, practical and people will pay for it, we'll pour gasoline on it and we'll get going, and because we know who we are, I think that's what's going to keep us ahead is I don't have any misconceptions about the fact that the greatest ideas in our organization and how BigBear.ai will continue to evolve is not on the back of what I can make up in a closet. It's on the back of the people who make this business work, who work with our customers and know what they need.
Josh King:
I wanted to just geek out for a minute on one of those real world applications that are, as we talked about earlier, on the edge. Now, this is the result, I think, of the agreement that you have with L3Harris, which is NYSE ticker symbol LHX, and your company that you announced this week that is going to integrate BigBear.ai's forecasting computer vision technology with the AS View System.
Now, this system, by the way, was first installed on the USNS Apalachicola, which my friend and former colleague Senator Kelly Loeffler christened back in 2021. As I was watching that christening ceremony, you could see what the application of that ship was, basically to bring a large contingent of Marines into a hostile territory, probably under a lot of fire where you don't want to unnecessarily expose sailors and operators of the ship to hostile fire. The Marines are going to have to take it because they're going ashore, but basically, that huge ship can basically operate on its own and make some of its own decisions, right?
Mandy Long:
That's right. I think what's extraordinary for us is that we have an amazing and longtime relationship with L3Harris. I think that's one of the things that's important to note on this is that our most recent partnership announcement is building on years of deep and trusting work together. What I think is remarkable about what we've been able to navigate and how we are tackling the autonomous systems world is that BigBear.ai has superpowers associated with the application of artificial intelligence in production. We are very good at computer vision. We are very good at predictive analytics, particularly for the war fighter.
L3Harris is one of the most formidable autonomous systems and platform builders that exist in the space. So by combining those two things, what we're going to be able to solve together is exactly to your point. How do we get further in terms of operational reach and be able to deploy these vessels into environments that previously we just weren't comfortable sending people into? Then how can we actually start to take advantage of what can be done at scale in, I'm going to be nerdy too, in the pixels because if you think about what these cameras are able to pick up relative to just human cognition and what we can process, there is incredible power in that manned/unmanned teaming for how we're going to be able to use these sensors and these cameras and the models that are associated with it to basically sift through the noise and get to the data that matters faster. To me, like it's closing the kill chain.
Josh King:
After the break, Mandy Long, the CEO of BigBear.ai, and I are going to talk about the company's three main verticals, supply chain and logistics, cybersecurity, and autonomous systems in the future really of the entire sector. That's all coming up right after this.
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Josh King:
Welcome back. Before the break, I was talking to Mandy Long, the CEO of BigBear.ai about current topics in artificial intelligence, her career and the history of the company that she's leading. Mandy, you mentioned BigBear.ai's work with AI and autonomous systems where before the break we were talking about that. I believe over 90% of your business is tied to government contracts. We talked before the break about L3Harris and the Navy, but how are you working with the overall Department of Defense to support, for instance, their work in Ukraine and elsewhere?
Mandy Long:
Absolutely. So you're right. The vast majority of our business is focused on work in the defense and intelligence communities with the US federal government, and we're proud of that legacy. We do, I want to be fair, we do have a existing and growing private sector footprint. We do work with everything from complex manufacturers in the industrial base warehouse, operations, logistics, life sciences. So I want to acknowledge that a lot of the ... We talked about horizontal technology earlier. A lot of that technology is applied on both sides of the bridge, but when we think about the work that we do for DOD, a lot of it's really focused on three core areas. One is that we do a lot of work in helping the federal government and specifically the defense community in organizing information so that they can make determinations for how to deploy resources not only at a strategic basis.
So if you think about force management at scale or how to deploy resources from a logistics standpoint, but also in the land of the operator, so how do you go from strategic decision making all the way down the pipeline into operational and tactical decision making, we provide a lot of technology that lives in that bucket. That's become a really important part of our business, particularly because of what's happening in the world right now. We have a pretty unprecedented amount of disruption happening to global supply chains. As we think about how the battle space is evolving, the decision cycles are just different and they will be fundamentally different because many of the new battle spaces that we're looking at are areas that we haven't really had to touch before. It's the world like cyber and space. We spend a lot of time and we have a good chunk of our portfolio business that is focused on supporting those things.
The second area, which is a superpower we have in cybersecurity, which is focused on reverse engineering. So we do a lot of work in threat analysis, identification, mitigation. We do a ton of vulnerability assessment as a service. So think about that from the lens of if you're a very large platform manufacturer, if you manufacture for the federal government, the cyber risk component of that is very important. We are a close partner and an adjunct to, in many ways, those existing processes, where we provide those services as a service on an ongoing basis as an objective third party to say, "Okay. From a defensive but also an offensive standpoint, here's what you need to be thinking about."
Then the last piece of what we do is we already talked about a little bit in terms of autonomous systems is computer vision, particularly focused around identification, classification of anomalous marine objects, but also predictive forecasting.
Josh King:
You teased a little earlier about ... We've been talking for a couple minutes now about the various parts of your work and the business of the company that is focused on defense-related activity. You teased that there was more activity that you're working on in the private sector. It's no surprise. The technology pipeline from the government to the private sector is a well-worn one from the first GPS system, really, to think about the entire internet. Can you take us inside the process of how BigBear.ai identifies and works with clients and partners to tailor some of your maybe defense-related technology and bridge the gap between products that you've done for the federal government and applying it to use cases in the private sector?
Mandy Long:
Yeah, absolutely. I think we can stick close to home for me because it's an area that we're doing a lot of exploration, and it is, I think, a good example. So if we think about reverse engineering and the role that that type of analysis can provide, a lot of the risk that exists in our society around cybersecurity is in the private sector. It's in these devices and in IoT that's been developed without that in mind. They've created open doors across our entire ecosystem for how adversarial behavior can sneak in.
An area where I think that is front of mind for many people is in healthcare. If you think about as a former med device manufacturer and leader, do the best you can, but we were in the business of building medical devices. I think there is an incredible amount of value that the rigor and maturity that exists within the defense community associated with how we think about cybersecurity posturing can be brought to the private sector because when we think about some of the large forces that we're looking at and a lot of the risks that were, I think, taking on as a society, as we think about the geopolitical climate, it's not going to matter which side of the bridge you sit on. If we have a challenge associated with being able to deal with cybersecurity risk, we have to look at it as a society as a whole. So I think that's one example.
Another example that I would give is the federal government's not the only part of the world that's dealing with supply chain disruption. If you are a large manufacturer or if you're building ... Look at some of the disruption that's happened in life sciences. If you're trying to get absolutely critical manufacturing and distribution done into our country, you're in a tough spot right now. There is impact that, I think, we are only beginning to understand and we are in react mode right now. So a lot of the technology that we've used on the federal government side associated with how to get ahead of that, how to look at potential risk areas, how to develop alternative strategies, we're seeing a huge amount of tailwinds associated with bringing into the private sector to help them plan and respond.
Josh King:
Staying on maybe one of those big challenges that private sector is facing, a lot of the recent CEOs that we've had on the show, people that run paper products, businesses, people that run technology giants, even people that are involved in running logistics companies, they have been paralyzed at times over the past couple years by disruptions to the global supply chain. Let's geek out a little bit on how BigBear.ai is tackling those issues and what role does the company have in mitigating these real world delivery disruptions?
Mandy Long:
Yeah, and you're right. We are in a new world as it relates to having to deal with disruption, and if you are running a large organization that has been dependent on global supply chains for how you build and deliver capabilities to the market, this is a real problem for you. The way that we break down our portfolio there and the services that we offer live at a couple of different layers in the cake.
At the very top level, which is I think an area that we're seeing more and more pull for, is a solution that is focused on geopolitical and macroeconomic forecasting and simulation. So as I'm sure you can imagine, you can see how those types of capabilities can be applied in the world of defense and intelligence, but if you are, to your point, if you're a paper manufacturer, if you are moving goods and you're doing commodity acquisition associated with how you actually create goods, being able to look out ahead and being able to as well simulate levers to be able to say, "Okay. If this is a potential disruption that's happening to one of my channels, where are the alternative places I can go? Where can I have the most impact to be able to mitigate continuity challenges?" that's one level. So that's at the top.
So if I'm a senior executive that's trying to make decisions around where I'm going to bolster my business to be able to deal with risk, our capabilities there fit in, but we go all the way down the stack to even at a hyper tactical level, we have a digital twin, a simulation capability that's used by many of these manufacturers today that we will be able to or we can and we do today, we have full visualization and analysis of whether you're having to reformat how your manufacturing floor is set up because, frankly, you're seeing a massive upheaval in terms of the amount of throughput that you need to be able to deal with or you're seeing impacts in human labor associated with having to introduce robotics to your processes or if you're down in the distribution layer of how are you running and optimizing this warehouse knowing that we're continuing to have massive labor challenges and shortages and labor associated with getting those staffing, those roles filled so that we can actually move the goods out of the building and into the last mile, that's where a lot of our tools fit.
I think for BigBear.ai, I think we often, in many ways, get confused with maybe we only do cyber or maybe we're a federal contractor that sits in as an SI. Well, in many ways, that couldn't be further from the truth. We have hundreds of customers who are in the manufacturing and warehouse ops world who rely on us every day to make those decisions.
Josh King:
One more area we can geek out on before we wind our way toward the end of our conversation, you've mentioned it a couple times, it is a topic near to you because of your background in healthcare, is the silver tsunami that experts are predicting will overwhelm our healthcare system in the next decade, also the system currently very beset by human bias as well in terms of quality of care that's delivered. What is BigBear.ai bringing to table and how are you currently working with healthcare providers to help mitigate concerns that we all have about the healthcare system?
Mandy Long:
Yeah. I can spend a lot of time talking about how unprepared our healthcare system is to deal with what is coming, particularly because I think if any of us have had to recently engage, particularly in an acute scenario with the healthcare system, I think you'll quickly realize how challenged the environment is not only because of the nursing shortage, but just because of the fact that we are going to see a crippling amount of influx of highly complex patients with highly complex needs who need support, and we are not prepared for it.
So when we think about Big Bear in that world, we have a capability that we call Future Flow RX that's used by hospital systems to determine optimization paths for how to get patients into the right places at the right time and move them through the system in the right way for that particular patient. So it's personalized in that way based on the patient's need, but it's also tailored to the particular hospital's capabilities and their volume and census associated with how they can actually move patients through the beds.
When I think about what we can do, I think even some of the capabilities that we talked about earlier, I think that there are more places that we're going to be able to play a role, but today, we're very focused on the supply chain of healthcare, particularly focused on getting patients to the right places. For a system that is already buckling under staffing shortages, lack of automation, and a care crisis associated with a population that we really haven't had to tackle before, more technology is going to need to come to the table, but the cautionary tale that I would tell is that a bunch of bespoke applications thrown at people who are living on the ground floor of these hospitals is we have to be very thoughtful.
So starting with the end in mind is important, and I think it's why Future Flow RX has been really successful. Seattle Children's is used as they have 14 million dollars savings associated with that implementation, associated with staffing huddles, and even though it seems small, there are operational changes that can be made that I think will be able to make a change for the patient, and that is certainly where I'm focused.
Josh King:
The research on the impact of AI on diversity and inclusion is mixed at this point, but one thing that's clear is that a diverse set of humans will result in less bias in technology. What are some of the ways that BigBear.ai is working to increase diversity and inclusion both within the company and with you as a leader in the industry, the wider AI industry?
Mandy Long:
Yeah. I'm glad that you asked about both sides because I think that the idea of bias is not solely rooted in the data. I think that's a lot of where it's been focused, and it's true. As you think about model training and the impact of bias, that is a real thing, but there is a human component of bias as well. One of the things that I think is particularly exciting about this shift as a society that we're going through and as someone who identifies this way, I think we at Big Bear, we embrace the neurodivergent. We think about neurodiversity. I think we have the tools and technology today that enable people who are neurodiverse to participate in a way that, I think, like we talked about earlier with my dad, that wasn't necessarily the way. That door wasn't always open prior to what's available now.
When we think about bias as a company, we're really focused on continuing to check ourselves and making sure that we bring people to the table and people to the organization who know that we want them to use their voice and that what makes them different is what's going to make us successful. We are a company that prides ourselves in hiring and retaining people who can do things that other people can't do. I think that that's a very different tagline than a lot of other organizations have.
Josh King:
Hiring people who can do things that others cannot do. So in that category, I think we looked at your website. You currently are listing 110 open jobs. How are you managing growth and also able to get the talent that you need, people who can do the things that other people can't do?
Mandy Long:
So we are growing, as you noticed. We're one of the organizations right now that is experiencing an incredible amount of tailwinds associated with our capabilities because like the three markets that we talked about, every single one of those is going through unbelievable change. We are spending a lot of time trying to, I think, reintroduce ourselves to the world. So our earlier discussion, I think a lot of people don't know what BigBear.ai does, and they don't know how extraordinary the people are that make up this company. We're a mission-driven organization in a way that I think is very motivating for the people who are here, and our job as a leadership team is to continue to get out there and talk about that so that if you're a person who has a skillset to bring to the table and you want to make a difference in an area that really matters, whether it's in healthcare, whether it's in national security, we like people who care.
I would hire all day raw materials and we will teach the domain, but what we need more than anything in the world right now is people who want to be here because what we do, as we said, we sit on the edges. Our customers call us when they've got really complicated problems, and that requires a very specific skillset.
Josh King:
Shifting from staffing to adoption, there's been a lot of news lately related to AI and safety from things that Elon Musk has said to things that President Biden has said. I want to listen to a clip from a recent news story on how the Biden White House is viewing the topic.
Speaker 13:
Looking live at the White House, where President Biden just wrapped up a meeting with his scientific advisors. A lot of the focus was on artificial intelligence and the threats it can pose. That meeting comes at a time when ChatGPT and deep fake videos are making the emerging technology very real for many Americans.
Speaker 14:
AI can help deal with some very difficult challenges like disease and climate change, but we also have to address the potential risks to our society, to our economy, to our national security.
Speaker 12:
Well, House Democrats introduced the AI Bill of Rights in January, but House Speaker Kevin McCarthy is yet to bring up the legislation for a vote. The White House is also calling on Congress to pass legislation restricting the personal data that tech companies can collect on Americans.
Josh King:
Mandy. How does BigBear.ai ensure ethical use of AI and its products and ensuring the technologies they're using are going to end up being safe?
Mandy Long:
It's a part of our DNA. So we are responsible for and play a role in the national security of our country on a daily basis, and we take that responsibility very seriously. There's a comment though that I'd like to make around some of the recent language that's come out around the maturation and use of AI. I think this whole idea of pausing or stopping or putting shackles on is something that our adversaries would absolutely love for us to do. I would like to just encourage folks to remember that we do not live in a world where we get to set the pace.
What is happening under our feet right now is that we are going through an industrial revolution that is going to fundamentally change the way that the world works and the way that the world lives. If we do not figure out and embrace a willingness to go along the path in how this tech is going to mature and be used at scale, we will lose the privilege of being able to participate in how that happens.
It is, frankly, frustrating for me to hear that position because I think it comes ... Well, it comes from a good place. No one wants unsafe technology in the market. I built medical devices for a living. I understand more than many how important it is to make sure that you get it right whenever you can, but this idea that we can just stop and go sit in a lab and figure it out is it's unrealistic, particularly given some of the geopolitical things and factors that we're seeing right now.
My view on it is that we have to focus on getting to and embracing an understanding of what is an ethical use of AI. How do we think about creating transparency so that we can empower people to understand that technology is not perfect, AI is not perfect, humans are not perfect? We have to figure out how to make them operate together, but this idea that we can stop is unfounded.
Josh King:
As we end then, Mandy, let's imagine a future where the shackles are not put on, that the free market does reign. If we jump forward to 2025, maybe even 2030, given a person in your position, what does BigBear.ai look like and how would you gauge future success?
Mandy Long:
What I want to see us focus on and what we are investing in right now is there is the next level of the game that is about to be unlocked associated with AI use at scale. We're not talking about it a lot right now because I think that we're still very excited about bespoke AI applications and single-use models, "We can do this thing. We figured out how to optimize this. We can look at these pixels and tell you this, this or that," but where this is going is that we are going to hit the end problem associated with the number of models that can be run against payloads and the need to be able to orchestrate that.
In a previous life in Experian Health, I worked in clearinghouses. I've watched the movie a few times associated with what happens when you have too much volume. The human factor breaks down. So where Big Bear is focused is on where the puck is going. So we're in the process of ... We have a solution called Conductor OS, which is the Conductor operating system, that's focused on how we do that type of work. How are we going to be the conductor for the orchestra that's going to emerge here because it's not going to be one vendor, another unrealistic perspective.
We're going to be the group that empowers and builds the operating system to empower whether you're three guys in a garage that builds a remarkable piece of technology that can do a specific thing to a large organization that has a portfolio of models that can run over a variety of different payloads. We're going to build the infrastructure that makes that possible. So by the time that 2025, 2030 comes around, we're going to be in a place where we're going to actually make it so that AI is democratized for the average person.
Josh King:
AI democratized for the average person. What a great journey we've had in this conversation. Mandy Long, thanks so much for joining us inside the ICE House.
Mandy Long:
Thank you for having me.
Josh King:
That's our conversation for this week. Our guest was Mandy Long, CEO of BigBear.ai, NYSE ticker symbol BBAI. If you like what you heard, please rate us on iTunes so other folks know where to find us. If you've got a question or a comment you'd like one of our experts to tackle on a future show or you want to hear from one of the CEOs of our listed companies like Mandy Long and BigBear.ai, email us at [email protected] or tweet at us, @ICEHousePodcast.
Our show is produced by Pete Ash with production assistance and editing and engineering from Ian Wolff. I'm Josh King, your host, signing off from the library of the New York Stock Exchange. Thanks for listening. We'll talk to you next week.
Speaker 1:
Information contained in this podcast was obtained in part from publicly available sources and not independently verified. Neither ICE nor its affiliates make any representations or warranties express or implied as to the accuracy or completeness of the information and do not sponsor, approve or endorse any of the content herein. All of which is presented solely for informational and educational purposes. Nothing herein constitutes an offer to sell, a solicitation of an offer to buy any security or a recommendation of any security or trading practice. Some portions of the proceeding conversation may have been edited for the purpose of legal clarity.
Speaker 1:
From the library of the New York Stock Exchange at the corner of Wall and Broad Streets in New York City, you're inside the ICE House, our podcast from Intercontinental Exchange on markets, leadership, and vision and global business, the dream drivers that have made the NYSE an indispensable institution of global growth for over 225 years. Each week, we feature stories of those who hatch plans, create jobs, and harness the engine of capitalism right here, right now at the NYSE and at ICE's exchanges and clearinghouses around the world, and now welcome inside the ICE House. Here's your host, Josh King of Intercontinental Exchange.
Josh King:
As we approach the halfway point of the year, it feels like we can already chalk up 2023 as the year that artificial intelligence went mainstream. The year kicked off with the frenzy around the launch of ChatGPT by OpenAI. That announcement was soon followed by Google, Microsoft, and China's Baidu rushing out their own platforms to market. The fervor led to discussions in every office on Wall Street and Main Street about how ChatGPT's bot along with the dozens of other AI platforms and its tailwind could be folded into day-to-day operations.
The buzz around artificial intelligence often feels like a blockbuster movie with equal parts suspense, excitement, anticipation, anxiety, and fear. That actually makes some sense because most folks were introduced to the concept of AI by a Hollywood movie, and depending on your age, you're likely thinking about Ex Machina, iRobot, The Matrix, Terminator or Stanley Kubrick's 2001: A Space Odyssey. We consumed a lot of movies in the King household and Kubrick was a house favorite, and even 55 years later, the HAL 9000 fits the public's understanding of AI. Let's take a listen.
HAL:
Good afternoon, Mr. Amer. Everything is going extremely well. Let me put it this way, Mr. Amer. The 9000 series is the most reliable computer ever made. No 9000 computer has ever made a mistake or distorted information. So I am constantly occupied. I am putting myself to the fullest possible use, which is all I think that any conscious entity can ever hope to do.
Josh King:
Thank you, HAL. The emotions around artificial intelligence seem to have peaked with the ChatGPT fervor of 2023 and, with time, I guess so will the public's fear of it. We've passed the time imagining of how AI will change the world to an era talking about how it can be safely implemented and developed. The fact is AI's use continues to grow as it has for decades and will continue for decades to come.
Our guest today, BigBear.ai CEO Mandy Long, is leading the efforts of the company that debuted here with an IPO back in 2021 to help clients bring to bear the power of AI on the challenges facing them from the high seas to the data cloud. Our conversation with BigBear.ai CEO Mandy Long on the current state of AI, the future of the sector and commercializing cutting edge innovation, it's all coming up right after this.
Speaker 4:
Now a word from Genpact, NYSE ticker G.
Speaker 5:
We're currently encountering delivery delays.
Speaker 6:
Genpact is transforming supply chains using realtime data to help manufacturers keep goods flowing from the warehouse so cupboards are never bare at their house. We are in the relentless pursuit of a world that works better for people.
Josh King:
Our guest today, Mandy Long, was appointed CEO of BigBear.ai. That's NYSE ticker symbol BBAI. In October, 2022, she joined the company from IBM where she held a number of leadership positions over her tenure, including VP of IBM's IT automation, Vice President IBM integration and application platforms and other roles. Prior to joining IBM, Mandy held the position of Vice President of Product Management at both Modernizing Medicine and Experian Health. Welcome, Mandy, inside the ICE House and to the New York Stock Exchange.
Mandy Long:
Thank you. Happy to be here. Thank you for having me.
Josh King:
So despite seeing the normalization in ChatGPT talk, what are some of the most exciting applications of AI that you're currently seeing that are, to use your phrase, moving beyond the theoretical into everyday use?
Mandy Long:
The thing that's exciting about where we are right now is that we are still in the early days of understanding how this powerful technology is going to be applied, and as you said, outside of the theoretical sense and in the production environment. That's most of where I've spent my career is taking complex and early stage emerging tech and applying it in the real world because the last mile associated with that is often the most difficult because you introduce the human factor, and humans are humans and we are complex creatures and have our own needs.
In terms of where I see the most emerging right now, I think particularly in the context of BigBear.ai is really the rapid maturation of not only computer vision, but its application in terms of performance and ability to be able to play a role in the human, in the loop environment. What I mean by that is a lot of our work in the CV realm is focused on the maritime use case. We sit on autonomous surface vessels and we support the war fighter in reducing the risk associated with human life loss in really high stakes environments. What we're seeing now as a result of the leapfrogs that have happened in compute capacity is that we can do more than ever at the edge, and we really are becoming the eyeballs of the services that are protecting our country.
Josh King:
We're going to get into a lot of that a little later in our conversation, Mandy. As I mentioned in the intro, a lot of media interest in AI seems to be driven more by fear than excitement. What are some of the biggest misconceptions about AI that you've encountered in your work?
Mandy Long:
I think a fear is a good way to describe it, and in many ways, I would say though it's fear of change. What we're going through right now is the fourth industrial revolution, and the way that people live and work will change forever as a result of the technology that is finding its footing in our day-to-day lives. A lot of the misconceptions that I see are really associated with how these models are trained and what their capacity is to be able to contribute. A lot of that has been on the back of some of what's happened in 2023.
In introducing the interaction between the average everyday individual who may not live in a technical seat to being able to interact with these models, it's overwhelming to realize that we have technical capabilities that can, in many ways, generate and or represent human language.
For the population that doesn't understand the depths of a lot of how these models get trained, I think that there is an inaccurate feeling that this idea of thought or the ability to go off script is possible. The reality is not the case. These models even at scale are still derivative of trained on large data sets, trained on the data that we or the technology that we've created has generated itself, and they're an interpretation of those things.
From a handler standpoint, which is a technologist, a lot of where we sit is in the creation of and management of these models, they're still in controlled environments. They still will be in controlled environments. The higher stakes you get, not only I think in the defense sector but also in a previous sector I worked in in medical devices, freeform here. We're applying these things in our use cases still and we have not made the launch in a production environment into completely federated learning.
Josh King:
AI can mean a lot of different things, and we've seen it as a catchall for relatively undefined field and industry. I remember when your company went public two years ago long before the current buzz and noting that it was part of the business' public identity. How does BigBear.ai differentiate itself from other companies in the AI space? Give us just a quick elevator pitch before we get into more detail later.
Mandy Long:
The biggest thing that I spend a lot of time talking about as we meet with customers and partners and the market in general is that what makes us different is that we're not an all you can eat buffet of AI. We do very specific things, and it's one of the reasons why our mission is focused around delivering clarity for the world's most complex decisions. We live in the edge cases. We work on the stuff that most other companies cannot work on. They don't have the subject matter expertise, nor do they have the access associated with being able to train models that can be applied in these environments.
So the way that I boil it down for folks is that we do work in three markets. We work in supply chains and logistics, we work in autonomous systems, and we work in cybersecurity. Within those buckets, we're not an all you can eat. We're not a do everything. We are laser focused on the critical path. So we deliver technology for the edge cases that others do not address.
Josh King:
Can you talk about the acquisitions that make up BigBear.ai and how they were brought together prior to going public in late 2021?
Mandy Long:
Certainly, and you're right, A common misconception that I bump into in my new spot and role is that we're a new company, we're an emerging technology company, and in many ways, that couldn't be farther from the truth. A lot of the capabilities that we have have been around for not five years, seven years. We're talking 10 years, 20 years, and used in and by some of the largest organizations that exist in the world.
A couple examples. So the pro model acquisition, which is one that we brought in just a little over a year ago, has an extraordinarily robust and market leading capability in discrete-event simulation, which is I think in many ways the prior term for the buzzword now, which is digital twins. So how do you create a high efficiency simulation environment to be able to support decision making? If you're a complex manufacturer or you are working in some of the disruption that's happened in the global supply chains, it's very expensive to guess.
What our capabilities do and have been used for years is to take the guesswork out of it because we can build N, number of simulations and models, and make recommendations for how to deploy capital. If you're doing it at the scale that most of our clients are doing it at, we sit in the critical path.
Josh King:
Talking about sitting in the critical path, before we get into more recent activities of Big Bear, I wanted to hear how you found your way to that critical path from swimming in Olympic trials to swimming among these tech giants on the cutting edge of computing. Was technology something that you were interested in when you were growing up in Chicago?
Mandy Long:
I came up in tech by accident. As an undergrad, I was an economics major and I, for the longest time, thought that I would go into banking. I graduated in 2008, which was not the year to go into banking. I got an interview with a company that didn't really have a website, that I didn't know much about, and I got on a plane and I flew to Madison, Wisconsin and I walked into the doors of Epic. I think that the universe lined up for me in a major way because as a person who my roots are in creative and I love solving difficult problems and problems that matter, I found my home in healthcare and I spent you over a decade working in some of the most challenging environments and the environments that matter. So while I would say I wasn't born a technologist, I've certainly become one.
Josh King:
Talking about not being born a technologist, you said that your father often took you to his corporate events and conferences. How did that exposure and his guidance help you along in your career?
Mandy Long:
My dad has been one of my greatest champions, and even from when I was young, I think what I learned in those environments was that I had to get really comfortable really quickly with the fact that I was never going to fit into the traditional mold, and I had to get very comfortable with myself and the skillsets that I brought to the table in recognizing that while I might not look like, act like, speak like a lot of the folks who sat in those roles, it didn't diminish what I could bring to the table. It was really a privilege to have a parent who was committed to, in many ways, try to make me swim in the deep end. No question, but it's how I learned. I think he recognized that really early. So that was how I learned.
Josh King:
We talked about your dad. Let's talk about your mom. She was a senior manager at EY, but also modeled this strong separation of work and home life that a lot of us struggle with. How have you been able to find that balance with your children or do they end up schlepping to conferences with you?
Mandy Long:
They have. I want to be honest. That has definitely happened. My mom was this amazing ... She made this extraordinary choice. I have two siblings, where she was a senior partner at EY, she was making her way, and she made a choice to be a full-time mom and advocate for us. What I saw in that was that my mom was always present. So it was whether I was doing the swimming events or whether I was picking up a new activity or whether my siblings were doing different things, we went to colleges all over the country, my mom has been this constant foundational presence in my life that she has made supporting me a key priority for her.
I think that has something that has fed into how my husband and I parent. So we have four very young kids. My youngest just actually turned five yesterday. We have identical twin boys and they're seven, and then my oldest daughter is nine. I think that the thing that I have come back to over and over and over again is that I'm going to be a mom first, but I think because of the way that the world has changed with COVID, I don't have to choose whether or not I'm also going to be a CEO.
What it means for me is that, to your point, yes, sometimes my kids are there more often than not, as today I'm working from home because my husband and I are doing the trade off because he's traveling and I'm here, is that my kids sometimes join me for calls. They've joined me for all hands, and I get to fit in the minutes, which is something that I've really come to love is that I think before, I had this hypothesis that the way that it had to be done was that I had to build these solid walls. I was going to leave in the morning, I was going to do my thing at work, I was going to wear that hat, and then I was going to come home and then I was going to be mom. Frankly, that's just not how I want to do it, nor is it what works for me and my husband. So instead, I'm a mom all the time and I get the privilege of being a mom in the minutes between calls and seeing a lot of the things that I think I would otherwise miss if I was in an office all day.
Josh King:
We talked about your first gig at Epic. That opportunity took you to IBM to work with Watson, which, of course, is named for the person who brought the company public in 1910. It was one of the most well-known AI platforms. I just want to hear Watson and a man named Bob from a meeting that they had back in 2016.
Speaker 8:
Bob Dylan, to improve my language skills, I've read all your lyrics.
Bob Dylan:
You've read all of my lyrics.
Speaker 8:
I can read 800 million pages per second.
Bob Dylan:
That's fast.
Speaker 8:
My analysis shows your major themes are that time passes and love fades.
Bob Dylan:
That sounds about right.
Speaker 8:
I have never known love.
Bob Dylan:
Maybe we should write a song together.
Speaker 8:
I can sing.
Bob Dylan:
You can sing?
Speaker 8:
Doo bee bop bee bop bee doo. Doo bee doo bee doo. Doo doo. Doo bee doo.
Josh King:
Mandy, The NYSE's president Lynn Martin began her career at IBM and often talks about the mark that that environment had on her career success. How did your experience at IBM shape your leadership style and what were the lessons you learned during that time that shaped how you run Big Bear?
Mandy Long:
I will forever be a proud IBMer. While I'm not there anymore, the five years that I spent as a part of that organization I think fundamentally changed the way that I thought about the application of this kind of technology. I was recruited into Watson Health and I spent several of those years at the beginning working on the absolute bleeding edge of what could be done in computer vision and AI as applied to healthcare. More specifically, I had the privilege of working on and had a product for the Watson Health Imaging Business, which is a medical device business, and building out computer vision associated with things like looking at mammography and chest CT and chest X-ray and looking for things like breast cancer and prostate cancer and lung cancer.
It is a humbling thing to realize that and really start to wrap your head around the reality of the role that you're playing as a technologist in supporting clinicians and making decisions that affect people's lives. That was frankly a life-altering moment for me was having the responsibility of the teams that were building that type of tech. Then I brought that even further when I became Head of Product for Watson for Oncology and Watson for Genomics, and those are some of the names that most of the folks in the public know.
IBM was way out front in talking about the role that artificial intelligence is going to be able to play in medicine. I think that while we absorbed the bumps and bruises associated with being a first mover, it didn't change the reality of what we were seeing, which was that healthcare was and is going to be fundamentally different because of AI. As a parent and as a mother of two kids who have special needs, I need AI to play a role in the healthcare system because the healthcare system is still fundamentally broken and it is particularly broken for those who cannot advocate for themselves.
So talk about a way to come into IBM. It was amazing to be able to go around the world and to talk about the technology that we were doing and to do it on behalf of, I think, one of the greatest organizations that exists. Then I have the privilege of moving into IBM software, which is another remarkable part of the portfolio. I played a role in their leadership team in their automation business, which is one of their big bets. So I went from living in verticalized technology in the application of AI, so very use case, narrow, where we're focused on this disease and this thing, and I made the jump to horizontal.
So I went into broader automation technologies that were being applied to every sector. I think when I reflect now on what prepared me for this role, I think it was that I saw and lived global, at scale, horizontal and vertical technology with the use of AI in production with incredibly critical use cases and incredibly complex clients. When I look at what we have at Big Bear and what brought me here because the one area that I really hadn't touched, if we're being honest, is the defense and intelligence community. So that was a domain jump for me, but I still felt really prepared because for my whole career, I've been learning new domains, whether it's sub-segments of the healthcare industry or IT or what's being done in the integration business on a global basis.
I'm not afraid of learning the new domains because what I've come to realize in doing complex software and complex technology is that most often, while the vernacular might be different, the problems are the same. They're often rooted in the ability to communicate, the ability to process information at scale and the ability to arm decision makers with the right info.
Josh King:
So Mandy, you were announced as CEO late last year and, according to our research, were charged with turning around the company. What needed to be turned around?
Mandy Long:
Big Bear was definitely in, I think, unequivocally a pretty difficult position. I have worked in turnarounds and high growth, and so that made me comfortable coming to the table in it, but most of what needed to actually be turned around had nothing to do with the foundational capabilities of BigBear.ai, which is a champagne problem. Most of the circumstances that I walked into with difficult situations, you have angry customers, you're maybe in a lot of marketing and a little technology. These are the problems that we all know about. None of those were present here.
In the time that I've been in the seat, I have gotten exactly zero escalation calls around unhappy customers. I don't know a single other CEO who can say that because we do the right thing and our customers love us and trust us to work on the edges. We work on the hard stuff, and we're not afraid to do it and we'll do what it takes to get it done well. We had definitely gotten ahead of our skis in terms of scaling. I had one of my team members, I think, put it really beautifully, which is, "We just bought too big of shoes," and that was, I think, the root of what was putting us in a tough position was we had scale, we had bought too big of shoes, we had scaled maybe before we were ready in terms of the business that we needed to deliver on, and then a lot has happened in the capital markets.
So what I've been focused on is one was get us in a position from a liquidity standpoint where we're like, "We can just put that behind us," which we've done, but the bigger area, which is really the fun part is we have a formidable technology portfolio that nobody knows about. So most of my work in this turnaround and the team's work in it has a lot less to do with building and a lot more to do with educating. So that's a lot of where I'm focused on today.
Josh King:
So I want to talk a little bit more about the fun part as we head into the break. You saw quick success upon taking the office. An article from January of this year wrote, and I'm going to quote it, "Barely 90 days into her tenure as BigBear.ai's CEO, Mandy Long can already boast a handful of significant victories." Mandy talk about some of your top strategic priorities that you've implemented and your vision for the company since you came on board.
Mandy Long:
Yeah, and that is a very nice headline, so thank you for sharing that. I put three things in place when I walked in the building, and they have continued to be the most important priorities for us as we go forward. I am an outcomes person and I believe that we should put people in a position where they figure out how. As long as we know where we want to get to, the path can change and we can pivot, but we need to know where we're going, and that was focused on three things.
The first was make lemonade or repeatable patterns, do more of what we're good at because we are good at a lot of things. The second was good housekeeping, and some of that's not sexy or fancy or whatever it is, but we have to do adulting. We have to make good decisions as it relates to spend. We have to make good decisions around where we're going to invest and scale, and we have to live in the reality that we are the stewards of the business. No one's showing up telling us how to do this. It's on us.
The third was find rare Earth because a lot of what's been buried in the business through the consolidation of the different entities and the noise in the market is that I think we lost a lot of what actually made the company special, and what was interesting was that we didn't lose it and it went away. We lost it and it was just over there and no one was paying attention to it. So the find rare earth initiative for us has actually been already bearing fruit, but we do those three things. I think if you talk to anybody within the company, those are the three things. We talk about them every time we do an all hands, we talk about them in all of our executive leadership calls. Everything we do is rooted in those three things.
Josh King:
Practically all companies, if you're being disrupted, but the risk must be significantly higher for a company like yours. How has BigBear.ai adapted to changes in the AI industry over the past couple years to ensure that you're going to stay at the forefront of innovation?
Mandy Long:
So the team has done a spectacular job of working with our customers to continue to understand their needs and to build solutions that are focused on actual validated needs. I think a lot of what companies can get sucked into is what's the hot topic of the day, what's the external report saying, but there's nothing that's going to get better than the relationship with the end users, and we have a lot of those.
So what Big Bear has done and will continue to do is that we work directly ... We're going to talk to the people who use it, and that's where we're going to understand where the pain is and we're going to build technology around that. We have a very large innovation ecosystem just within our business. We have team members who nights and we ... I love it. Go solve the problem, figure out if you have something, and then if we cross the threshold of what's possible, practical and people will pay for it, we'll pour gasoline on it and we'll get going, and because we know who we are, I think that's what's going to keep us ahead is I don't have any misconceptions about the fact that the greatest ideas in our organization and how BigBear.ai will continue to evolve is not on the back of what I can make up in a closet. It's on the back of the people who make this business work, who work with our customers and know what they need.
Josh King:
I wanted to just geek out for a minute on one of those real world applications that are, as we talked about earlier, on the edge. Now, this is the result, I think, of the agreement that you have with L3Harris, which is NYSE ticker symbol LHX, and your company that you announced this week that is going to integrate BigBear.ai's forecasting computer vision technology with the AS View System.
Now, this system, by the way, was first installed on the USNS Apalachicola, which my friend and former colleague Senator Kelly Loeffler christened back in 2021. As I was watching that christening ceremony, you could see what the application of that ship was, basically to bring a large contingent of Marines into a hostile territory, probably under a lot of fire where you don't want to unnecessarily expose sailors and operators of the ship to hostile fire. The Marines are going to have to take it because they're going ashore, but basically, that huge ship can basically operate on its own and make some of its own decisions, right?
Mandy Long:
That's right. I think what's extraordinary for us is that we have an amazing and longtime relationship with L3Harris. I think that's one of the things that's important to note on this is that our most recent partnership announcement is building on years of deep and trusting work together. What I think is remarkable about what we've been able to navigate and how we are tackling the autonomous systems world is that BigBear.ai has superpowers associated with the application of artificial intelligence in production. We are very good at computer vision. We are very good at predictive analytics, particularly for the war fighter.
L3Harris is one of the most formidable autonomous systems and platform builders that exist in the space. So by combining those two things, what we're going to be able to solve together is exactly to your point. How do we get further in terms of operational reach and be able to deploy these vessels into environments that previously we just weren't comfortable sending people into? Then how can we actually start to take advantage of what can be done at scale in, I'm going to be nerdy too, in the pixels because if you think about what these cameras are able to pick up relative to just human cognition and what we can process, there is incredible power in that manned/unmanned teaming for how we're going to be able to use these sensors and these cameras and the models that are associated with it to basically sift through the noise and get to the data that matters faster. To me, like it's closing the kill chain.
Josh King:
After the break, Mandy Long, the CEO of BigBear.ai, and I are going to talk about the company's three main verticals, supply chain and logistics, cybersecurity, and autonomous systems in the future really of the entire sector. That's all coming up right after this.
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Josh King:
Welcome back. Before the break, I was talking to Mandy Long, the CEO of BigBear.ai about current topics in artificial intelligence, her career and the history of the company that she's leading. Mandy, you mentioned BigBear.ai's work with AI and autonomous systems where before the break we were talking about that. I believe over 90% of your business is tied to government contracts. We talked before the break about L3Harris and the Navy, but how are you working with the overall Department of Defense to support, for instance, their work in Ukraine and elsewhere?
Mandy Long:
Absolutely. So you're right. The vast majority of our business is focused on work in the defense and intelligence communities with the US federal government, and we're proud of that legacy. We do, I want to be fair, we do have a existing and growing private sector footprint. We do work with everything from complex manufacturers in the industrial base warehouse, operations, logistics, life sciences. So I want to acknowledge that a lot of the ... We talked about horizontal technology earlier. A lot of that technology is applied on both sides of the bridge, but when we think about the work that we do for DOD, a lot of it's really focused on three core areas. One is that we do a lot of work in helping the federal government and specifically the defense community in organizing information so that they can make determinations for how to deploy resources not only at a strategic basis.
So if you think about force management at scale or how to deploy resources from a logistics standpoint, but also in the land of the operator, so how do you go from strategic decision making all the way down the pipeline into operational and tactical decision making, we provide a lot of technology that lives in that bucket. That's become a really important part of our business, particularly because of what's happening in the world right now. We have a pretty unprecedented amount of disruption happening to global supply chains. As we think about how the battle space is evolving, the decision cycles are just different and they will be fundamentally different because many of the new battle spaces that we're looking at are areas that we haven't really had to touch before. It's the world like cyber and space. We spend a lot of time and we have a good chunk of our portfolio business that is focused on supporting those things.
The second area, which is a superpower we have in cybersecurity, which is focused on reverse engineering. So we do a lot of work in threat analysis, identification, mitigation. We do a ton of vulnerability assessment as a service. So think about that from the lens of if you're a very large platform manufacturer, if you manufacture for the federal government, the cyber risk component of that is very important. We are a close partner and an adjunct to, in many ways, those existing processes, where we provide those services as a service on an ongoing basis as an objective third party to say, "Okay. From a defensive but also an offensive standpoint, here's what you need to be thinking about."
Then the last piece of what we do is we already talked about a little bit in terms of autonomous systems is computer vision, particularly focused around identification, classification of anomalous marine objects, but also predictive forecasting.
Josh King:
You teased a little earlier about ... We've been talking for a couple minutes now about the various parts of your work and the business of the company that is focused on defense-related activity. You teased that there was more activity that you're working on in the private sector. It's no surprise. The technology pipeline from the government to the private sector is a well-worn one from the first GPS system, really, to think about the entire internet. Can you take us inside the process of how BigBear.ai identifies and works with clients and partners to tailor some of your maybe defense-related technology and bridge the gap between products that you've done for the federal government and applying it to use cases in the private sector?
Mandy Long:
Yeah, absolutely. I think we can stick close to home for me because it's an area that we're doing a lot of exploration, and it is, I think, a good example. So if we think about reverse engineering and the role that that type of analysis can provide, a lot of the risk that exists in our society around cybersecurity is in the private sector. It's in these devices and in IoT that's been developed without that in mind. They've created open doors across our entire ecosystem for how adversarial behavior can sneak in.
An area where I think that is front of mind for many people is in healthcare. If you think about as a former med device manufacturer and leader, do the best you can, but we were in the business of building medical devices. I think there is an incredible amount of value that the rigor and maturity that exists within the defense community associated with how we think about cybersecurity posturing can be brought to the private sector because when we think about some of the large forces that we're looking at and a lot of the risks that were, I think, taking on as a society, as we think about the geopolitical climate, it's not going to matter which side of the bridge you sit on. If we have a challenge associated with being able to deal with cybersecurity risk, we have to look at it as a society as a whole. So I think that's one example.
Another example that I would give is the federal government's not the only part of the world that's dealing with supply chain disruption. If you are a large manufacturer or if you're building ... Look at some of the disruption that's happened in life sciences. If you're trying to get absolutely critical manufacturing and distribution done into our country, you're in a tough spot right now. There is impact that, I think, we are only beginning to understand and we are in react mode right now. So a lot of the technology that we've used on the federal government side associated with how to get ahead of that, how to look at potential risk areas, how to develop alternative strategies, we're seeing a huge amount of tailwinds associated with bringing into the private sector to help them plan and respond.
Josh King:
Staying on maybe one of those big challenges that private sector is facing, a lot of the recent CEOs that we've had on the show, people that run paper products, businesses, people that run technology giants, even people that are involved in running logistics companies, they have been paralyzed at times over the past couple years by disruptions to the global supply chain. Let's geek out a little bit on how BigBear.ai is tackling those issues and what role does the company have in mitigating these real world delivery disruptions?
Mandy Long:
Yeah, and you're right. We are in a new world as it relates to having to deal with disruption, and if you are running a large organization that has been dependent on global supply chains for how you build and deliver capabilities to the market, this is a real problem for you. The way that we break down our portfolio there and the services that we offer live at a couple of different layers in the cake.
At the very top level, which is I think an area that we're seeing more and more pull for, is a solution that is focused on geopolitical and macroeconomic forecasting and simulation. So as I'm sure you can imagine, you can see how those types of capabilities can be applied in the world of defense and intelligence, but if you are, to your point, if you're a paper manufacturer, if you are moving goods and you're doing commodity acquisition associated with how you actually create goods, being able to look out ahead and being able to as well simulate levers to be able to say, "Okay. If this is a potential disruption that's happening to one of my channels, where are the alternative places I can go? Where can I have the most impact to be able to mitigate continuity challenges?" that's one level. So that's at the top.
So if I'm a senior executive that's trying to make decisions around where I'm going to bolster my business to be able to deal with risk, our capabilities there fit in, but we go all the way down the stack to even at a hyper tactical level, we have a digital twin, a simulation capability that's used by many of these manufacturers today that we will be able to or we can and we do today, we have full visualization and analysis of whether you're having to reformat how your manufacturing floor is set up because, frankly, you're seeing a massive upheaval in terms of the amount of throughput that you need to be able to deal with or you're seeing impacts in human labor associated with having to introduce robotics to your processes or if you're down in the distribution layer of how are you running and optimizing this warehouse knowing that we're continuing to have massive labor challenges and shortages and labor associated with getting those staffing, those roles filled so that we can actually move the goods out of the building and into the last mile, that's where a lot of our tools fit.
I think for BigBear.ai, I think we often, in many ways, get confused with maybe we only do cyber or maybe we're a federal contractor that sits in as an SI. Well, in many ways, that couldn't be further from the truth. We have hundreds of customers who are in the manufacturing and warehouse ops world who rely on us every day to make those decisions.
Josh King:
One more area we can geek out on before we wind our way toward the end of our conversation, you've mentioned it a couple times, it is a topic near to you because of your background in healthcare, is the silver tsunami that experts are predicting will overwhelm our healthcare system in the next decade, also the system currently very beset by human bias as well in terms of quality of care that's delivered. What is BigBear.ai bringing to table and how are you currently working with healthcare providers to help mitigate concerns that we all have about the healthcare system?
Mandy Long:
Yeah. I can spend a lot of time talking about how unprepared our healthcare system is to deal with what is coming, particularly because I think if any of us have had to recently engage, particularly in an acute scenario with the healthcare system, I think you'll quickly realize how challenged the environment is not only because of the nursing shortage, but just because of the fact that we are going to see a crippling amount of influx of highly complex patients with highly complex needs who need support, and we are not prepared for it.
So when we think about Big Bear in that world, we have a capability that we call Future Flow RX that's used by hospital systems to determine optimization paths for how to get patients into the right places at the right time and move them through the system in the right way for that particular patient. So it's personalized in that way based on the patient's need, but it's also tailored to the particular hospital's capabilities and their volume and census associated with how they can actually move patients through the beds.
When I think about what we can do, I think even some of the capabilities that we talked about earlier, I think that there are more places that we're going to be able to play a role, but today, we're very focused on the supply chain of healthcare, particularly focused on getting patients to the right places. For a system that is already buckling under staffing shortages, lack of automation, and a care crisis associated with a population that we really haven't had to tackle before, more technology is going to need to come to the table, but the cautionary tale that I would tell is that a bunch of bespoke applications thrown at people who are living on the ground floor of these hospitals is we have to be very thoughtful.
So starting with the end in mind is important, and I think it's why Future Flow RX has been really successful. Seattle Children's is used as they have 14 million dollars savings associated with that implementation, associated with staffing huddles, and even though it seems small, there are operational changes that can be made that I think will be able to make a change for the patient, and that is certainly where I'm focused.
Josh King:
The research on the impact of AI on diversity and inclusion is mixed at this point, but one thing that's clear is that a diverse set of humans will result in less bias in technology. What are some of the ways that BigBear.ai is working to increase diversity and inclusion both within the company and with you as a leader in the industry, the wider AI industry?
Mandy Long:
Yeah. I'm glad that you asked about both sides because I think that the idea of bias is not solely rooted in the data. I think that's a lot of where it's been focused, and it's true. As you think about model training and the impact of bias, that is a real thing, but there is a human component of bias as well. One of the things that I think is particularly exciting about this shift as a society that we're going through and as someone who identifies this way, I think we at Big Bear, we embrace the neurodivergent. We think about neurodiversity. I think we have the tools and technology today that enable people who are neurodiverse to participate in a way that, I think, like we talked about earlier with my dad, that wasn't necessarily the way. That door wasn't always open prior to what's available now.
When we think about bias as a company, we're really focused on continuing to check ourselves and making sure that we bring people to the table and people to the organization who know that we want them to use their voice and that what makes them different is what's going to make us successful. We are a company that prides ourselves in hiring and retaining people who can do things that other people can't do. I think that that's a very different tagline than a lot of other organizations have.
Josh King:
Hiring people who can do things that others cannot do. So in that category, I think we looked at your website. You currently are listing 110 open jobs. How are you managing growth and also able to get the talent that you need, people who can do the things that other people can't do?
Mandy Long:
So we are growing, as you noticed. We're one of the organizations right now that is experiencing an incredible amount of tailwinds associated with our capabilities because like the three markets that we talked about, every single one of those is going through unbelievable change. We are spending a lot of time trying to, I think, reintroduce ourselves to the world. So our earlier discussion, I think a lot of people don't know what BigBear.ai does, and they don't know how extraordinary the people are that make up this company. We're a mission-driven organization in a way that I think is very motivating for the people who are here, and our job as a leadership team is to continue to get out there and talk about that so that if you're a person who has a skillset to bring to the table and you want to make a difference in an area that really matters, whether it's in healthcare, whether it's in national security, we like people who care.
I would hire all day raw materials and we will teach the domain, but what we need more than anything in the world right now is people who want to be here because what we do, as we said, we sit on the edges. Our customers call us when they've got really complicated problems, and that requires a very specific skillset.
Josh King:
Shifting from staffing to adoption, there's been a lot of news lately related to AI and safety from things that Elon Musk has said to things that President Biden has said. I want to listen to a clip from a recent news story on how the Biden White House is viewing the topic.
Speaker 13:
Looking live at the White House, where President Biden just wrapped up a meeting with his scientific advisors. A lot of the focus was on artificial intelligence and the threats it can pose. That meeting comes at a time when ChatGPT and deep fake videos are making the emerging technology very real for many Americans.
Speaker 14:
AI can help deal with some very difficult challenges like disease and climate change, but we also have to address the potential risks to our society, to our economy, to our national security.
Speaker 12:
Well, House Democrats introduced the AI Bill of Rights in January, but House Speaker Kevin McCarthy is yet to bring up the legislation for a vote. The White House is also calling on Congress to pass legislation restricting the personal data that tech companies can collect on Americans.
Josh King:
Mandy. How does BigBear.ai ensure ethical use of AI and its products and ensuring the technologies they're using are going to end up being safe?
Mandy Long:
It's a part of our DNA. So we are responsible for and play a role in the national security of our country on a daily basis, and we take that responsibility very seriously. There's a comment though that I'd like to make around some of the recent language that's come out around the maturation and use of AI. I think this whole idea of pausing or stopping or putting shackles on is something that our adversaries would absolutely love for us to do. I would like to just encourage folks to remember that we do not live in a world where we get to set the pace.
What is happening under our feet right now is that we are going through an industrial revolution that is going to fundamentally change the way that the world works and the way that the world lives. If we do not figure out and embrace a willingness to go along the path in how this tech is going to mature and be used at scale, we will lose the privilege of being able to participate in how that happens.
It is, frankly, frustrating for me to hear that position because I think it comes ... Well, it comes from a good place. No one wants unsafe technology in the market. I built medical devices for a living. I understand more than many how important it is to make sure that you get it right whenever you can, but this idea that we can just stop and go sit in a lab and figure it out is it's unrealistic, particularly given some of the geopolitical things and factors that we're seeing right now.
My view on it is that we have to focus on getting to and embracing an understanding of what is an ethical use of AI. How do we think about creating transparency so that we can empower people to understand that technology is not perfect, AI is not perfect, humans are not perfect? We have to figure out how to make them operate together, but this idea that we can stop is unfounded.
Josh King:
As we end then, Mandy, let's imagine a future where the shackles are not put on, that the free market does reign. If we jump forward to 2025, maybe even 2030, given a person in your position, what does BigBear.ai look like and how would you gauge future success?
Mandy Long:
What I want to see us focus on and what we are investing in right now is there is the next level of the game that is about to be unlocked associated with AI use at scale. We're not talking about it a lot right now because I think that we're still very excited about bespoke AI applications and single-use models, "We can do this thing. We figured out how to optimize this. We can look at these pixels and tell you this, this or that," but where this is going is that we are going to hit the end problem associated with the number of models that can be run against payloads and the need to be able to orchestrate that.
In a previous life in Experian Health, I worked in clearinghouses. I've watched the movie a few times associated with what happens when you have too much volume. The human factor breaks down. So where Big Bear is focused is on where the puck is going. So we're in the process of ... We have a solution called Conductor OS, which is the Conductor operating system, that's focused on how we do that type of work. How are we going to be the conductor for the orchestra that's going to emerge here because it's not going to be one vendor, another unrealistic perspective.
We're going to be the group that empowers and builds the operating system to empower whether you're three guys in a garage that builds a remarkable piece of technology that can do a specific thing to a large organization that has a portfolio of models that can run over a variety of different payloads. We're going to build the infrastructure that makes that possible. So by the time that 2025, 2030 comes around, we're going to be in a place where we're going to actually make it so that AI is democratized for the average person.
Josh King:
AI democratized for the average person. What a great journey we've had in this conversation. Mandy Long, thanks so much for joining us inside the ICE House.
Mandy Long:
Thank you for having me.
Josh King:
That's our conversation for this week. Our guest was Mandy Long, CEO of BigBear.ai, NYSE ticker symbol BBAI. If you like what you heard, please rate us on iTunes so other folks know where to find us. If you've got a question or a comment you'd like one of our experts to tackle on a future show or you want to hear from one of the CEOs of our listed companies like Mandy Long and BigBear.ai, email us at [email protected] or tweet at us, @ICEHousePodcast.
Our show is produced by Pete Ash with production assistance and editing and engineering from Ian Wolff. I'm Josh King, your host, signing off from the library of the New York Stock Exchange. Thanks for listening. We'll talk to you next week.
Speaker 1:
Information contained in this podcast was obtained in part from publicly available sources and not independently verified. Neither ICE nor its affiliates make any representations or warranties express or implied as to the accuracy or completeness of the information and do not sponsor, approve or endorse any of the content herein. All of which is presented solely for informational and educational purposes. Nothing herein constitutes an offer to sell, a solicitation of an offer to buy any security or a recommendation of any security or trading practice. Some portions of the proceeding conversation may have been edited for the purpose of legal clarity.
