Ep. 8: Analytics Ventures CEO Navid Alipour on How Leaders Should be Thinking about AI
In this episode, Darren Reinke chats with Navid Alipour, co-founder and managing partner of Analytics Ventures. Navid talks about how AI is taking on breast cancer, his journey from a political science major to co-founding a venture capital company focused on artificial intelligence, how leaders should be thinking about AI, and how AI can drive humanity forward.
Analytics Ventures is a Venture Formation Fund focusing on artificial intelligence, deep learning, and the Internet of Things. Analytics Ventures creates and funds brand new companies in the fastest growing area of technology.
Powered by RedCircle
Listen and Leave a Review/Rating on Any of the Following Platforms
SHOW NOTES
Navid’s Career in Artificial Intelligence (AI) Without a Data Background (1:15)
How Navid’s AI Portfolio Companies Benefit Consumers (4:18)
How Artificial Intelligence Empowers Humans (6:52)
How AI Frees Us From the Jobs We Don’t Want To do (9:55)
The Three Components Fueling the Growth of AI (12:49)
How to Think About AI as a Leader (14:15)
How to Apply AI Within Your Business Without a Data Background (17:57)
Overcoming the Challenges That Come With Adopting AI (20:50)
How to Successfully Implement AI Within Your Organization (22:57)
Training Artificial Intelligence to Make Ethical Decisions (23:48)
The Role of the Human in AI (26:20)
Understanding Why AI by Itself is Not Good or Evil (26:40)
How Navid Manages Being the CEO of Two Portfolio Companies (28:33)
Navid’s Biggest Lessons Learned From Being CEO (32:33)
Navid’s Advice for Leaders (35:15)
SHOW LINKS
If you enjoyed this podcast, please subscribe, rate, or provide a review on Apple Podcasts, Spotify, or Google Podcasts. It only takes a few seconds and would be greatly appreciated!
For additional leadership tips, be sure to check out Darren's book - The Savage Leader: 13 Principles to Become a Better Leader from the Inside Out.
PODCAST TRANSCRIPT
Darren Reinke: Welcome to The Savage Leader Podcast, where I interview leaders from all walks of life so that you can walk away with tips to apply to your life and your career. But this isn't your traditional leadership podcast because I believe that leadership tips come from successful entrepreneurs and business executives, of course. Still, they also come from unexpected places, like Navy SEALs, successful professional athletes, sports coaches, musicians, entertainers, and more. So let's dive right into today's episode; my hope is you walk away with something tangible that you can apply immediately to your life in your career. Today's guest is Navid Alipour. Navid is the founder and managing director of Analytics Ventures, which is a venture formation fund focusing on artificial intelligence, deep learning, and the Internet of Things. Navid is also the CEO of cure metrics, which is a global leader in artificial intelligence for medical imaging, committed to the advancement of technology that improves cancer survival rates worldwide. Navid, thanks for coming on today.
Navid Alipour: Thank you, Darren, thanks for having me.
NAVID’S CAREER IN ARTIFICIAL INTELLIGENCE (AI) WITHOUT A DATA BACKGROUND (1:15)
Darren Reinke: So, your story's an interesting one, how did you get involved in AI as someone who studied political science, economics, Middle Eastern history, but also have your JD MBA?
Navid Alipour: Yeah, so I didn't even know what venture capital was in college back in the late 90s. To be honest, so you know, after you know, finishing undergrad at UCSD, like you said, you know, PolSci econ background, so I'm not technical, I don't code. I'm not a data scientist. And from there, I went on to grab school wanted to stay in San Diego went to USC, did my law, my MBA there. And I want the finance route for about 10 years of your traditional firms, your Merrill Lynch's with Barney's of the world and long the short of it is I always wanted to start my own business and become fascinated with startups and had kind of immersed myself in the San Diego venture group and other organizations in town that, you know, work with startups in different capacities. And so, I started putting my money where my mouth is, making some angel investments in startups. And in this process, met one of my partners, Blaise Barrelet. He's a freshman who came here in his early 20s. I had a very successful, one of the most successful SEO companies. In fact, website’s story, he was one of the few internet companies in the late 90s, and made money from day one, and then ultimately IPO and got acquired by Adobe. So, Blaise and I were introduced by a mutual friend, we complemented each other while he is technical. And so, he said, Hey, you know, why don't we do this full time, instead of just investing in startups on the side? Let's do something. And it's all about Navid and Blaise. So, we ended up starting analytics ventures. And about a year into this venture, we were approached by some scientists out of UCSD and a lot of people don't know UCSD is one of the epicenters of artificial intelligence, dating back to the very beginning of the university. And so, you know, they had heard about us and our focus and our emphasis on software. And so, they came to us and said, Look, AI machine learning will impact us and change the world. And you know, some would argue more than more ways than the internet itself has. And anywhere that you could make a prediction or a recommendation of forecasts or detect something that does not belong. Using AI and machine learning. One can increase revenues, decrease costs by bringing operational efficiencies or in the healthcare sense, like your metrics, by detecting breast cancer earlier, we all know that prolongs life and saves lives, right. And so, that's where I'm particularly most proud of our health care companies. But that's really how we got into AI is a bit of, you know, luck meeting opportunity, we were in the right place. And we ended up seeing that when we really got into it about six years ago. Again, the term AI is not new. It's been around since the late 50s. But we realized that this is going to change our lives and that we're at a cornerstone in history. And so, we decided to laser focus, and say we are, you know, an AI-focused venture fund, irrespective of what industry.
Darren Reinke: Yes, definitely so much potential and seeing some of those early applications of AI. He talked a little bit about your portfolio companies and what they're doing with AI to benefit consumers broadly.
HOW NAVID’S AI PORTFOLIO COMPANIES Benefit Consumers (4:18)
Navid Alipour: Sure. I mean, on the healthcare front, of course, as I mentioned, cure metrics, which I am wearing the CEO hat on, and we talk about that later and how that happened. But a cure metrics. We have FDA clearance, the first of its kind, it's just software, but because it's a diagnostic for the FDA, we have to get that clearance, that seal of approval, call it and to sell the software, and we detect breast cancer better than any other technology in the world. We are the best AI medical technology in detecting breast cancer currently. And so, that's huge right with regard to how it impacts the Patient if you want to say a consumer is the doctor, the doctor is by the software. But that's, you know, one example of how AI impacts lives by, in that example of detecting cancer and mammograms better and faster and more accurately. And then on the FinTech side, we have alpha trai, which we applied our we literally built that internally 100%, we didn't have outside co-founders. And so, we've kind have been out of for about three and a half years and are applying AI and machine learning to the stock market. So, where our healthcare companies, you know, we feel good their social impact, alpha trai is just about pure greed and capitalism just about making more money by detecting signals in the markets. And so, we have now spun off a hedge fund, the alpha trai domestic performance fund, and brought the former president of LPL build wire, who's one of our investors is jumped in full time to be the managing partner of the hedge fund, since he comes from that world. And so, the hedge fund is the first product, but we are looking to bring this technology to the consumers in other vehicles, be it ETFs, or it's at some point of self-directed or self-guided, called the next Vanguard. We feel that, you know, Wall Street is very overpaid. So, you have a lot of financial advisors and mutual fund managers, and we feel that a lot of those fees take away from the retail mom-and-pop investors, as we all know, compound interest, if you can reduce those fees, you know, you'll have a lot more retirement. So, our goal was to bring more efficiency to the markets there for the consumer.
HOW ARTIFICIAL INTELLIGENCE EMPOWERS HUMANS (6:52)
Darren Reinke: Okay, you mentioned something interesting, I think a lot of people's misconception is that AI is just the machines taking over. And he talked about how within the situation with cure metrics, and it's really complementing the work that the radiologist is doing. Can you talk a little bit about that partnership?
Navid Alipour: Yeah, no, I'm glad you brought that up. So, there's a saying I like where it says, you know, is the human in the loop, on the loop, or outside the loop? The human is in the loop, the human is absolutely essential. And there is no AI machine learning, right? It’s just if the human is doing their job, whatever that is, be it real estate, be it law, be it in the healthcare vertical. When the human is in the loop, it means there is automation, there is machine learning, but the human oversees it, right. And then if the human is outside the loop, the human is not needed at all. So, you could say when we get to self-driving vehicles, the human in many ways is outside the loop, right? If we're gonna have drones delivering food and medicine and other things, there's no human involved or anything you automated and pieces of machinery where there's no human, they're completely fully outside the loop. But in healthcare, human needs to be in the loop, they need to be involved. So, AI is not going to replace the radiologist and the cure metric, for example, but the radiologists using AI will replace radiologists that's not, so AI is a tool to empower the doctors to deliver better care for their patients, empower them to work more efficiently and deliver better care by detecting cancer, better reducing false positives and false negatives. So, you know, that's wherein the healthcare world specifically, if there's bad news to be delivered, you know, you don't want to get an AI chatbot telling you, you have cancer, you know, you want a human doctor to, you know, put their arm around you or pat you on the back and say, hey, it's gonna be okay. There are things to do you need that human element. And so all the talk about the robots are the machines taking over? You know, I think that's a little premature, frankly.
Darren Reinke: Now, I think that's an interesting distinction in highlighting that partnership, I think there are a lot of opportunities for companies not just to replace, but to use AI as a complementary tool to develop businesses.
Navid Alipour: Absolutely. And, you know, something else to note is, there are a lot of jobs that people don't want to do anymore. For example, you know, offshore oil rigs, you know, they have certain GE equipment, for example, that if you know, to get that thing fixed, there are fewer and fewer and fewer people that know how to fix that machine. Because our generation and those younger, they don't want those type of jobs. And so, this expertise is going away, frankly, to fix certain machines.
HOW AI FREES US FROM THE JOBS WE DON’T WANT TO DO (9:55)
Navid Alipour: And so, that's where AI and machine learning can come into play, to learn, you know, the skill set, frankly, to fix that machine and to maintain it before it breaks down. In Japan, another example, the people who fix the rail lines and the train systems, they're saying that they're having less and less people with that expertise. So, before the expertise dies off, they're actually training robots and machines to maintain better and to fix equipment. So, it becomes to the point where they're jobs that we don't want to do. So, that's where AI will be a tool to free us to be more creative to work on other things to, again, to not sound, you know, cheesy about it, but to take our civilization to a higher level by allowing us to focus on new ventures and new creative means.
Darren Reinke: And I think it's important is to highlight some of the positive applications in seems like most people, at least in the media are worried about the negative implications of it.
Navid Alipour: Big look, negative news sells better, right? Whether it's about Elon Musk going on and saying the robots are gonna take over. And again, I'm a huge admirer of his, but you know, he's, uh, he's not a public company, and he needs to be on the news. And that stuff sells, it gets attention, right? The stock market drops 500 points today, it's on, you know, RK USI local news. And everyone knows about it. But if it goes up 500 points, people don't necessarily talk about it. So, bad news just sells better? Yeah, absolutely.
Darren Reinke: So you're in a unique situation, you look at a lot of companies, a lot of technologies. What are you most excited about looking forward? And what are some of the big opportunities around artificial intelligence.
Navid Alipour: So you know, I'm a glass half full type of guy. I know, we're in unusual times here in 2020, a lot of tension at a national level at a geopolitical level. And, you know, just there's a lot of just agitation out there in the world, in a lot of doom and gloom. And, and I'm just not like that. I mean, we're so fortunate to be living in the time we are, and the innovations that are being made across all fields, AI, of course, included. But you know, with life science, and, you know, medicine and transportation and clean energy, and there's so much happening, that I think historians are really going to look back on the 2020s is a pivotal decade.
THE THREE COMPONENTS FUELING THE GROWTH OF AI (12:49)
Navid Alipour: And artificial intelligence will touch every aspect of that, by the way, from the industrial to the clean tech to the healthcare, to the insurance, industry, finance, agriculture is there's gonna be, you know, billions more people on less arable land, we need to be more efficient and growing food to feed the world. And so, AI is going to play a role in that, whether it's you know, the company that was able to buy image recognition, detect weeds better, and deer bought them for $300 million, by the way, and all they did is detect weeds better, so that deer can put that on their tractor and say, hey, buy our tractor, instead of, you know, Caterpillar is because by helping you detect the weeds better, you'll save money on spraying chemicals. And that's also less toxic, right. And so, AI is touching everything. And really three reasons that the time is now, it comes down to more powerful computers, one to the cloud. Now a company like cure metrics, we could never build cure metrics 10 years ago, or before the cloud because we'd have to buy our own data centers. So okay, let me take that I would not we could never do it, it will cost much, much, much, much more to develop what we do, but we're 100% on Amazon's cloud. And so, we can get 10 million mammograms tomorrow and process them. Right? We don't need our own data center. So, that's amazing. That is an amazing fact. So more powerful computers, the cloud and more data, right because of Internet of Things, whether the cell phones were all carrying, or the Tesla's, you know, cars are essentially becoming IoT devices, Internet of Things devices, you plug in your car at night, it's getting its software updated, to our Fitbits, and pacemakers and sleep apnea machines, everything is connected to the internet. And everything is generating data. Well, data is useless unless you can get value out of that, right. And so, that's what AI does, but because there's data because there's more powerful computers, and because we have a cloud to process that data cheaper, the algorithms learn. So, that's then machine learning where you feed it more data, and it learns, and it becomes better. And we couldn't do that if we did not have this alignment of these three forces.
How to Think About AI as a Leader (14:15)
Darren Reinke: What about from a leadership perspective? What are some of the opportunities that leaders should be aware of as about how to think about and potentially even apply AI within their companies?
Navid Alipour: Fantastic questions. So, when I talk at panels, or to students, you know, at colleges or any other venue, whether it's for real estate professionals, or lawyers, or CPAs, or engineers, I always say you don't have to be a data scientist to understand the benefits of AI. Right? We all use Excel. We know how to use it. We didn't have to develop it, right? We didn't have to develop the software. And so, AI is another tool to empower us to do our jobs better and more efficient. Simply. And so from a leadership level, a CEO, a board, senior execs that have control over a company's direction, be it small, or be it a fortune 100 company. If they don't start thinking of how to apply AI to their business, their competitors will eat their lunch. And they'll go the way of the dinosaurs or to bring it right home to businesses, they'll go the way of a Blockbuster Video, or, you know, Barnes and Noble, where they didn't adapt. So, leaders have to look at this now and say, How can we be competitive by using AI to squeeze efficiencies from our manufacturing facilities to advertise better to the right consumers at the right time to increase our sales to, let's say, a real estate example to make sure we optimize the rents that are commercial property by getting the right tenants in there if you San Diego's I think the smartest city, or it's got the smart grid, right? Where all the lights are, you know, there's everything smart. And there are cameras everywhere. And so if you could tap into that data, which is publicly available, and let's say you, you have a building, and whether you're the owner, you're the commercial real estate broker, you want to get the best tenants in there. So if the camera is showing Mercedes and BMWs, and Ferraris and Porsches driving by, and if you have the demographic information about how college-educated people are, or how, you know, level of education they have in degrees, and PhDs and so forth, then you say, Okay, let's put up more than Steakhouse in there, instead of a Fridays or a Denny's, right? Let's put a high-end gym in there instead of a 24-Hour Fitness. And then it is true. Also, if you have that information that you know, like look, the cameras recognizing, again, not knocking on Toyota Corollas or, or smaller cars that are not Porsches or BMWs. But let's say it's recognizing less expensive cars, the demographic information shows more blue collar versus white collar, then you need to not put in a more in a steakhouse or high-end gym, but 711 and, you know, 24-hour fitness and, and so this is a good example, in the real estate vertical, where leaders need to recognize how they could use these tools to win that business, right? If you're that commercial real estate broker to optimize the rents for your building, if you're a pension fund or a REIT, so that your building's value goes up because of optimizing those rents. So, that's wherein any industry again, if you can make a prediction or recommendation or forecasts or detect something that does not belong in the data set, you can increase revenues or decrease costs. And at the end of the day, that's what it's all about in business.
HOW TO APPLY AI WITHIN YOUR BUSINESS WITHOUT A DATA BACKGROUND (17:57)
Darren Reinke: It can be a tall task for leaders unless they perhaps have a very experienced, knowledgeable Chief Technology Officer. How can leaders of companies or leaders within an organization get started in thinking about opportunities for AI?
Navid Alipour: So, that's a key point because the statistic out there was a few years ago, but it was a New York Times article that said there are only 10,000 real data scientists globally in the world. So, there aren't that many data scientists. And there's a complaint that as people are going through their masters and PhDs to, you know, go the whole nine yards to become these esteemed PhD data scientists, the Google's Amazons, and Facebook's of the world, are snapping these people up before they finish their PhD. And it's limiting who's left in academia to train the future generations, right. So, there is a critical issue with the not having enough scientists. So, that's whereas a leader of a company, again, we saw an opportunity here. So, we created a company in AI as a service company called dynam.ai. That's dynam.ai. And it was for that very purpose because we realized there's a huge vacuum in corporate America because these data scientists are really good ones. They don't want to work for just one company. They don't want to go home to their spouse at the end of the day. And say I work with Coca-Cola, a soda manufacturer, or Johnson and Johnson or pharma medical device company, or Harley-Davidson, a motorcycle company or ExxonMobil. And so, that doesn't excite them to say they work at one company working on one product, one thing, but all those companies need data scientists. And so, that's where we built our own AI Lab. That's Dynam AI. And so, companies public fortune 100 companies on down from the resumes of the world to Boston Consulting Group to Titleist the golf company, have hired us to leverage our AI bench. And so, that's where it's up to a leader, a CEO of management Board of the team, or company to decide, do we wanna go find the best outside and bring them in to develop for us what we need, and let's focus on being that medical device company. And that's our core efficiency, or do we want to try to do it in house? Now, it's not that it can't be done in house, but it would be a massive, massive investment in time and money. And if you don't have the right person at the top, but as a data scientist level, it might be 18 months later, until you realize that you got the wrong team. Because a lot of people are slapping AI and machine learning on their resumes and CVs and LinkedIn. And they're very smart people. But they're using a glorified business intelligence, they're not really data scientists that are machine learning experts. So, that's what senior execs in the leadership team needs to be very cautious of.
OVERCOMING THE CHALLENGES THAT COME WITH ADOPTING AI (20:50)
Darren Reinke: That's great advice, and what about flipping it around? What are some challenges leaders might be facing? And how can they overcome them in terms of adopting artificial intelligence, the biggest challenge is having good clean structured data?
Navid Alipour: So, you have to start there, if you don't have good data, it's garbage in, garbage out, right. You can't train the algorithms to do something if you don't have the data collected in a structured manner, right? If you're a hospital, and you know, you have one person's age, but not the others, you have, you know, one person's weight, but not the other or zipcode as in, you know, demographic areas to detect, let's say if there's a flu epidemic in a certain area that you want to be able to detect or COVID, right, things like that. So, you have to collect data in a clean, organized, structured manner. And you know, cure metrics, for example, the mammograms, we have to clean the data. So, they all look the same in regard to the markers, right? And analyze the personal health info, the PHI, and then the machine learnings can learn from it because you feed it to them. And it looks the same way. And so, there's the saying that data is the 21st century's oil. Well, we could be sitting on, you know, a company could be the next Saudi Arabian oil or better example, Venezuela, Venezuela has more oil than Saudi Arabia, but they can't get it out of the damn ground. Because of their politics and a host of other reasons, the country's falling apart. So, it's useless oil just sitting in the ground. So, data is the same way, you could sit it on be sitting on a mountain of it a goldmine. And if you can't get it out of the ground, refine it, and turn it into gasoline, it's useless. So, I like to say that the refinery is the AI Lab, the data scientists, right? So, we've built the lab, we have the refinery, and we look to find partners that have the data, we say, hey, let's get that out of the ground. And let's get value out of that data. Let's create value out of that data by helping apply machine learning to detect and automate and predict, which will therefore then help that respective business.
HOW TO SUCCESSFULLY IMPLEMENT AI WITHIN YOUR ORGANIZATION (22:57)
Darren Reinke: Those are great examples of a leader should be thinking about both opportunity-wise and challenges. What about from an organizational perspective? What are companies going to need to do to change to adapt to integrating AI?
Navid Alipour: I think the time has come where there really needs to be a chief AI officer, really, I get the senior exec level, you need one person dedicated. And they don't need to be the data scientists. But they need to be the person who is steering that business from a strategic level, to look at every piece of that company's business and processes and say, can we automate? Can we apply machine learning? Can we make predictions here that'll help? Can we make forecasts? Can we detect failure in a machine before it happens?
TRAINING ARTIFICIAL INTELLIGENCE TO MAKE ETHICAL DECISIONS (23:48)
Navid Alipour: And so, there need to be not only a chief AI officers, I feel strongly at companies, but there's even now PhDs in AI ethics. So if you're building driverless cars, or if you're building robots, you have to train those machines to make decisions. And so, the knowledge I might have shared with you in the past, but if I'm driving in my car and my daughter in the passenger seat, and there's, you know, a car in front of me a car behind me, pedestrians to my left, or bikers and semi-truck is hurtling at me from the other end that if it hits the car, it's gonna vary and all likely to kill my passenger, my daughter and myself, human response, there's severe the car, you know where it's not. So, that could be veering into the pedestrians that could be slamming on the brake and having another car hit you or, or accelerating and hitting the car in front. That's what a human would do. But if you're training the cars, AI system, the brains, what do you do there? Because if it veers into the people, now your Ford Motor Company, your Toyota, and your car just drove and killed three pedestrians, and yes, it saved the two people in the car. But how does To decide that, how does it decide? Does it save the people in the car or the pedestrians? Because if it doesn't do anything, the owners of the car will end up suing Ford or Toyota. Right? So, it's a tough question. It's an ethical question, as to how do we train the robots to, you know, what do they do. And this goes hearkens back to, you know, I just thought of the iRobot movie with Will Smith and 20 plus years ago, where, you know, the robot saw two cars go over and chose to save the character Will Smith plays instead of the eight-year-old girl that died because it detected that the percentage likelihood of him surviving is higher than the girl, whereas a human would have gone for the child, right? The human goat, a human who's trying to rescue in that situation, you rescue the child first. And so, again, that's a movie, but science fiction becomes reality. And so, companies will increasingly need to have folks trained in AI ethics, as they're building their machines, good robots, cars, or other internet of thing devices.
Darren Reinke: So, when we look back a few years from now, it seems like the technology part will be the easy part, the challenging part will be how do we solve that ethical problem? And who makes those decisions?
THE ROLE OF THE HUMAN IN AI (26:20)
Navid Alipour: Absolutely. Darren, you're 100%. Correct. And that, and again, these are going to be questions and decisions that need to be made for the next foreseeable future, the next 100 years. And that's to the very point why the human has to be in the loop, the human is not going away, the robots are not taking over, we have to be here to train this amazing technology because the impact will be unimaginable. And we're only in the first or second inning here.
UNDERSTANDING WHY AI BY ITSELF IS NOT GOOD OR EVIL (26:40)
Navid Alipour: So AI is not good or bad. It's not good or evil, right, just like the automobile wasn't when the car came around, at the turn of the last century, people said, you know what's going to happen to the people that take care of the horses, and the carriages and the horseshoes and, and you're right, all those jobs went away. But look at all the jobs that were created from the auto industry, and look at all the great benefits we've had. But the cars also killed 10s of millions of people over the last 100 plus years, right from car accidents that maimed people and destroyed lives and polluted air. So, the car is not good or bad. It's how it's used. And AI also is not good or bad. It's how it's used. And it will absolutely be used for MAL intent for bad purposes, bad actors. And so, that's where you need the good guys, you need to, you know, the people the laws or regulation, and folks fighting against the bad elements that'll look to use it in detrimental ways. So, I mean, it's gonna, again, impact every facet of our lives. And it's not a good or bad thing. It's a technology, and we need to adapt to it. And the law needs to catch up. And you know, the law is always behind the technology. It's not just an AI thing. But the law has to catch up to technology. So, that's kind of where we are now, where the law will catch up to create laws that are needed to regulate tech and AI tools. And a lot of work to be done. That's for sure. Absolutely.
Darren Reinke: So, attorneys don't need to worry, you know, they'll have plenty of work, as they always do, it seems indeed.
HOW NAVID MANAGES BEING THE CEO OF TWO PORTFOLIO COMPANIES (28:33)
Darren Reinke: I'd love to switch gears for a minute. And something that's interesting that struck me about your current changing roles in terms of taking on the CEO hat of, I believe, two of your portfolio companies. How was that switch gone? Where you were looking for great attributes of leaders, perhaps even developing them? Now? You're actually sitting in the CEO chair or two CEO chairs? How's that gone?
Navid Alipour: Oh, I've never been busier. But that's for sure. And I do have a strong sense of purpose because of these healthcare companies. And that if we get these technologies out there, the more lives we're going to touch, the more lives will be impacted 10s of millions, if not more over time. And so, you know, I don't know if I could have done it at companies that did not have such a big social impact, but with cure metrics and cure match specifically, you know, while we're VCs, and we're the way we're you know, our law firm or attorneys Cooley formed us. We're a plain vanilla venture capital fund, we're VCs, but we're frankly prouder of saying we're entrepreneurs. And so, our model under this venture studio model to help create and build companies, we roll up our sleeves. And so, we are very operational. And you'll find this in the venture capital industry. There are operators that end up becoming VCs and investors because of their domain expertise because they were so successful at, you know, being an operator, be it on a marketing front or product development front or technology front. And so, it's not a new thing to have a partner from a VC fund, take an operational role. And it's something that I always made the joke, not a joke, but I always said that you know, I like being on board. Being an investor and a CEO serves at the pleasure of the board, right? A CEO is not the boss, the board is the boss. And so, here is the board of both companies and these are two that you know Blaise and I, personally, founded before raising the current fund. So, we're personally co-founders on these two, and on the boards, and they have a special purpose for us cure match, for example, we, we ended up starting that, and it was because Blaise had cancer, he had terminal cancer, and was told his five years to live. And he wasn't just going to take that lying down and was on a quest to meet oncologists from all over the world that are working on new innovative technologies. And that's how we met the co-founder with us there, a lady by the name of Dr. Razelle, Kurzrock, who's truly one of the top oncologists in the world. And that's where cure match came from, what they what she was doing at the Moores Cancer Center in partnership with the Supercomputer Center. Scientists there she partnered with. And so, the board of both companies said, hey, the time has come to kind of transition the company to the next level, you know, these companies better than anyone else, outside of the people on the team, you know, why don't you jump in as CEO, and to get them to the next level, especially as we're looking at potentially merging them into a larger AI healthcare company, as they're both fighting cancer, right cure metrics, detects cancer, by images and cure match is a decision support tool for oncologists where if they want to recommend a three-drug combo, that's four and a half million combinations, no human brain can process that. So, that's what cure match does, it recommends based on the patient's specific cancer sequence biopsy, and the drugs available, what the best combination for that patient would be with amazing results. And so, there's been interest from investors to merge these two companies into a larger AI healthcare company with these different divisions. And so, I'm kind of steering the ship right now. And you know, there's a saying that in the startup world, where a good CEO is always looking to replace himself or herself. So, I'm going to do what's best for the companies. And at some point, that's going to be, you know, handing the baton off to someone else to take it to the next level. But right now, the two boards, you know, asked me to step in, since I know both companies intimately. And so, I'm very much enjoying the operational role as CEO, and helping steer the companies and the teams in the right direction to ultimately with our North Stars, get these technologies out there as fast as possible and impact as many lives as possible.
NAVID’S BIGGEST LESSONS LEARNED FROM BEING CEO (32:33)
Darren Reinke: Sounds like a very promising future. That's really exciting. Thank you. What did you learn? Just last question for you, what have you learned about yourself from a leadership perspective, as you made the shift, or really just taken on those two additional hats as being CEOs of both firms?
Navid Alipour: Yeah, you know, it's definitely been a learning experience, there's nothing like doing, you know, advice is always easier given than taken. So, I've always been giving advice, right because I'm on a board. And the CEO asks for advice on everything from, you know, whom to hire and fire to What product are all out whom to partner with, etc, etc. But now wearing the CEO hat myself, of course, I can lean on the board still, now I'm getting advice from them. But in being on the ground daily, and minute, by minute, it's different, it's completely different than just being on a board. Right. And, and so I have a stronger sense of responsibility to steer these companies, and also to make them successful, not just for the end user, that doctors to impact lives for patients. But, you know, we have 40 plus employees between the two companies. So, no, we're not Amazon, but those are 40 families, that their you know, their livelihood depends on these companies, you know, for getting paid. And that's not loss upon me that, you know, these companies mean a lot to a lot of people. And so, you know, I wake up every day saying, you know, how could I do things bigger, better, faster? And in many ways, I've kind of become a therapist, and marriage counselor, I joke because as teams grow, you know, there's sometimes clashes amongst people. And there's other, you know, politics internally, and so I have to be much more patient than is natural of me. Let's put it that way.
Darren Reinke: Absolutely. I think a lot of people don't think about the responsibilities that CEOs have, and you made a great point, you're responsible for the livelihood of those 40 folks and their family. So, it definitely is a big responsibility.
Navid Alipour: And it's also you know, in addition to that, something else to add, you know, I come from a place of servant leadership. So, I'm there to help them do their jobs better. They're not there for me. I'm there for them. And so, that's where I come from. And I asked him, you know, every day every week on after every Zoom call, or you know, what hurdles can I help take down what can I block and tackle On How can I help you? What's missing here? And what resources do you need to do your job better to meet expectations? And that's really where it comes from is managing those expectations and setting people up for success.
NAVID’S ADVICE FOR LEADERS (35:15)
Darren Reinke: What about, what's one piece of advice? Obviously, you've got a wealth of insight you provided today, but what's one insight or a piece of advice you'd give to leaders?
Navid Alipour: I mean, if, again, if I could be so presumptuous to think that it's not known, but I would just emphasize, that come from a place of servant leadership and leaders there to empower the team to, you know, do the job to the best of their abilities and to drive the company. Yes, drive the company to success for shareholders and investors. But you can't forget along the way are those employees that are day in and day out, you know, putting in their blood, sweat, and tears.
Darren Reinke: Navid, thank you so much for coming on today. I know you're incredibly busy with not just one job but three. So, I really truly appreciate your time.
Navid Alipour: Thanks so much, Darren, anytime.
Darren Reinke: Thanks for listening to today's episode of The Savage Leader Podcast. My hope is you walk away with tactics that you can apply to become a better leader in your life and in your career. If you're looking for additional insight in tactics, be sure to check out my book titled The Savage Leader 13 Principles to Become a Better Leader From The Inside Out. Also, be sure to subscribe to the podcast and I would truly appreciate it if you would leave a review and also rate the podcast. Thanks and see you on the next episode.