Leadership, Entrepreneurship, and Innovation with Chris Wolfel and Gene Kesselman

Join MINDWORKS host Daniel Serfaty as he continues a special series on the nature and practice of innovation.

In Episode 3, Daniel talks with Gene Keselman of MIT and Chris Wolfel of Northeastern University about the connection between Leadership, Entrepreneurship, and Innovation. 

How do leaders develop great innovators? What qualities must an innovator have to succeed? And how is generative AI changing the nature of innovation and what it means to be innovative?

Transcript

Daniel Serfaty: What is the connection between leadership, entrepreneurship, and innovation? How do leaders develop great innovators? What qualities must an innovator have in order to succeed? And with the omnipresence of large language models such as ChatGPT, how is generative AI changing the very nature of innovation and what it means to be innovative?

In this special episode of MINDWORKS, we continue our series on innovation with still distinguished and very much in demand guests, Gene Keselman and Chris Wolfel. During the first half of this episode, I will explore the nexus between leadership, entrepreneurship, and innovation with both Gene and Chris. During the second half, we will have a one-on-one conversation with Gene Keselman about the impact of generative AI on innovation.

What I love about talking with both these gentlemen is that they not only recognize leaders and educators in their fields, but they teach and they also do. They are innovators and entrepreneurs in their own right, which made them the ideal folks to talk about leadership of innovation, as well as the impact of generative AI on the innovation process.

Gene Keselman is currently a lecturer at MIT Sloan School of Management. He's the executive director of the MIT Mission Innovation Experimental and managing director of MIT's venture studio, Proto Ventures. He is formerly the executive director of the MIT Innovation Initiative.

Gene has held leadership positions in a range of startups, co-founder of ServDAO, former co-founder of Esports One and the Foundation for Innovation and Discovery. He supports numerous startup as board advisor and has also been a space and defense industry consultant.

As a military officer in the Air Force Reserves, Colonel Gene Keselman works as the senior reservist and director of Strategic Incubation and Strategic Studies Group Reserve Program for the Chief of Staff of the Air Force. He has formerly been the IMA to the Director of the DAF-MIT AI Accelerator and chief, Technology Development at the Department of Defense Research and Engineering.

My second guest, Chris Wolfel, is the associate vice president for Entrepreneurship and Venture Creation at Northeastern University. Chris is a member of the leadership team for Northeastern University Roux Institute, where he is the head of Entrepreneurship and Venture Creation.

He has served the university in many roles over the past four years, including managing director of the Northeastern University Center for Entrepreneurship Education, an organization that had a massive impact with several thousands of Northeastern students and alumni that supports program funding, mentoring, and entrepreneurship across Northeastern global university system in places such as London, Oakland, and Miami.

Prior to joining Northeastern, Chris spent a decade working on the operator side of startup, co-founding two software companies, Mavrck, an influencer marketing software platform, and Helpful, a community engagement and management platform. In addition to his work as an operator and executive, Chris is a board member of Startup Maine, which serves as a convener, educator, and catalyst of the Maine startup ecosystem. Gene and Chris, welcome to MINDWORKS.

We start by, if you don't mind, introducing yourselves beyond the very unjust and too quick resume I just shared with our audience. What are your experiences as an innovator, as a leader, as an entrepreneur, and, more importantly, what makes you migrate toward this area as a field of interest? Gene, if you don't mind starting?

Gene Kesselman: Yeah, I feel like I've been living with all of the advantages and all the burden of that word innovation for the last probably half a decade. I find myself in a position all the time trying to explain what it is and trying to avoid it becoming just another buzzword, which I'm not sure I've been very successful at.

I wear two general hats. There's a part of me that sits inside the government in my military capacity and all this. I feel like I've become an innovation generalist. What that entails is trying to capture the process and the mindset of what innovation actually is without, again, getting down the rabbit hole of the word and what is really innovation, what's the difference between entrepreneurship and innovation, things like that.

So I will say that what I've learned, if anything, is that innovation is just building for impact. It is a process. I could try to explain it and somebody could take a class, but at the end of the day, it is just something you have to go through and you have to do it. You have to be able to look back and say, "I've learned something," and then be able to iterate.

It's really as simple as that. It's a very human nature of ... It's the way we learn anyway. And so, I think it's been captured recently in a way that makes it feel a little bit loose. But I think at the core of it, we all understand it. We all do it as little kids. We get on a bike, we ride it, we fall down, we get back up, we continue riding it, and at the end, we're riding a bike. We just innovated. We learned and we iterated and we succeeded. So that's all I've learned. I just summarized my entire history of the word.

Daniel Serfaty: You're right. It's becoming almost a buzzword, and people forget really the depth and the texture, really, of the concept behind it. Chris, I'm going to ask you the same question. Of all the experiences that you had, what made you choose this area?

Chris Wolfel: I think I probably should have prepped you on this ahead of time. I think innovation's one of the worst words in the world because it doesn't mean anything. I think it's a remarketing of the word change.

For me, I always had a curious DNA and say, "Why is this this way?" I was probably the annoying kid. I've got a three-year-old now that ask me a lot of why. I think the ability to retain that ability to ask why something's done a certain way is really what's at a core of innovation, because I mean, as Gene mentioned, it can be as small as learning to ride a bike. It can be as big as mRNA and everything in that. It's a spectrum.

And so, I think for me, the reason I stay in this field, innovation, I would almost argue it can't be a field because you can do it in any other field, is that every day has the potential to be different. I am not a person that could sit and look at the exact same process every single day. That's how some people are wired.

But I grew up with one parent that was an artist and one that was a general contractor and entrepreneur, and I think always being exposed to people looking at things a little bit differently or taking the beaten path has just stuck with me where I want to say, "Why is it this way?" and, "Can we change it? Can we make it better and not be afraid of that change?"

Gene Kesselman: I disagree with Chris that it can't be a career path, because then I wouldn't have a job.

Chris Wolfel: That's true. I guess I might put myself out of a job too if I said that. But I mean innovation could happen in any industry. It can be a job, but it can be applied. You can innovate in academia, you can innovate in healthcare, you can innovate in podcasting, right? I think in media, that ... I would say it's probably actually a role that should be in every industry, but I wouldn't ... I guess, therefore, I'd define an industry itself. So maybe I just contradicted myself in the first five minutes. But that's a good point.

Daniel Serfaty: That's what innovators do, their ability to contradict themselves and continue to function, perhaps. Perhaps for our audience, I mean both of you find yourself at the interaction between academia and the world of innovation and entrepreneurship. Could you describe, please, to our audience, what do you do in your day job currently? Gene, how would you describe that?

Gene Kesselman: I think it's pretty straightforward. I came here to MIT to run a new initiative on innovation that was stood up. I think as it's evolved and as we've transitioned and sunsetted the initiative and launched a few programs, I think the general thing that I've been doing since I got here was just building new things inside MIT. In that sense, I have probably the best job here because I didn't have to stand on any rails. I didn't have to look at anything in the past and say, I have to build something like this. I got to build from scratch based upon opportunities that we saw across MIT to do things a better way.

Now going back to our previous discussion, if you ask anybody here at any academic institution, everybody thinks they're innovating and everybody probably is innovating, whether it'd be in their basic research field, in the classroom, in applied research, in translation of research. You don't go into somebody in an academic institution, especially like MIT, and go like, "I'm here to help you innovate." What you do is you look at the institute as a whole and you build innovation platforms, innovation infrastructure to help the entire system innovate better.

And so, I think that's what we've been doing for the past few years here. I think it all comes down to one, I think, basic premise, is it's all about translation. It's about taking things that are being done in research and finding the opportunities to translate those into things that will impact the world. It doesn't have to be a commercializable company. It could be research that gets translated to a corporate environment, research that's taken to some other research paradigm, but it's all about translations, about taking the things that are happening here and turning them into an impactful process or service or product or something after that.

Daniel Serfaty: It's not trivial, isn't it? Because you work with one of the leading academic institution in the world focused on engineering and the like. And so, every single person on campus must consider themselves an innovator, whether they're a freshman or a tenured professor, and you are there to tell them, hold on, I'm going to build a road to take that ideal, that concept that you have and take it to, what? Take it to market, take it to a place where other people can use it, which is really the difficulty here, isn't it?

Gene Kesselman: It is. I would say even to your premise, I don't go to them and say anything. I don't bug them. I let everybody do what they do. What I try to do is I try to build around them, and below them and above them and near them, but there's very little that I want to do in a way that is directly changing anything that anyone does here. It's all about providing, in some cases, the easy button.

So we have a venture studio that we've built over the last three or four years inside MIT. The venture studio's primary goal is to help translate more research out of MIT. The way to describe it sometimes is there's PIs out there that are interested in translation, they just don't know how to do it or don't have the time or don't have the staff, the postdocs or PhDs that are interested in doing it. But we bring them the easy button because we created a platform that allows research to be translated impactfully. All they have to do is be interested and work with us and allow us to look at the things they're doing and maybe include that in some of the translation activities we're doing. It's not that I want to change anything they're doing. I want to help what they're doing impact commercially or in other ways.

Daniel Serfaty: The easy button, I like that. We'll go back to that easy button. So across the Charles River here in Boston, there is another institution of higher learning called Northeastern, where actually Chris operates. Chris, how would you describe in a way that our audience can understand, what do you do in your day job? Same challenge. A major institution of higher learning that's focused very much on practicums. You send your students one year during their bachelor degree to work in the industry, in other things before they come back to finish their degree. What do you do in all these functions that you fulfill to create more innovation and entrepreneurship?

Chris Wolfel: Ultimately, what's also interesting is, much like Gene, I was brought on to start a new initiative here at Northeastern University, which was our campus in Portland, Maine, at the Roux Institute. One of the pieces that we have is Northeastern is now a global university system. A lot of people may not be aware, there's now over a dozen campuses around the world in three different countries, and there are innovators and entrepreneurs in every single one of those campuses.

So I like to say there's really three core pieces of my role once we develop the strategy, but how do we develop entrepreneurial skills in our communities, whether those are students or faculty, researchers, alumni, help and enable the growth of high potential ventures out of that ecosystem? Then, third, build a support network that enables them to have greater odds of success.

There's a lot we do under the bucket there, but those are the three big activities and trying to figure out then how do we scale that in a multi-college, multi-location university has a competitive advantage in a way for these aspiring entrepreneurs and innovators, because if you're doing, for example, ocean climate research, being able to have access to Boston as well as London and Portland, Maine and Seattle is actually a really interesting opportunity. What we're doing now is really building out how do we use that as an accelerant of taking these different innovations to market.

I love what Gene mentioned about translating and not forcing, because I think that's the other problem. A lot of people like to say, "Oh, we have this great breakthrough innovation technology. Let's spin it out and turn it into a company." Well, that's not always the right answer. You need the right people around the table. You need the right dynamic of a founding team if you want to turn it into a company.

So I think figuring out the best way to translate an innovation to impact is a brilliant way to look at that, because it seems like our roles are similar as we're enablers of this, not the doing. I think that enablement piece is critical.

Daniel Serfaty: I wish I was still an undergrad student when people like you would function. We didn't have that, didn't we, a few years ago, a few decades ago in this case, at the university, kind of a channel, that easy button? You may be bursting with new ideas whether you're in aerospace engineering or in geology, but there was no channel other than going to your advisor, who was an academic and will tell you to stay in your lane, to express that.

So have you seen recently ... I know what you say, Gene, that you don't push people. You let them come in and then you shape that translation or that ramp. You build within that ramp, but can you think of a recent example of what you would consider innovation? We'll go into the definition in a few minutes, but that made you go, "Wow. That thing, given my long experience, I feel, has a better chance than the others?" Can you give us such an example? I'm going to ask you the same question, Chris. That one thing that basically made it click.

Gene Kesselman: I mean this one is easy because it's the big studio we're starting right now with the Plasma Science Fusion Center at MIT that launched a Commonwealth Fusion Systems, which many people know is the nuclear fusion startup. Those things, five years ago, would've been ironic and best put together or oxymoronic. So nuclear fusion startup that raised, I think, over a billion dollars in a Series B recently, and that came out of the Plasma Science Fusion Center. But we're building a studio and hiring our first EIR venture builder for the studio right now.

And so, it's easy for me to connect to that as the most interesting and, quite frankly, the most awe-inspiring technology I've seen in a while because, A, I'm close to it and, B, it could lead to literally changing humanity and the way that we exist and live if we are able to commercialize and scale nuclear fusion.

The technology that they were able to fund and turn into a commercial company was a high-temperature superconducting magnet that was able to create a field of 20 Tesla in a steady state for a while and, thus, proving that they could produce more energy than they took to heat the plasma.

That's the first step to a scaled system that could not sit on your coffee table or be in the back of your car, but could certainly change the way that the world consumes and uses energy. So it's very, very exciting, and I'm just honored and thrilled to be working even near it to help commercialize and translate more technologies in that area right now.

Daniel Serfaty: Wow. That's a big one. I can ... It sounds so exciting even in the tone of your voice here. That's-

Gene Kesselman: Yeah, it's not hard.

Daniel Serfaty: Because, as you say, it can change humanity. That's a huge bar to pass for an innovation. What about you, Chris? Have you seen recently in the different adventures there at Northeastern, something that pique your curiosity and you say, "Wow. That one has a potential," especially as an investor in your own right?

Chris Wolfel: Yeah. Well, when I was thinking of ... When you had sent this kind of concept as a question to me, I actually got it while I was sitting at a car dealership. So I was going to go the total opposite of a research lab. I was getting work done on my car. Volvo now has a built-in car seat into their car and, in a way, it's like a booster seat that was built in. To me, the beauty in that innovation was in a way obvious but complicated it probably was to make that a reality and understanding a true problem than building something that meets a need. So I was going polar opposite when I was thinking through that.

I think one of the most interesting, exciting things I've seen recently at Northeastern is actually right now, less about in a lab, but in a approach to how we are trying to solve problems moving forward as a university. We launched something called Impact Engines where we are pulling together across disciplinary clusters of experts across our colleges and campuses to solve problems and looking at the historic structures of the university, not necessarily being designed to make impact in the world and shuffling this up.

As someone that would've honestly never ... If we did this interview three to four years ago, I would've never forecast that I would be at a university. In my point of view, before getting deeply embedded here, it was a great part of my experience. I did my undergraduate at Northeastern, so I have a big circle there. But I fell victim, I think, to the view that universities are slow and universities can't innovate on the edge. And so, seeing things like this and rethinking structures to me is just a really exciting way to think about innovation that will develop other innovations.

That's the areas for me recently that have been exciting wows in very different ways. One in a simplistic, usability problem-solving way and the other in the way to potentially reshape an industry and academia that hasn't had a whole lot of breakthrough innovation or innovation at all in the past hundreds or thousands of years.

Daniel Serfaty: I don't think it's a coincidence that both you, Chris and Gene, you come actually from a domain that is not the traditional academic path. Because of your experiences in those domains, whether it's investment or entrepreneurship or even military leadership, you are able to bring innovation into the innovation process per se. I think that perhaps that's one of the key ingredients, that notion of looking at the same object sometime with different eyes and seeing things that other people don't see. I don't think it's a coincidence. I think it's great news for a university to have folks like you facilitate that translation.

Gene Kesselman: I don't think it's optimized, and this might come as a shock to everybody. Universities are not optimized for enterprise changing the way we think. Universities are all about bringing very smart people together in one place and then letting them be the best of the world in that narrow field that they're working in.

Then on scale, they make this incredible impact to the world. But in any one stovepipe, you have basically someone working very, very hard, very, very deep on one thing. I think, if nothing else, perspective shift, novel, lasting perspective shift is the key input variable for innovation, and you can't do that at a university without some purposeful design.

Chris Wolfel: That's a great point because I was thinking through that as a key ingredient to an innovation is a different view, because if everyone's looked at the same problem the same way for 20 years, they're going to come up with the same answer for the most part. Even when we launched the Roux Institute about two years ago, one of the very intentional decisions was our mission was an economic development engine here in the State of Maine, and we had partners before we had a full-time staff here, to figure out what were the problems they needed solved, not necessarily the ones we wanted to solve.

As we built the team here, I don't know the exact percentage anymore, but a much higher, double-digit percentage of the staff did not come from academia. My entrepreneurship team is actually ... No one has an academic background. I've got founders, we've got people that run large banks, we have people that have run investor networks, and bringing that different view in has also rub-off effects in innovation ecosystem because that person getting pulled into a meeting that might not have the traditional background in any other department or any other ... And this is probably scalable to any large entity as well. If you're a big insurance company, having someone from a different team, a different industry sitting in a meeting will bring a different perspective and increase the likelihood you can create some sort of innovation.

Daniel Serfaty: So you already helped me a lot ... Empower the answer a lot by putting some ingredients here of really the key question I want to go back to, which is a question of definition. Not to be academic about it, but to help our audience recognize is something innovative, is an idea innovative. Is innovation synonymous with creativity or is that creativity plus something else? The innovation, I mean the Latin word is about nova, to do something new. Perhaps you can help us not just to find the ideal definition, we can all go to the dictionary for that, but really from your perspective, is creativity a necessary ingredient but not sufficient, for example?

Gene Kesselman: I think that's right. You also have to define creativity.

Daniel Serfaty: You've been spending way too much time in academia. You pushed me back on my [inaudible 00:23:03].

Gene Kesselman: I know, I know. I can't help it. I literally spent the first year trying to find the enterprise definition for innovation. So it's neither more complicated nor that simple, but I think it's just about a process to creating some kind of impact. If you stick to three basic components, I think, it's an idea, there's a process in between, and then there's an impact.

If you can look at anything and say was there an idea, did something happen, did a process happen there in the middle, and then there was an impact from that idea based upon what happened in that process, then I think, as far as I'm concerned, then you innovated. Whether that was creative, whether that was very formulaic, whether it was based on process and design, or whether it was completely by accident, you stumbled into it and you had no idea what you were doing, but somehow you created something that impacted people's lives, as far as I'm concerned, you innovated.

Chris Wolfel: Okay. I think-

Gene Kesselman: I don't think it has to be complicated than that.

Chris Wolfel: I would agree. The thing that I would add is it's almost like creativity is a key component to that idea or the process, but everything you do that's creative isn't necessarily innovative. If I paint a landscape picture, it could be very creative and not necessarily innovative. So I think they're closely related, but I think the innovation side, much like entrepreneurship, like ideas are free. The ability to take it from idea to a thing, whether that's a translatable impact, a business model impact, I like Gene's definition there, moving to impact, that's the innovation.

That's the hard part is taking it from a whiteboard or your mind to changing an industry, changing a process. So that's, I think, where I would say they're closely related, but not synonymous.

Daniel Serfaty: I think that distinction is important, because a lot of frustration I think that I see sometime with scientists and engineers, that they have a new idea, they have published that idea, the respectable journal accepted to publish their paper on the idea, but those two other ingredients that you listed, the process to take that idea and eventually the impact that that idea has on the field, it's the most difficult thing to do in industry, isn't it?

Gene Kesselman: And in academia. I mean you just mentioned something that when I got here, a lot of the ... When we would talk about innovation or what's the most innovative university, the metric that many times would get quoted to me would be the number of patents, how much IP we've created. It didn't take long to basically derive that there's almost no correlation to the number of patents. There's correlation obviously, because if you have a huge dataset, obviously you're going to get a higher percentage of those be commercialized. But that's not how we should ...

We should be measuring. It shouldn't just be how many patents you filed or how many peer-reviewed papers you published, because really what you need to be looking at is how many of those things were translated and how many of those things made an impact. Again, the impact can be anything, but that's what we should be looking at.

And so, it's very, very hard to actually quantify. We had pitch decks that we had to create about innovation at MIT and we'd be thinking about this all the time as, okay, well, we have this huge dataset of patents, the number of Nobel prizes, all this crazy stuff, but is that really innovation? Then, okay, well, how about number of startups have come out of MIT? Okay, well, maybe that's getting a little closer, and so on and so forth. You have to really try to figure out where's the path lead to? What's at the end of there? What was impacted because of this patent or this research or something, or this startup?

Chris Wolfel: I think that ... Also, to one of your earlier comments, Daniel, is looking at a university ecosystem as well is there's a key piece that is the research component, but there's a lot of other innovations happening all over, and students and alums and the corporate partners that are involved. There are ... Like you said, Gene, it can't just be a patent number. There are so many other pieces, and especially in the shift to a lot of the SaaS-based innovations, like Marc Benioff going to a subscription model was a massive innovation that would've never lived in a paper, [inaudible 00:27:21] patent.

Daniel Serfaty: You're talking about Salesforce?

Chris Wolfel: Yes. When Marc decided, "Hey, I'm not going to sell you a piece of software that you install on your server. I'm going to have you pay every single month as a subscription," that's an innovation that changed an industry. That wasn't an innovation that, to my knowledge, came out of a research lab anywhere. No one researched, okay, is it better for someone to pay me once or pay me every month? That would've been a pretty easy calculation potentially. But it was a bet, a risk, and a shift, and it's changed a lot of our industry.

So I think looking at innovations, especially in the university ecosystem only, I mean the biggest technological, scientific innovations are definitely coming ... I would say probably. You can never say definitely. 98% are probably coming out of a research lab. But overall innovation, and you get broad with that word, whether it's governmental innovation, policy innovation, those are coming from everywhere.

Daniel Serfaty: I wonder actually ... You gave the example of Salesforce. You gave the example earlier of nuclear fusion. I wonder whether or not there is an acceleration of the process. I was having a conversation with some friends this week in anticipation of this discussion, and somebody asked me, "Well, was Einstein innovative when he wrote his theory of relativity, or was he just amazingly creative?" I didn't know how to answer that question. That's why you're here, to answer the question for me.

My point was that maybe it is an issue of time that acceleration for impact may take a century or it may take, as you say with the Salesforce example, probably a few weeks, and perhaps the time that we measure impact is what in the modern definition today defines innovation. I'm just throwing that out there.

Chris Wolfel: I think the speed and flow of information and the ability to take things to market now are accelerating innovation, because one of my favorite books is a biography of Leonardo da Vinci by Walter Isaacson. That is to me just fascinating. When you talk about creative and innovation and things like ... I mean his basically hypothesis and design of blood flow was hundreds of years ahead of its time, and it took a long time for anyone to recognize that was an innovation that he figured that out. Today, if he had figured that out, he'd tweet about it, blog about it, podcast about it, and everyone would know tomorrow.

So I think there are other structures of society that have allowed the dissemination of when an innovation happens, and then there's also probably all the technologies that have been able to go from concept to proving something. There's almost two layers. You look at even the low code movement and the ability for someone to take an idea and build an app really quickly. That has transitioned the pace that people could do things.

So I think there are societal and technological pieces that have allowed us to innovate and tell the story and get the story out faster in today's world, but I look at someone like Da Vinci or ... To your point, those people were innovators and creative. It just sometimes took longer to recognize and validate what they're working on.

Gene Kesselman: This is a little dangerous ground for me to tread on because I am nowhere near a physicist or a mathematician, so it's hard for me to grasp how much of the physics and mathematics that happened before Einstein came along that led to his ability to create the theory of relativity or any of the other theories that he pioneered. But I do remember ... I believe there was a story, and I have no idea if this is true or not, that there was something about when he was a young man, he was standing in front of the mirror and he had this idea about what would happen if he and the mirror were traveling at the speed of light and how would that change what he saw?

Again, somebody's going to listen to this and probably say that that's folklore or something or that's not how it worked. But I love that idea that when he was a kid, something came to him. I don't think you have to be a genius to be able to look at a mirror and maybe understand the different properties of light, and then later on in life, many years later ... Or maybe not that many years, but a decade later, he has the training and the background and the intellectual now might to go with his intellectual curiosity of a decade prior to finally create an answer to that question in a way that nobody else had looked at previously or maybe had not fully completed that journey.

The beginning of that started with really a question and an unknown for someone that was going to be smart enough to figure out that answer. But that could have been any of us. Any of us could have been standing there looking at the mirror, going, "I wonder what would happen if we were traveling at the speed of light. Never mind, I'll go off and I'll just go join the military." That's a really interesting innovation, I think, and does it come without that question at the beginning, I guess, is the answer that I'd have.

Daniel Serfaty: I think your example is very powerful, whether it's legend or true. But it's well-documented that Einstein in this particular case, but also other innovators are capable of mental experiments like that. They imagine before even they build the thing. They imagine what it could do, the project, and they're capable of mental simulation of sorts, maybe better, faster, earlier than their peer, and that's how they distinguish themselves.

Gene Kesselman: The certain obsessive point to this in that if there's something you go to bed thinking about and wake up thinking about, then you go do your job. Then you come home and then you just can't stop thinking about it. I always say that's the startup you should work on, but that's also a necessity. I think that's required for this process, I believe, because it takes those cycles. You have to constantly be thinking and all of a sudden something will happen and your perspective will shift. You see it from a different angle and all of a sudden that's where that starts.

I think it doesn't have to be on purpose. You don't have to be, "I need to be sitting down from 8:00 till 10:00 every night thinking about this." It just happens. Maybe in the Einstein example is this was just the way he thought and constantly this kept coming up, coming up. "What would happen if I was in this situation at the speed of light and then this situation at the speed of light?" and then you get the training and you figure it out. I think there's some obsessive parts of this as well.

Chris Wolfel: Back to even your earlier conversation of can creative and innovation, how they connected, I think that idea, the difference here was he decided to do something about it. What you were saying earlier, Gene, about process, or that idea or the question, it doesn't matter if you do something about it a week later or 15 years later, but that process in that cycle is what took ... There probably were other people that looked at the mirror and said the same thing and they just went about their day, or did join the military, like you said, or did whatever the thing was. He jumped in and kept working on it. Whether that was the next morning or 15 years later, that's a proof point on the execution or process to impact as an important factor in innovation.

Daniel Serfaty: Yes. Let me shift gears slightly now and continue to ask this notion, innovation seems to be an inherent quality that we select for, we look for, we invest in in today's society. You both are in an academic environment, even though you're not attached to a particular department in academia.

So question is that can innovation ... That process that is not so magic, yet there is a method to it, as you said earlier, can innovation be taught? Can you actually take a bunch of smart people that self-select when they go to Northeastern or when they go to MIT and teach them to be more innovative?

Gene Kesselman: I definitely think you can teach them the tools and the components that are necessary for innovation, but I don't think you can ... I did a talk this summer and I said you can't become an entrepreneur from a class. You can learn how to be an entrepreneur from a class. You can learn from case studies, you can look at all of the different examples, but you can't be an entrepreneur until you actually do it.

As we all know, the ecosystem and the lore of entrepreneurship is that even at a failure, you're a success in some ways. There's all about the culture in Silicon Valley, like you don't get funded unless you have two failures of your first startups. There's almost no downside to trying it and doing it.

So I do think that you have to make that distinction, is that you can certainly learn and read about entrepreneurship, but you can't be one without doing it. I guess that's then synonymous with innovation is you can you take all the classes at MIT or Northeastern or any other university about entrepreneurship and we'll teach you all of the components. There's books, every single book, which I think are 80% the same book rewritten over and over again, about you have to learn who your customer is, find a problem to solve, create a low-fidelity MVP, or figure out how to make money, scale. These are basic components you can read about and then you have to go do them. That's how you do it.

Chris Wolfel: I'm completely in line with that view. You can teach a set of skills, both hard and soft. I think that's the other piece, especially in entrepreneurship innovation, is you need to either unlock or develop a set of soft skills. There's, as you mentioned, the ability to be creative, the confidence to say, you know what, when most people tell you this is going to fail or this is wrong, like to go and keep at it.

Those are things ... You can teach a set of skills, you can help develop and maybe unlock some ability to think certain ways, but you have to do it. It is not something that you can just take the test and check the box. I like Gene's point there, is you can learn about being entrepreneurial or being an entrepreneur or being an innovator, but until you actually do it, it's all theory.

Daniel Serfaty: I don't know if you know this, but we are now conflating the two concepts. Maybe they are synonymous, or at least highly overlapping in this world of ... Called fast innovation, the concept of entrepreneurship and the concept of innovation. Are all entrepreneurs innovators? Is that a requirement, or vice versa for that matter?

Gene Kesselman: No, I don't think so. The French word entreprendre means to create-

Daniel Serfaty: Take on.

Gene Kesselman: To take on, yeah. But there's entrepreneurs that buy a company that's brick and mortar and doing something, and I don't think you'd say someone that buys or starts a laundromat is necessarily an innovator, but they're an entrepreneur. We did conflate ... And I'm certainly not denigrating laundromat owners. I'm just saying that's been around for a while.

We did conflate the two terms, but I think it's just the easiest way because a majority of the classes at the university are about entrepreneurship, because we all agree that entrepreneurship is one path to translation and the path that many young people want to go on these days. But innovation inside a corporate environment, we get a ton, a ton, a ton of companies that come through here that want to learn how to innovate the way we do, and then go try to do it inside their companies. Some people call that intrapreneurship, so it's innovation or corporate entrepreneurship. Whatever the term is, it's all the same.

It's all the same as finding some ideas inside the company or outside the company, bringing them in, and making an impact on the company, whether that'd be bottom line or profit or not, or maybe new product line. Again, if you just measure those three components, innovation entrepreneurship doesn't actually matter at that point, what you're calling it. It's just we have an idea, let's go do something. Then, okay, does it impact the company? Does it impact the world? Does it market diversity?

Chris Wolfel: I think part of the challenge is they're almost a heavily-overlapped Venn diagram, where the majority of use cases or examples you hear of entrepreneurs, like when you hear of the headline entrepreneurs, they are normally also innovators because they're changing the market. To Gene's point, someone opening a brick and mortar business is a very entrepreneurial activity. It is not always innovative.

There's also innovators who create breakthrough technologies, and the right thing is just license it out to a company or create an innovation in government, which is not necessarily an entrepreneur.

So I think there are some Venn diagram where the innovator has more the idea. Still with the execution, as we talked about, but that's there. The entrepreneur is all about the execution, whether that's buying a business or starting with your own innovation. Because of that, I think you're looking at an area that's got heavy overlap, and that's where it gets confusing when maybe 80% are both. The 20% on each end get a little tough to define.

Daniel Serfaty: That's a very good point. So given what we learned so far about the nature of innovation that overlap that you mentioned, high overlap between innovation and entrepreneurship or innovators and entrepreneurs, can you think of one person that is in the public eye in particular, or perhaps not even the person that you know, that you particularly admire? You will tell your students, "Here's an example in the realm of innovation and/or entrepreneurship," and describe it. Tell us why, why you admire that person.

Gene Kesselman: This one is really hard for me, I've got to be honest. There are so many entrepreneurs out there that I think could fall easily into this bucket. But it's one of those things when you work ... There's a term for it. When you see the sausage made, when you work at the back of the restaurant, you don't want to eat there anymore.

It's not that I believe there are very, very successful entrepreneurs that deserve it, but I also have seen how much luck and how much being at the right place and the right time with access ... Especially for venture capital, but also with startups. You have to be as lucky and as situationally in the right place as good to be an entrepreneur.

Then there's this reinforcing cycle that happens that very good entrepreneurs or exited entrepreneurs get to be future billionaire. Exited entrepreneurs because there's a record of return and things like that, and same for venture capital. So all of the people that we normally would answer this question with, Steve Jobs, Elon Musk, Bill Gates, they were as much a product of their times and the situations as they are of very, very good businessmen and women.

So I don't admire entrepreneurs. I celebrate their accomplishments and I love a lot of their products. But I also know that there was an enormous amount of luck for each and every single one of them. For every person that thinks Elon Musk, especially these days, is the god of entrepreneurs is another army of people that point out all of the advantages he had starting out with PayPal and all of the buying into Tesla instead of starting Tesla and things like that.

So when you said this, I kept going back to a student that came out of MIT, that we hired to be our first venture builder, who pulled himself up, bootstrapped his whole life up to getting his PhD at MIT, finished it in four years, came on to be our venture builder, launched two startups in a year and a half, did all of the coding, design, business development, and every other piece of launching those startups by himself, was brilliant at all of those things. He had a hard science PhD, but could also code, a brilliant artist.

When I met him. I immediately was like, "Well, first of all, A, we're definitely hiring him and, B, this is a future billionaire. I better get to know him better because he might be the person whose coattails I ride for the rest of my life," because that's the kind of person I admire.

It's pre-success, pre-luck and pre-success that I really feel like that's where we should be putting admiration. So that's my non-answer, unfortunately.

Daniel Serfaty: No, it's actually a very good answer, this notion of admiring what they do, as you say, pre-success, I like that term, because they're going to fail, they're going to succeed, and eventually people tend to have a very simplistic view of what success looks like with a snapshot as opposed to the trajectory and the movie, including the moments of luck and being at the right place at the right time. I accept your question, Gene-

Gene Kesselman: Okay, thank you.

Daniel Serfaty: ... and I think our audience will accept your answer.

Gene Kesselman: Appreciate it.

Daniel Serfaty: Chris, what's your perspective? Do you think of one person in particular?

Chris Wolfel: I think of the archetype that can build things in different markets. Similar in a way to Gene, it's not the one person that did one thing. What fascinates me and really gains my respect is people that are able to consistently deliver in different industries. I'm going to contradict myself here, and I always love a founder market fit when you're building something, but at the same time, watching people that can jump into different industries or different verticals to me is one of the most admirable things, because if you build company X and your next four ventures are in the same vertical with the same investors, with the same team, you had some luck and some wins to get there and then you rinse and repeat.

It's still impressive, don't get me wrong. People that have multiple exits in the same industry, same vertical, incredibly impressive. But looking at ... Maybe recency bias here, but again I mentioned Leonardo da Vinci as another one. Everyone knows him for the paintings, but scuba suits, a more accurate two-handed watch, like the ability to jump into things that seemingly don't make sense to be good at both of these things, those are the people that I admire and the ability to take a skill set and bring it into a new vertical.

Maybe it's biased because that's what I want to ... I like being the outsider in a room that has a completely different point of view. I find that challenge invigorating. So watching people that have done it jumping into other verticals or other industries, that to me is an inspiration.

Another is, on the entrepreneur end, small business entrepreneurs. I think this is the area that the venture capitalists didn't venture back to ventures. I started companies that were venture-backed and there's a lot of challenge to it, but there's also a bit of a safety net.

Once you get to a certain point, you never want this to happen, but a company can wind down, and if you raised a boatload of money ... I mean you look at the Adam Neumanns of the world, it didn't really go to plan, he's just fine on the next venture. You look at people that are running a small business and mortgaging their house, that's ... The level of commitment and dedication and risk that those people take, to me, is also a hugely admirable piece.

They might not be in the innovator bucket, but those organizations are the lifeblood of communities, and those are people that I really respect because of the grit and risk that's all themselves. Reputational risk when you raise a big venture round is ... It's almost ... I mean you mentioned this earlier. You're expected to fail a few times before you have the big one. Not really easy to do that if you bet your house and your life savings on a pizza shop. That is all in and that, to me, is who I admire, is people that are willing to do things like that.

Daniel Serfaty: These are qualities, taking risks, steadiness, stubbornness almost sometimes that pay off if other ingredients that are not under your control, as Gene reminds us, are there, too. It's a very complicated soup to make because some ingredients, you don't have them on the counter necessarily.

You mentioned something, Chris, here, and I wanted to ask you that question, is the ability to innovate transferable from one domain, what you called in business school one vertical, to another? Have we seen those people that are able to enter a domain that was not necessarily where they spend the previous 10 years and innovate repeatedly? In a sense, are there some intrinsic qualities that are necessary that transcend the particular expertise necessary to a technical domain or a medical domain or a business domain?

Chris Wolfel: I think the mindset of willing to push the envelope think differently and challenge the status quo is what those innovators have, and that translates industry-to-industry. The comfort of saying, "Hey, I know we've done it this way for a hundred years, but I'm going to look at it differently," I actually think those people are better when they're industry-jumping.

I jokingly have said this to some of the people I work with. I'm worth less to a university every day that I work at a university, because I start thinking more like I work at a university than when I was an entrepreneur, which is why I spend as much time as possible with entrepreneurs and investors to keep that mind shift. But it's natural to get into a groove and a set and a status quo.

I think those innovators, and moving, we use the most, again, probably divisive example right now, but Elon Musk has been in a lot of diverse industries and done some innovations. That's probably the one that everyone knows. But I know folks that have worked in finance and then moved into hospital systems and take innovations into billing and accounting. I know people that have worked at startups and then go work at a giant publicly traded company and become the internal innovator.

So I think it's definitely transferable, and this is almost where we started the conversation about, is innovation in industry for ... It's almost a role and a tool versus an industry itself. Maybe it's a horizontal with a bunch of verticals. You can get into however you want to chart it. But I think those people, when someone says they want corporate innovation or an internal entrepreneur, okay, I talked to a lot of companies that say, "Hey, we need entrepreneurs in our organization, they're really saying, "I want someone that's willing to say, 'I don't agree with the way we've done this,'" and willing to take that risk and make that bet.

So I think those people are transferable vertical-to-vertical. Then I would actually encourage that they continue to move. I don't think someone in that type of role should be in the same organization for 25 years. That's just ... Unless they're moving maybe team-to-team. If you're in a big enough entity, if you're in Disney and you spend some time at ESPN and they go to parks and you go to fit ... Yeah, you can do it that way. But if you work in the same division of the same team for 25 years, your ability to innovate, I believe, is going to exponentially decrease every year.

Daniel Serfaty: Well, on this note, I would like very much to thank you, Chris and Gene, for not just sharing with us but enlightening us with these insights and ideas. The richness of what you shared with our MINDWORKS audience comes from both your experience as mentors, but also your experience as entrepreneurs yourselves, and people who have lived in and around innovation for some time. We'll be back in just a moment. Stick around.

Hello, MINDWORKS listeners. This is Daniel Serfaty. Do you love MINDWORKS, but don't have time to listen to an entire episode? Then we have a solution for you. MINDWORKS Minis, curated segments from the MINDWORKS podcast condensed to under 15 minutes each and designed to work with your busy schedule. You'll find the Minis along with full-length episodes under MINDWORKS on Apple, Spotify, Buzzsprout, or wherever you get your podcasts.

Welcome back to MINDWORKS, Gene, for this conversation about generative AI and innovation. Today we're going to explore how generative AI, that has been omnipresent in almost everything we do over the past year and a half, how generative AI actually influence the very process of innovation and entrepreneurship that you have described in the past hour, especially you have deep experience with that very process. You teach about it, you manage it at MIT. I would like to see your take on whether or not those GenAI platforms for the entrepreneurs, for the inventors, do they enhance or inhibit innovation according to what you have observed so far? If you have some examples to share with our audience, that would be wonderful.

Gene Kesselman: Thank you again for having me. It's a real pleasure to talk to you from this topic. I think, generally speaking, you can't put a full wrapper of a statement on this. I don't think I can say all of generative AI is helpful or all of it is hurtful, especially when it comes to something as maybe a little abstract as innovation.

But my experience has been, no, not just a fan, but a deep user of generative AI, as much as you can be a customer, is that really, if you think of innovation as this process that we have an idea and then you do something within and you take it to some kind of impact or market or mission, I think what generative AI, what it does best right now is on three axes. Those three axes are ... And this is my theory, my three axes, is efficiency, creativity, and problem solving. You can think about a value proposition across those three axes with an AI platform or AI product.

And so, to the extent that if you think innovation just generally is this thing where people, smart people or innovative people, hardworking people, whatever, just people, create this stuff from their ideas, all three of those axes play very deeply in that process. So you become more efficient, you can become more creative, or maybe creativity becomes easier, and it is extraordinarily good at problem solving, at least problem solving to the 80 or 90% solution.

So if you take just that layer, I think it is all benefit. It is just extraordinarily helpful. Of course, you have to then discount for all of the potential issues, the black box issues, the ethics of it, the hallucinations of it. And so, you do have to be very careful that you don't make it the panacea and just cut-and-paste solutions.

But I think, generally speaking, my experience with it and watching other people use it is that if you think of it on those three axes, then you can really boil down the value proposition of generative AI to innovation and thinking how does it help on all of those axes?

Daniel Serfaty: Yeah, thank you. I love your categorization of those three axes because I certainly share that. I can see that, how it influence even the work with my colleagues, the efficiency, creativity, problem solving. I'm going to ask you in a second to perhaps give an example, either of one of them or all three of them, in which you've seen that basically those three essential process of innovation and also, frankly, entrepreneurial innovation, all three axes affect positively the process. But for our audience, you talk about three concerns. Let's start with the concerns and then go back to the examples.

Gene Kesselman: Sure.

Daniel Serfaty: You talked about the black box effect, the ethics effect, the hallucination. Can you expand a little bit on that?

Gene Kesselman: Very high level, very simply, these models are, for the most part, black boxes, even though open source models, where you cannot necessarily recreate or reverse-engineer an answer to some extent, and you don't actually know after a certain amount of training what's going on within the black box of algorithms or processing of the model.

So in most cases, you can't actually say exactly why it resulted in the answer it resulted in. You can give general ideas, you can give general assumptions based upon the training that was done for the model and the training dataset, but you cannot, like I said, reverse engineer exactly how it created that solution. So that's the black box problem.

The ethics problem obviously is because these models are trained on now trillions of tokens. Humans are flawed. We have lots of biases. Those biases are represented in our language and in our writing and in our content. Then those biases then get passed along to the models that are trained on that. So you have to always be careful about the training datasets and the biases that are inherent in that training data.

The hallucination is that, again, these are not perfect models. They're not 100% accurate. In fact, they are not accurate per se. As most people now know, these models predict language and words. And so, they're not actually creating accurate representations for the most part. They're actually just guessing what words come after other words. And so, sometimes what they write isn't false or made up, or hallucination is what they're called. And so, you just have to make sure that you are always doing your diligence on whatever's created to make sure that it's not just making up statements and data and things like that. So those are the three primary, I think ... There's others, but primary concerns about generative AI.

Daniel Serfaty: Thank you for your clarification. I think as much as our audience is familiar and probably using that in their day-to-day, whether they write a speech or they solve a problem in their work, I'm glad you clarified those things, because they are not articulated as clearly as you just did in the open literature.

So let's go back to some examples that you could share with us. When you observe ... In your role at MIT, you are in charge of the studio, the venture studio, but also you are watching some companies being created at the intersection of government work and commercial work. Can you think of an example, without revealing things that should remain private, you've observed either that the efficiency or creativity or even problem solving was enhanced as a result of the inventor or the entrepreneur or the team were able to interact with a generative AI application such as GPT or others?

Gene Kesselman: I have a couple ideas, and the focus here is going to be obviously not on AI as the product, because it's impossible to work with companies now and not run into many, many that are integrating AI into a solution. So we're not talking about that. We're talking about how a company, a startup is using AI as a tool.

I think one of the most stark, best examples I can give you is something probably close to your heart and your experiences. There's a process for applying for government grants and contracts.

So, historically, as you know, the way a small business and startup would begin to access government contracts is through the SBIR, STTR, or SBIR or STTR process, and it was always very onerous for groups that did not have a capture team, a bunch of people that are really experienced with writing government grants, to use the right words, use the right ideas, concepts, understand the customer. You have to have people whose jobs were to do this for a living, to capture government contracts.

The government has taken steps to make all of that easier directly for small businesses and startups to access it through open topic SBIRs and STTRs, but it's still pages and pages of reading and pages and pages of documents and writing. Well, as much as it's probably a bad sign for the SBIR consulting industry where people help you win those contracts, it is now a insignificant and highly efficient effort to use these large language models to basically write your products for you.

I am not just saying I'm the president, I'm a user of this idea. I'm very much using this every day where we are also looking at the things that the government's putting out, and these are ... Even for a guy that's been in for 24 years, going through these documents can be such a laborious task. In five seconds, I can get a very, very good, concise summary of a 40-page PDF that the government puts out for RFP. I can create a standing GPT or standing prompt that basically will write the grant response for me in about 30 seconds. It's an 80% solution. I have to go back in and I have to edit it and add my own flavor and add my own insights.

But what would take, as you know, teams of people days, if not weeks of time, I can, no exaggeration, respond to almost any small business or government grant now in a matter of hours, if not a day or two, by myself.

Daniel Serfaty: This is a wonderful example of efficiency and problem solving actually in your own terminology. That's going to put the whole industry probably out of business, as you say, the proposal consultants, or at least force them to change. As we know, a lot of this introduction of AI in our world is more paradigm of transformation rather than replacement.

But you said something very important here for our audience. You said, "It gets me to the 80% solution." Then Gene Keselman or his team of innovators are now going from the 80% to the 100%. 80% solution gets you a viable proposal. 100% gets you a winning proposal.

Gene Kesselman: That's right. That's right.

Daniel Serfaty: So that teaming between the human expert and the AI has been crafted in a way that basically it gets you already to the point where you can express your true creativity. Is that right?

Gene Kesselman: I will completely agree with that premise, but I will caveat with that is the situation today. I think the speed of which these models are adapting, the amount of data that they are trading on and the trillions now of dollars that are being poured into this means that it is only temporarily an 80% solution. It is only a matter of time before ... I used to think it'd be five years. Now, the way these models are evolving and how fast they're moving, I think it's a matter of months, if not a year or two, where it won't be an 80% solution anymore. It will be a 95, 98% solution. Maybe it's never 100 because you never want to ever just blindly cut and paste.

But the idea of it's not just a model, it can now be actual representation of your persona. You can encapsulate ... Most of us have enough of a digital footprint out there. We have enough of a representation of ourselves where it is, again, very closely and temporally close that we'll be able to just not only get it to the 80% solution, and then fix it with 20% ourselves, but get it to the 80% solution, and then have fix that 20% as ourselves.

So the direct agent of Daniel or Gene does the last 20% of the work, and that's in your emails, all of your documents. Everything that you've created creates this persona, this agent that will do exactly the same thing almost that you would do. So that's the idea, and we're not that far away. So I will say that.

Daniel Serfaty: I don't know if ... To get very enthusiastic about it or a little bit scared, because what you're saying is basically the next generation of those systems is going to have a very accurate model of each one of us and, therefore, be able to write that proposal in a sense, whether it's a proposal to the government or, frankly, a proposal to any other funding mechanisms, including investors, in a way that is fully representative of each one of us, kind of a digital twin of sort.

Gene Kesselman: Yes.

Daniel Serfaty: Well, that will allow us to spend more time at the beach, I guess, while the proposal is being written in our name. That's an interesting vision. I haven't thought about it that way, Gene. Thank you.

So let me speak to the other side of your own personal self in a sense that you are not just nurturing entrepreneurs and incubating ideas or helping launch companies at MIT, you're also a lecturer. You also have students in a classroom that come to listen to what you have to teach, either in entrepreneurship or in how to transition dual-use technology from, say, the military to the civilian sector.

As a teacher this time, as a person who is having in front of him a collection of learners, of students, very smart students in that case, tell me a little bit about their use or your own use of generative AI in the classroom in order to do their work in the classroom. Is it affecting your teaching?

Gene Kesselman: Yes and no. So we taught a design-build engineering class last semester with Special Operations Command, and in that case it was not a big impact on our work because it was a fundamental engineering curriculum that was very obviously hands-on and experiential. And so, they had to be building ... They got a problem set, they talked to the mission user, they got the context, and then they went off and spent the semester building a prototype.

So to the extent that the students absolutely used generative AI to help them with their creativity probably allowed their efficiency of writing the engineering deliverables that we had them write. The fundamentals are that the AI's not going to build the prototype for you at this point. And so, there's still a lot of work that the students have to do as engineering students.

That being said, on the other side, to MIT's credit, MIT Sloan had a open call for a AI learning group at Sloan that I happened to be selected for and was a part of, and that's for teaching faculty that were using AI in the curriculum and how we could do it better. They gave us access to every model available. We were able to get the pro accounts, too. They gave us a bunch of new products that were coming out. Every week, there was something new coming out and we were talking about how to use them in our teaching and things like that.

So anyone that's teaching anything at any level has to be aware of the impact. I think it makes grading very difficult. I think it makes writing papers much easier. I think it makes creating problem sets much easier. There's just so much good and bad, and the teaching is going to fundamentally change because of it, even more so than it has.

I can't give you a final answer to your question, unfortunately, because everybody's figuring it out right now. Everybody is. Some think of it as a real detractor. Some think of it as the evolution of teaching should go. But it's changing. One way or another, it's absolutely changing. We just don't know yet how much is the daily answer, basically.

Daniel Serfaty: I like that answer. I like we don't know yet because that gives me an excuse to invite you again a year from now or so to the next podcast, when you tell me, "Okay. Do you remember what I told you a year ago? This is really what has happened in the classroom."

Gene Kesselman: Sure.

Daniel Serfaty: That would be wonderful. A couple of weeks ago, we had a MINDWORKS podcast focusing on that, on the transformation of education, both at the professional level, as well as in the schoolhouse, including K through 12 and at the university. And so, we are tracking that very closely here at MINDWORKS, and certainly I would be delighted if you could share your insight in a few months or next year about it.

Gene Kesselman: I'd love to.

Daniel Serfaty: Let me ask you one last quick question. In your work, you see some companies being launched. You see the student or the entrepreneur or the student entrepreneur go out and launch a company. Some of them are successful. What would be your advice for that young CEO or CTO that has just been successful, has gone through maybe a seed stage, and is now managing building a company? How can they use generative AI to be a better manager, leader of that startup?

Gene Kesselman: It's hard to say because I don't get a lot of access to the day-to-day use of AI within a startup. I will say from a product standpoint, the thing that we generally advise about the AI market is a little bit of it is taken, from my experience, in the Web3 and the crypto market of the last 5 to 10 years.

To be very clear, I do not think they're at all equivalent. I think the crypto market ended up being a huge bubble because, in and of itself, the technology just ... It's a very real technology, but the market made it that it was very ripe for a whole lot of corruption and rug pulls and a lot of bad market players. I don't think AI is like that, but I do think that there were companies just sprinkling ... I'd say sprinkling crypto over everything. Now there's this time to sprinkle AI in your startup and just figure out some way to integrate an LLM or a product.

We certainly advise against that because while you may be able to raise a little bit more money because you have AI in your title, long term that is obviously corrupting the whole idea of finding that product market fit.

The other thing we see is the focus on AI as a product. If you're not creating a foundational model, which is very, very hard if you're not working in AI data, you're creating wrappers basically, wrappers around models, wrappers around foundational models or other things. You have to be very sure, and the first question we ask is, does your startup become obsolete the next time ChatGPT releases a new version?

There's a funny anecdote about ... I don't know if it's lore or true because I'm not that involved in the west coast, but that an entire Y Combinator class was wiped out when ChatGPT came up with CustomGPTs. All they were doing was creating basically just ways to create your own custom, trained dataset model, and then ChatGPT comes out with CustomGPTs and the whole class is wiped out.

So obviously it's quite an exaggeration, but make sure that you're attacking the market in a way that's at least somewhat defendable from companies that have trillion-dollar cap tables. It's very difficult to compete with those folks.

So that's what I'm seeing. I'm sure the startups are using it on those three axes that I talked to. But everybody should be using it on those three axes. But I don't think I have a good example of just how a startup is making ... Did they raise a VC round faster because they used AI? I'm sure there's a lot of people that have made much better pitch decks with AI than ... I just don't have a really great visceral example of that.

Daniel Serfaty: No, no, but you gave us one very good examples of that and the danger of just using AI as a wrapper, because I think there will be some backlash about the market, and the investors are going to see through whether or not you're just using AI as a lubricant or you're using AI because it's part of the core of what you're doing.

Gene Kesselman: Absolutely.

Daniel Serfaty: Well, Gene Keselman, thank you very much for sharing those additional insights. Your position and your job when you straddle academia and industry makes your position particularly privileged to see really the evolution of that in those two worlds, and sharing that with our audience is great. Thank you.

Gene Kesselman: My pleasure.

Daniel Serfaty: We're going to share more in subsequent podcasts about how AI is affecting different industries. We started with education and training. We're going to continue in a large number of verticals or vertical markets or industries to explore more perhaps what you just said, what you just hinted at about the use of AI in products, the use of AI in launching new lines of solutions in the market.

Thank you for joining me today. As always, the MINDWORKS team welcomes your comments and feedback, as well as your suggestions for future topics and guests. You can email us at mindworkspodcast@gmail.com. We love hearing from you.

MINDWORKS is a production of Aptima Incorporated. My executive producer is Miss Debra McNeely and my assistant producer is Miss Chelsea Morrissey. Sound engineering is provided by Bespoke Podcast Editing. To learn more, please visit aptima.com/mindworks. Thank you.