Empowering Exceptional with Manoj Saxena

For this episode, we’re joined by Manoj Saxena, a serial entrepreneur focused on artificial intelligence and augmented intelligence.  A longtime client of V&E partner Paul Tobias, Manoj talks with Paul and Empowering Exceptional host Sean Becker about how he got his start in tech and shares his thoughts on what it takes to succeed in the startup space. He also explains the innovative work of his current startup, Cognitive Scale, as well as the mission of his nonprofit, Responsible AI.

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Sean Becker:

Manoj is a thought leader in the field, an entrepreneur, and a true innovator.

Hello, and welcome to Empower Exceptional, V&E+’s podcast series, focusing on fascinating people doing incredible things in their fields. I’m your host, and also the head of V&E’s Employment, Labor, and OSHA practice, Sean Becker.
We’re joined today by Manoj Suxena. Manoj is interested in all things artificial intelligence. He’s a venture capitalist in that space, executive chairman of the AI start-up CognitiveScale, and the founder of a non-profit called Responsible AI. Manoj is a thought leader in the field, an entrepreneur, and a true innovator. Welcome.
Manoj Suxena:
Thanks, Sean. Pleasure to be here.
Sean Becker:
We’re also joined today by Paul Tobias, a partner in the Mergers and Acquisitions and Capital Markets practice at V&E, working in our Austin office. Paul’s first client in Austin was Manoj Suxena. Paul, tell us how you two met.
Paul Tobias:
Thanks, Sean. Manoj, it’s tough to believe, but it’s been 20 years plus since we met, and you had just started Exterprise, and you were looking to raise money from an investor, Shelby Carter. That was an important moment for you to raise money because you had run up $200 thousand dollars of credit on your 13 credit cards. What were you thinking?
Manoj Suxena:
Clearly not right, but, no it’s incredible to think it’s 20 years. Just a quick recap, I had moved to Austin from 3M in Minnesota. I’d gone to business school and got hired by 3M. After freezing my behind for 15 or 18 months in 3M, I decided, “I gotta look for something more warm,” so I moved down to Austin with 3M.
In 1996, I came across this thing called Mosaic, the browser. It was on one of those life-changing moments for me, when I realized what it meant in terms of accessing and distributing information. So, I started getting this passion of trying to find and build a business, because the one thing I learned at 3M was the art of innovation.
In the 7 years I was there, I had multiple promotions, but one of the things I really admired was how do you convert ideas into products into profits. The browser, even though I didn’t have much of a software background, I realized instinctively that that’s going to be civilization-changing, not just market-changing.
So, I had this obsession about trying to put that to work in transforming how businesses connect with each other, but I had no background in that area. I didn’t have any money. I had no credibility, but at that time, I decided the one way to do that was I needed strong, technical people, and they wouldn’t come to me if I told them, “Work for peanuts.”
So, I took 13 credit cards, and I owed $200 thousand dollars of credit on it, although I didn’t end up using all of them. I only used about half of it before I realized I should get some investors in here to start sharing the risk. When I was doing that, one of the best piece of advice I got when I was leaving 3M was to make sure that I go the best lawyer and the best accountant I could.
When I started asking around town, “Who was the best lawyer?” Paul’s name came up in multiple sources. That’s how we got connected, and we haven’t looked back. I always say that I will never do a start-up or a venture fund without Paul Tobias by my side.
Paul Tobias:
Yeah, I say the same thing, Manoj.
Paul Tobias:
When you started Exterprise, it was a good time to start a company, but by the time you were in the mode to sell Exterprise, the market had changed.
Manoj Suxena:
Oh, yeah.
Paul Tobias:
You sold that to Commerce One, a very fine exit, in particular, at that time. Then you decided to do another start-up. What was driving you to do your next start-up?
Manoj Suxena:
Yeah, so, a couple of things. We got lucky. A lot of times you want to think you’re good, but effort helps, talent helps, but luck and timing also has a lot to do with it. When we got acquired by Commerce One, I spent about a year there to make sure a couple of things happened, make sure that my team was taken care of in terms of getting integrated properly and got good career paths, and also to make sure that the technology was being put to use in the right way.
But, the markets in 2001 started really going down south fast, and they wanted me to come and move to California and be the president of Commerce One, and I just couldn’t find it in myself to leave Austin and go to California. After about a year, I decided to leave and build Webify, which was a second company.
So, there was about a year’s gap where I was working as a big company exec, and then started Webify, which, again, Paul was the first one I called, saying, “Let’s incorporate this company.”
Paul Tobias:
So, that was another fun ride together, Manoj. In 2006, you decided it was time to sell the company again, and this time you sold Webify to IBM and ended up ultimately becoming the first general manager of IBM Watson. What did you do with IBM Watson, and how did you approach that incredible opportunity?
Manoj Suxena:

The people part of this is the most important part. People think it’s about technology, but it’s actually about people.

Yeah, again, IBM was a phenomenal validation of the work that the team had done and the product and technology that we had built. I was there for about three years when the Jeopardy game was played and IBM decided, the board decided, to make a commercial business unit out of it.
Given that I was a guy who had built and sold a couple of companies, they asked me to lead that business. I literally started with a department [inaudible 00:07:04] and a budget for tens of millions of dollars. When I got going, I had to frame the problem and solve for four things.
Number one, I had to figure out what exactly is this technology and what does it do? It’s one thing to play Jeopardy and beat the Jeopardy champions. It’s another thing to build a commercial application that people will pay tens of millions of dollars for. So, one, I had to understand what it was.
Second, I had to put a team of people around me who could believe that this could be put to work in a commercial way for the good of humanity and good of IBM, so I had to go recruit other people.
There is an old African saying that says, “If you want to go fast, you go alone. If you want to go far, you go with a group.” I knew that I had to get the right group around me. The people part of this is the most important part. People think it’s about technology, but it’s actually about people. It’s a human enterprise. So, that was the second part I had to do.
Third thing I had to do was go find the markets and applications to apply this incredibly powerful technology, which we all knew that was going to change not just IBM, but change the entire industry along the lines of what IBM mainframe had done for the company. So, I had to be very thoughtful about where we put this to work, because history will judge us.
The mainframe, for example, IBM very thoughtfully chose to apply the first application of it for census. It was something for the good of humanity and good of the social cause, so I decided, and we decided, to put IBM Watson to work for cancer and medical care. So, that was the third piece we had to do.
Fourth was we had to get a customer who would then sign up to be a pioneer with us. They say that the way to identify a pioneer is someone with the most arrows in his back or her back, so you had to find someone who was willing to take those arrows in their back, and we got some good customers. I stayed with IBM Watson for over three years, grew it to a few hundred million dollars in revenues, and then I decided to move on from becoming a … from changing from being a player to being a coach and to invest in other people’s potential, so that was sort of the last phase.
Again, Paul was right through helping me negotiate my employment agreements going in and employment agreements coming out of IBM, for which I am very thankful.
Sean Becker:
Manoj, I’ve heard you talk about your experience with Watson, and you analogized it to an industry that people were dying of thirst in an ocean of saltwater.
Manoj Suxena:
Sean Becker:
There was information all around, but you didn’t know what questions to ask. So, tell us how you went about applying this incredibly powerful tool with Watson to the healthcare industry.
Manoj Suxena:
What occurred to me was what we were talking about is a whole new class of tools that humanity has invented, and this class of tools will go down as the most significant. ‘Cause everything before Watson, whatever humankind had invented, amplified our arms or our legs, but nothing ever came to the power of our brain. Watson represented a class of technologies called artificial intelligence. Now Google and Facebook and everyone else is doing it, now.
That was the first set of tools that were able to amplify our brains, that were able to amplify the processing power of what human mind does, what human brain does. Because, before, and even now, most of the times, a computer is nothing but a giant calculator. All it can do is can do math and it can do a little bit of understanding of numbers and text, but without that, it can’t process an image. I can’t point my camera to that chandelier and say, “Who is the designer of it, and where can I buy it?” Because an image is a non-computable object.
So, Watson and that technology is represented three sets of capabilities. I call it sense in foreign act. It was the ability of computers to first sense all available information, not just numbers and data. So, a computer could sense what an image meant. A computer could sense what a document, like a dissertation or a medical journal, meant. A computer could understand audio conversations. So, that was the first part, that sensing was a new capability that computers had that didn’t exist before.
Second was it could then infer and start tapping you on the shoulder and saying, “This is something I found of interest for you. You may want to look into it.” So far, and this is something I did after I left Watson, was almost flip Watson on its head, ’cause in Watson it was a question and answer system. I had to ask a question and I got an answer back. What if I didn’t know the question to ask? It was something, actually, a 10-year-old asked me in a class, and she said, “Excuse me, sir. Can Watson tell me what question to ask?”
So, I think that is that other genius of, “How do you use computers to augment our capabilities?” Third was, “How does it learn? Once I make a decision, how does it learn?” So, a good example of this is Spotify, right? If I’m listening to my music, if I give it a thumbs up, it starts creating new playlists for me based on my preferences and based on similar artists like that. I think that was the genius of what Watson was. It represented a generation one of a whole new class of computing system that could process all kinds of information and help you make better decisions.
Healthcare happened to be an area where there were eight million pages of research being published every year on different types of cancers. An average doctor was spending less than five hours a month reading of medical journals. Clearly, their ability to do diagnosis could have been augmented quite well if they had a tool like Watson that can help you guide through your diagnosis.
That’s sort of the journey. First, understanding what is it that this new class of systems are representing. Second is then applying it in a deep domain to drive outcomes.
Sean Becker:
So, your current company, CognitiveScale, that’s concerned with AI being augmented intelligence as opposed to artificial intelligence?
Manoj Suxena:

An AI system is a pattern-based system. It learns to connect the dots, and it gets smarter with time. So, while a traditional system loses value with time, an AI system gains value with time.

Yeah, that’s right. One thing is, if you look at artificial intelligence, there’s so much myth, and, frankly, there’s so much hype about AI today. The way to understand AI is not just as a set of technologies, but a set of capabilities. On one hand, you have artificial intelligence as a collection of technologies. Natural language processing, computer vision, sound processing, deep learning, all of these are components of a broad category of technology called AI.
Then, there is the application of AI, which is building intelligent systems that process all available information and help you make better decision, and they get smarter with time. Everything we have built in IT so far have been rules-based systems. The problem with rules-based systems is rules don’t learn. An AI system is a pattern-based system. It learns to connect the dots, and it gets smarter with time. So, while a traditional system loses value with time, an AI system gains value with time.
When you zoom back out and look at AI, there are three types of AI systems, broadly speaking. One is AI that could be used to automate a task and a human being. So, anything that a human brain can do in two seconds or less, today can be done by a machine in a much better and a cheaper way. So, one is automation.
On the other end of it is autonomous systems, things like self-driving cars, where you remove the human out of the loop and you completely have a self-driving system. I think both of these represent outlier cases. There’s only about 10% of work that is … Things like robotic process automation that can automate that work. I think autonomous systems … There are very few systems that are truly autonomous.
The bulk of opportunity is the middle, which is augmentation, which is, “How do you pair humans and machines together, so they can make better decision, and they can make …” So, to break out AI, it is automated decisions, augmented decisions, and autonomous decisions.
We felt, in the early days of CognitiveScale, we used to say that CognitiveScale is going to build the operating system for every person’s Iron Man Jarvis suit, so that every human being will have a computer that’s tapping you on the shoulder. Every lawyer has the power of 10 thousand best legal scholars behind saying, “When you’re preparing for that case, I’ve gone through all the case laws, gone through the jury’s profile. Here are four arguments I suggest you should make to have a better day at the court today.”
So, that’s the type of stuff that I really think is where the power is, is the ability to augment human decision-making.
Sean Becker:
It’s one thing to have an idea. It’s another thing to take that idea and execute on it successfully. You’ve done that repeatedly. So, what’s your secret? How do you take your visions and turn that into tangible success?
Manoj Suxena:
I think it’s a combination of things. I think one of them I gave a Ted talk on is about this notion of courage to fail. I would break it out into three or four things.
Number one is, you gotta have the courage to fail. One of the beautiful things about America … You know, I grew up in India, and in this society, no one cares if you fail. You pick yourself up and you go back again. That’s the pioneer spirit and the pioneer mentality. In India, if I failed, oh my god. That’s like a black name on my family, and people will say, “Your son is not cut out …”
So, this whole entrepreneurial peace is something I learned at 3M is the whole spirit of pioneering, the spirit of getting back on your feet and trying. So, this notion of, “Everyone has the desire to succeed, but very few people have the courage to fail.” I think building the resilience inside and saying, “It’s okay to fail.” Right? That’s one.
Number two is the ability to look around the corner, right? I have never been the smartest guy. I work hard, but there are many other people who work harder than me, but the gifts that I have are two gifts. One is I can look around the corner sooner than most people do, and second is, I have the ability to identify and inspire and engage the best and the brightest around this crazy thing I see coming around the corner.
Those would be the three things.
Paul Tobias:
So, Manoj, looking back at your failures and your successes, what advice do you have for entrepreneurs who are starting companies today?
Manoj Suxena:
Number one is there has never been a better time to be an entrepreneur than now. We are living in this time of a digital renaissance. What Italy went through back with the Renaissance, I think 10 years from now we’re going to look back and realize that what we’re going through right now is going to make the internet look small.
There is this Cambrian explosion of technologies that is happening right now. For a thousand dollars, a buck, a month, last year you could get the power of an insect’s brain in the Cloud. This year, for a thousand dollars a month, you can get the power of a mouse’s brain in the Cloud, and twelve years from now, you can get the power of a human brain in the Cloud for a thousand dollars a year.
When you have a digital canvas like that, there is a tremendous amount of creative things you can build on top of it, and new business models that can come up. It’s going to make the last set of companies look small, what has been built.
Second part is really understand yourself. Understand what your life plans are before you put your business plan in place. Many people, when they come to me and they say, “We want to start a company,” and I ask them, “Why?” Any one of them that says, “I want to make a lot of money,” and I tell them, “Go take a cold shower and don’t come back and talk to me until there is this deep, burning desire saying, “I want to change the world.” Because, there are easier ways to make money, and true entrepreneurs are obsessed about really changing the world.
Third is teams. You are only as good as the people that you hire. Find people who have complimentary skills than you do, and definitely don’t have friends to get into a business with. Beer buddies make the worst business partners, and if you want to destroy a relationship, absolutely go into business with someone. A lot of people come to me and say, “She’s my best friend and we have known each other for so many years.” I’m like, “Not going to make it.” Right? Unless the skills are complimentary.
Then, last but not the least, surround yourself with good advice. I think it’s incredibly important to get coaches. Everyone from people who have done companies before to people like Paul Tobias in the law side, to people on the accounting side … I think it’s critical to build an advisory group who can steer you through a lot of ditches that you will get into, and believe me, everyone gets into a ditch.
Sean Becker:

No matter what you start with, 90% of the start-ups changed course. The idea that you start with, 18 months down the line, there’s a 90% or better chance it will be something else, because the market would have guided you towards that.

Start-ups are synonymous with innovation, and entrepreneurs starting up, they might have the ideas. They might have the passion. They may even have some good advisors, but how did you overcome the challenge of having limited resources at the early stages?
Manoj Suxena:
You know, it takes three things to build companies: People, ideas, and capital. Of all of this, capital is the easiest to get. It sounds very non-intuitive to people who are starting off their companies. The hardest thing to get is people.
The second hardest thing to get is an idea that the time has come, and then the last one is money. People over-index on money in the early days because here’s the reason. If you are building a business around an idea or a concept for which there is no market need, no amount of money that you put into it, no amount of geniuses you put into it, is going to change the outcome.
Another thing I’ll guarantee is this. No matter what you start with, 90% of the start-ups changed course. The idea that you start with, 18 months down the line, there’s a 90% or better chance it will be something else, because the market would have guided you towards that. If you don’t have the right people with you, you will not be guided towards the right answer. I think that sequence of people, ideas, and capital, rather than capital, ideas, and people, is what I think good entrepreneurs need to understand.
Paul Tobias:
Manoj, you’re one of the few people who’s had multiple entrepreneurial successes, companies you’ve started, and you’ve also served as an executive of one of the largest companies in the world. Innovation is very difficult at large companies, it seems. What advice do you have for the large enterprise on how the enterprise can better invest in innovation?
Manoj Suxena:
Yeah, no, great question. In fact, it’s an area where I’ve been spending a lot of time, a lot of boards, and CEO’s today … I think there’re two parts to it. One is that the traditional model of innovation is going to be changed forever. Traditionally, the model was that, “I have size. I have customer access, and all the good ideas are going to come from me.”
I think that model is shifting very quickly towards the role of big company’s IT departments from building IT systems to building IT ecosystems, because not all the smart people are going to be within these companies, because the complexity of skills that you need across Cloud and big data and mobile and social and design is just not possible for large companies, even a company like IBM to be able to get all the ideas from the inside.
That’s why corporate venturing, I think, is going to get more and more relevant and important going forward, ’cause companies have access to customers and brands that every start-up needs, and start-ups have innovation and speed, which every big company needs. So, it’s a synergistic thing. That’s one.
The second part is being customer-focused, really understanding where is it that the market is guiding you, and there’s no guarantee that the business you are in today is going to be there five years from now. I think having a sense of, call it humility, as well as disrupting yourself by understanding the market.
In many cases, it might require putting a 22-year-old to drive an important business function that you may not have ever thought of. In fact, when I was running Watson, I got into trouble with some of the HR guys, where some projects I said, “No one over 30 will be on that project,” because it was requiring a whole new class of skills and expertise that I didn’t think old people like me would really grok it, to use a millennial term.
I think we got to have a combination of excitement and humility on how we innovate. Both innovate inside and outside, and innovate by engaging different groups of people.
Paul Tobias:
Artificial intelligence represents a tremendous opportunity, but there are many who fear the unintended consequences of artificial intelligence.
Paul Tobias:
You have a passion, I know, about making sure the use of artificial intelligence and augmented intelligence happens responsibly. Can you tell us about that?
Manoj Suxena:
Yeah, this is an area that really has grown and bothered me a lot. I tell my daughters that I want to eat well and sleep well, and of late I’ve been eating well but I’ve not been sleeping well, because of what I see coming with AI. The CEO of Google said that AI is going to be as transformational to humanity as fire and electricity was, and I think he’s not very far off the mark.
This is civilization-changing technology, and this is also a technology that has great power to do good and tremendous power to do harm. This is going to be like nuclear power times a million in terms of the advantages that you can derive and the disruption and dislocation that it can create for us as a society. What’s critical is for businesses and regulators and policy-makers to really start understanding, what is this technology? How is it being put to use? How can it be put to use for destructive purposes?
There are two parts to what I am doing in terms of my work. My family foundation, we are focused on this non-profit called Responsible.AI, which is how do you help governments and businesses understand and adopt AI by balancing innovation with regulation, right? Unlike with nuclear power, where the barrier to entry was very high, with AI, in two or three years, you could have a kid from any part of the world come in and mess up a big part of our infrastructure and economy.
There are people who are building autonomous drones for warfare. There are people who are building AI that detects mine and blows up when a soldier walks over it. There all kinds of crazy stuff that’s going on.
I think there is a tremendous need here for governments to really get ahead of this and start figuring out what kinds of rules of engagement. When the nuclear weapon were invented, we had the the convention that was the Geneva Convention, or the name, I think, was that, where the countries agreed how to put this to work. Something similar has to happen with AI.
The second, more pragmatic part of responsible AI is businesses and consumers understanding how this is going to be put to use. There’s a soap dispenser that uses an AI to dispense soap, and people found out that it only dispenses to white hands. It doesn’t dispense soap to black hands. When they found out what it was, they realized that the AI was fed images of light-skinned hands, and it saw that as a hand, so when a person of darker skin put the thing in it, it …
I mean, I have dozens of examples of AI going rogue because it was not designed properly.

The rest of my life I’m going to dedicate around educating governments and businesses around responsible use of AI.

Businesses have to start … I mean, what Facebook went through with Cambridge Analytica, what we’re seeing today in the world, this politics that we went through today. Social media has been weaponized with AI, ’cause what AI can do now is understand you at an individual level, and you at an individual level at a granularity far bigger than what we ever had, because every like, every picture you post, every person you comment on, is building a profile of you in a way that can then be manipulated. The human beings can be hacked with AI.
That’s what the last political campaign was. It had human brains, and it basically polarized us as a society. If you look at what happened not just in the US, but in Burma and in the Middle East and all, AI was used to hack the human software. If you don’t have proper regulations around it, you could have flash mobs, you could have fake news, you could have things that are way more destructive coming into us in the next 5 to 20 years that, as we as a society and as a business, if we don’t start getting ahead of it, I think it’s going to create a tremendous amount of disruption and chaos.
The rest of my life I’m going to dedicate around educating governments and businesses around responsible use of AI. I’m starting that with teaching a course in UT Austin next Spring on designing AI systems, so that’s going to be my first step into the realm of moving from a player to a coach, to now an educator. That’ll be the final phase of my life.
Sean Becker:
That’s fascinating, and you’ve clearly got a lot on your plate, a lot on your mind. Do you do anything to take a break from it all?
Paul Tobias:
I bet I know what he’s going to say.
Manoj Suxena:
Yeah, Paul knows. A lot of people get kind of concerns about it, but I love racing cars. Racing cars is the only time where I can shut my brain down, because it forces you to be one with the car, and if you think anything else outside of the car, bad things happen.
My daughter likes to say that I have like a million tabs open in my brain and I think that’s not very far off to think I do have a lot of tabs, like browser tabs, open in my brain. When I’m racing, it forces you to shut down all those tabs and focus on …
So, I do long distance racing. I have an 84-year-old car from 1934. There are only 22 of those left that I just drove across Africa in that. I did Singapore to Burma a couple of years ago, and my next big one is going to be around the world in 80 days.
The racing, to me, is like meditation in motion. Racing is where my brain gets calm and I kind of disconnect with the world, and it’s a great way to see the world and meet some cool and crazy people who like doing similar things. That’s kind of my passion and my outlet.
Sean Becker:
We’re grateful to you for spending your time today, and thank you for joining us and sharing your incredible insights.
Manoj Suxena:
My pleasure.
Paul Tobias:
Manoj, you talked about going from player, to coach, to educator, and I really enjoyed each phase of that for you. You’ve always been an educator to me. I’ve learned so much from you, observing the way you carry yourself, the way you run companies, and the way the integrity that you have as an individual, and I really appreciate you taking the time to share your insights with us today.
Manoj Suxena:
Thank you, Paul. It means a lot coming from you, and I wish my mom was alive to hear that, but thank you. It means a lot.