Adam Torres and Dr. Martin Trevino discuss vetting investments.
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Vetting companies and new technologies correctly can mean the difference between success and failure for VCs and the C-Suite. In this episode, Adam Torres and Dr. Martin Trevino, Cognitive Neuroscientist & Chief Scientific Advisor, explore what it takes to vet technologies and companies for investment.
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About Dr. Martin Trevino
Martin Trevino a Theoretical Scientist/ Tech Executive specializing in Next Generation Visual Analytics & Decision Science and Program Management.
His passion is next-generation Visual Analytics, Risk, and Human Factors influencing how humans make data-driven decisions. He believes in the “Art of the Possible” – “What can we do beyond mere incrementalism”? What will the next generation of Analytics and AI look like? How can we create new models of complementarity to mesh technology with human beings for innovation, performance, and uniqueness in products?
They stand at an amazing point in time where the Neuro and Cognitive Sciences now tell us that there are specific ways in which Design Thinking can assist the brain in making better data-informed decisions. A Science at the Center Approach to next-generation Analytics coupled with Design Thinking means they can reimagine what next-generation visual analytics will look like and advance data-driven decision-making across the spectrum of fully automated to human-centric. They can and must think differently about how humans and AI will mesh and interact as part of our DX efforts.
Full Unedited Transcript
Hey, I’d like to welcome you to another episode of Mission Matters. My name is Adam Torres, and if you’d like to apply to be a guest in the show, just head on over to mission matters.com and click on Be Our Guest to Apply. All right, so today is a very special episode we’re bringing on Dr. Martin Trevino on the line, he’s a cognitive neuroscientist and chief scientific officer.
Hey, Dr. Marty, welcome to the show. How are you, Adam? It’s a pleasure to be here. All right, Dr. Marty. So I’ll tell you, we’ve been working hard in labor and we got a, we got an event coming up next week for LA Tech Week where you will be the keynote speaker. And let me tell you, we are thrilled. I know we’ve been you and I have been doing some.
Some work on the backend talking about your keynote, some of the things you’ll talk about and really what, what you plan to deliver to the audience. And we’ll get into all of that. Plus, I’m interested to get your take on, you know, how the VCs and also the C-Suite should be approaching this, you know, this market cycle when it comes to vetting tech investments, which is what you’re known for and one of the reasons we asked you to speak at the event.
But before we get started with all that, Marty we’ll start this episode. The way that we start them all. With our mission matters minute. So Marty, we at Mission Matters, we amplify stories for entrepreneurs, executives, and experts. That’s our mission. Marty, what mission matters to you? Yeah I’m a theoretical scientist and tech executive.
The driving mission in my life really is an endless search for the truth and the art of the possible in, in human computer ai complementarity. Yeah, it’s great. I love bringing mission-based executives and entrepreneurs on the line to share, you know, why they do what they do, how they’re doing it, and really what we can all learn from that so that we all grow together.
So, great. Having Jan on and I guess just to get us kicked off, like what’s give us a little bit more of your background and your history and really what got you set on this path. Like, how’d you get started? Yeah, no thank you very much. The, the, the short version of that Went to, you know, went to college and wanted to serve our country afterward.
And had the rare, rare luck and privilege of being hired by the National Security Agency of the United States. The nsa and arose to the rank of senior technical officer with them. And they at one point they, they said, we really wanna understand how human beings make decisions, you know, particularly high risk decisions with data, so we can better inform, you know, generals and, and admirals and, and very senior civilian leaders can we make smarter decisions with data.
So they sent me back to school and. And a few years of a, of a doctoral program later I came back with a new appreciation of how the human brain makes makes decisions, first off, and then how in fact specializing how does it make high risk decisions with, with data, and how do we trust technology?
And what you find out, you know, in deep study there is that you know, we don’t make decisions like we think we do. And and we don’t trust technology, like we trust human beings. So it I kind of combined that with being a technologist and and now, now I approach you know, complementarity between humans and technology and AI from the perspective of the human brain.
Yeah, it’s great. And I love bringing mission-based executives on the line and entrepreneurs and Sure. You know, why they do what they do, how they’re doing, and really what we can all learn from that, so we grow together. So, great having you on and so from, you know, government intelligence to tech exec, like, like how did give us a little bit of that transition.
How’d that happen? Yeah, I, I, I stumbled and fell down the stairs and hit my head and, and woke up. No you know, served served, had the, had the great privilege of serving my country with some of the most awesome people in the world. You know, supported us through, you know, multiple challenges overseas.
And a few years ago just decided that, you know, It’s a really big world, and the intelligence community isn’t, it’s, it’s a very cool place, but it isn’t the only place to where you can make an impact. You see digital transformation happening you know, we’re, we’re living through another renaissance of AI right now you know, advanced analytics.
And you see, you see companies and executives, you know, really doing everything they can to, you know, to create our future, right? With innovation with. You know, productivity and, and solve, you know, wicked problems in the world. And I thought maybe, maybe I, I can, you know, be lucky enough to help. So, you know, obviously the, let’s just say the government complex one thing, working with C-Suite and, you know, VCs and, and, and other, you know, individuals and decision making positions to make, you know, allocate dollars in funds to technology, different technologies in different tech.
I, I would argue two different worlds. What drew you to kinda the, what drew you to the private sector, like kind of specifically working with that C level suite and VCs? Like, is there, what’s the difference? Yeah, so there. You know, in some cases the differences are very stark, right? Mm-hmm. The, the, the mo, the motive for their overarching motives can, can be very different.
The, the clearest and lowest resolution is, you know, one serves the people and, and security and the other serves the shareholders and investors, you know, but it’s not that simple, right? We, we all tend to work on very wicked problems, you know, problems that are not easily solved. An old mentor said you can thank your father for having solved all the easy problems.
The, the, the hard ones are left. Now to your generation. Yeah, thanks. But no, they’re just different, you know, different problems in some cases. But at the end of the day, you know, we’re really driving the same things, right? Mm-hmm. We want desirable strategic outcomes for the firm, for our people you know, the employees, our consumers, even though they’re greater, you know, our.
Our people and brothers and sisters all over the, you know, all over the country in the world. So it’s just it’s just another set of problems you know from a different lens. And, and I’ve had the privilege of helping some very, very smart people you know, drive, drive their digital transitions and figure out where to invest in, in new models.
Yeah. Well, and you know, you know, Marty, I, you know, I, I can’t have you on the line and on interview and not bring up chat G p t right now. I mean, there’s, it’s in the news constantly. I feel like you know, every, every other day you read a headline where it’s gonna just place. Something or some changes there.
I’m just curious from, from your vantage point having been, you know, working with technology so long, like, like how do you feel that the suite, suite should be kind of approaching or thinking about this next phase of, you know, chat G P T or whatever, whatever this new era is we’re entering? Yeah, so a number of lenses, okay?
Mm-hmm. One, what do we have today? Can very strongly be argued is not artificial intelligence. Let, let’s, let’s be very clear. There’s so much hype out there and people, oh, ai, ai, ai. Okay. If you begin with the perspective of the human brain, okay. As I, as I do, what we have today is not artificial intelligence.
It’s not a general purpose intelligence. They are more aptly called advanced information processing and synthesizing systems. Okay. In very advanced ways, they can take massive amounts of data, okay? In case, case of j g pt, very large language models, train them up and with a series of algorithms and mathematics that correlate, you know, pull things together and, and create and enable, enable this beautiful, you know, large artificial neural net to produce what it believes are the correct answers, right?
Mm-hmm. We’ve also seen how often. They are wrong. You know, very, very, very shockingly so. Okay. But, but the, one of the cool things is they enable trust in a fundamentally different way than a dashboard would. Mm-hmm. And that’s caused for really cool research. Why is it that we trust answers from chat sheet pt, when we would question the data in a pie chart?
You know, on our dashboard when they could be saying the same thing. And part of it might be the natural language, you know, processing unit. But, but as as we go forward, one, understand it’s not, it’s not artificial intelligence and, and general purpose, you know, real artificial intelligence is not a question for our generation.
It’s a question maybe for the next, or even the next century, and certainly terminators falling out of the sky. That, that, that per, you know, those conversations permeate to. It’s the end of the world, it’s the end of the economy. No, just, no. You know, and, and, and how I channel the conversation with, with people who are investing in this technology or bringing in, you know, digital transformations in the C-suite is the overwhelming majority of our.
Exponential order, order of magnitude gains, right? Yeah. Are gonna be from one thing and one thing at its core, and that’s human. AI technology complementarity. Yeah. How can we bring these new models of AI and the coming ones that are, you know, even cooler and very specific driven algorithms, if you will, some very specific functions.
How can we pull all this together in a way? That, that’s gonna compliment the, the, the human brain. And, and produce and produce something that’s awesome. That right, that’s gonna do innovation, design, those big things. We will replace people, you know, to certain levels, but, and it’s, you’re gonna get 10 or 20% improvements in productivity.
But that’s all incremental. That’s just incremental. I mean, it’s good. And they need to, you know, moving boxes, you know, performing rapid calculations back and forth. That’s fine, but, The the overarching way, we are going to get order of magnitude improvements in problem solving and rate of return. Okay?
Return on investment is gonna be new models of combining humans and technology. Yeah. And what do you, and I, I wanna go maybe a step or two further into this idea of digital transformation, because I feel like sometimes maybe the, the term digital transformation and, and you know, AI and all these things, they kind of get, you know, overlapped or kind of.
Throw in the same conversation, but, but they’re different, right? Like, cuz there’s different levels of digital transformation, whether it’s productivity, whether there’s, I mean, for some companies to take it to its very basic level, digital transformation can mean, you know, going online and finally selling their product online, right?
Things like that. Like, so maybe can you from, from your vantage point, give us a little bit of insight into just digital transformation in general? Yeah. So again, I tend to focus at, at the higher level yep. With how are the advanced technologies going to made up with human beings in a way to be seamless extensions of the human brain, right?
So we see examples of that or, you know, even the human self. So we see a couple of good examples. A few years ago NASA. Built a, a artificial intelligence bot if you will, but really machine learning set of algorithms defined new planets based on you know pictures from their telescope and an nasa, an NASA scientist you senior technologist, technical data science type.
Stood up and said, this is the, you know, one of the most sophisticated machine learning compilations we’ve ever put together, and we can just run it by itself. And of course, someone said, well, you know, maybe we wanna put this out to the world and have human beings even novice astronomers who have, you know, big, wonderful telescopes and, and have and love doing this.
Should we get their input too? And they said, no, no, nothing is ever going to beat this, this machine learning algorithm. Nothing. And so they turned it loose and it went out and found several hundred planets. But, but you go back and they, and they did the math and they said that this is not enough for the amount of space that’s out there.
We, we, we can prove mathematically there’s a lot more out there. And, and of course the, the, the data science types will just be wiled well, No, you know, the machine learning is, is, is, is the most awesome thing ever created. Well, so NASA did the beautiful thing and they put it out to the world for amateur astronomers.
And the amateur astronomers went and found, I believe it was 300 more planets in this one small space that the AI did not find. And, and it was one of the, you know, very high end. Most beautiful examples that humans and computers not only. Don’t compete with each other, okay? Mm-hmm. They are complimentary and they are also fundamentally different.
You know, the human brain and what we have today with advanced information processing systems, they are categorically different. But if we make the two of them and we can find. New models of mating them together. Right. We can do absolutely phenomenal things. A lower level example, digital transformation is restaurants today.
So, you know, go back I’ll date myself, you know, go back 20 years ago. And you walked into a restaurant and you met a smiling face of hostess. And that person had a you know, a a, a board with a, you know, with a, with a reasonable marker. And they had to scan out looking for, for, you know, the open tables.
Yeah. And then they went back and they tapped the server on the shoulder and said Table at 42. Yeah. And then they turned in a paper ticket. Okay. Today what technology offers, you know, state-of-the-art restaurants is so beyond that, right? How do you make a reservation today? Well, you use OpenTable or any one of other mm-hmm.
You know, 10 other apps, right? So they know when you’re coming so they can run simple, simple queuing. Algorithms that tell them exactly how many people to walk in at exactly what time. Mm-hmm. And exactly what the wait will be. All the guesswork is taken out of it, right? Mm-hmm. So how many fewer angry guests, because you’re missing the, the, the amount of time they have to wait for a table.
Far fewer. How much stress on that host person or two. Far less. And then the server, they don’t have to go tap the server. They set the server, they’re down, they have a tablet, they tap it and the server gets an, an awareness that a table was sat at, you know, table 42. And even the manager’s made aware that this person, and they can, they can also judge the number of tables that person has based on their, you know on their strengths that are inputted by the manager.
Mm-hmm. And everything is linked to that, right? The ordering system the food replenishment system. Every meal that they take into account has the exact amount of corn, green beans, and meat that was used, and that can be referenced to how much is left over all their shrink can be automatically determined.
Wow. Right. Yeah. Revolutionized by entirely new models of human, human technology being put together. How many people lost their jobs at restaurants? Well, some did. Yeah, some did. Cause there are restaurants, you know, I, I, I fly a lot. And there are restaurants and airports as you go in and it’s just the little, you know, the iPad and you can order things on the iPad and one person brings it out to you.
Mm-hmm. So, you know, are there changes? Yes. Okay. But I would argue that’s not the best restaurant experience. Yeah. And not, not for me anyway. Mm-hmm. You know, I much prefer a great restaurant in, you know, in the city where technology and humans are combined and I get the best of both worlds. Yeah. So those are two high and a low end example that That, you know, kind of show what transformation.
Mm-hmm. But also, had they stopped, had they had NASA approached? Yeah. The finding new planets from a human AI complementarity model, they would’ve known immediately. To have put it out to human beings, and they would’ve even built the artificial intelligence so that the human beings could, could interact with, you know, with those machine learning models.
So great examples by the way, Marty. And so looking at, you know, companies, I mean, companies, there’s a lot of leaders that have watched this, but they’re, you know, they’re VCs, there’s execs and I think as, as business owners, as executives, we all, you know, try to and strive to make, you know, data based.
Decision making. But as we start, you know, going further and further, where do you find, like, especially when you’re getting into companies that maybe the way the data’s interpreted or the way we’re approaching the data, like, like where do you find there’s some opportunity areas there? Many times? Oh, there’s so many opportunities.
There’re, there’re almost endless, mm-hmm. You know, start with strategy at the highest level. Okay. You define that digital transformation? Mm-hmm. Or you’ll define funding that new tech company, which, oh, by the way, every one of ’em is gonna come forward and say, we have AI at the center of our platform.
Right? Yeah. Just get past that. Oh. Oh, okay. Yes. Now let, now let’s start peeling the onion off. That’s the low resolution version, right? Mm-hmm. When you say, what’s the strategy out there? Now VCs will take a, you know, will take a different philosophy and let’s, let’s touch on that for just a minute. In their magnificent book zero to one, Peter Thiel and Blake Masters layout from a VC perspective.
Seven, seven. Overarching tenants that have to be there for, you know, for you to get to, to, to, to, to really up the probability of returns. And cuz we, they’re very correct. We live in a power law world and what you’re gonna find is one investment in your portfolio is gonna outperform all others.
Mm. Okay. And maybe a second investment is gonna get as much as 50 or 50%. The other 50%. Mm-hmm. And it’s a power law. But it’s also, it also goes to the things we know that the Pareto, Pareto distribution, okay? Mm-hmm. You know, 80%, 20%, right? But what we need from introducing a deep understanding of how human beings interact with technology, what we can approach it from a technology first, right?
You know, will this thing provide unique insights, right? Will it, is it revolutionary technology? Mm-hmm. Will it have enduring value? Okay. Those things are right that they, you know, that, that they put in their book. They’re phenomenal. But we need one level deeper is my thinking. Now, we need let’s call it a first principles underneath each one of those before you pour money into this, right?
What are first principles? Human technology complementarity that are centric, right, that are centric to the human being. And that one of those let’s just a couple of ’em that the human brain, when it makes decisions, The, the, the centers of the brain that make, that make decisions do not also control analytic functions.
So the part of your brain that makes a decision, it controls emotion and trust, but the part that conducts data analytics and analysis. But you know, and another tenant when updating your mental model, we use six times more information from we, we believe to be true than what we just saw with our eyes. So someone who says, well, we’ve created a whole new set of dashboards, okay.
You haven’t fundamentally overcome this new first principle, right? That should be underneath, underneath that revolutionary concept that you know, that, that, that that’s out there, right? How are you overcoming this? Right? And, and so one answer like chat GT is they’ve overcome some of that with a trust factor.
The new interfaces and the natural language processing overcomes the human brain’s resistance to trust in, in some forms of technology. So that’s, that’s pretty cool. And then you go further, further and further. Yeah. So that, that’s part of that, you know, from a, from a digital transformation perspective again, we made, I will, I’ll be inflammatory.
We made a huge error in the way we approach digital transformations, and then we approach it from the technology. From a data science you know, lens and, and, and we know this to be true, right? You don’t need a, a, a doctorate degree for this. Yeah. Talk to any exec. Tell me about your digital transformation.
Oh, and the launch into the technology, the cloud, the ml underpinning it, right. You know, you know, here’s how we forward phase to the customers, la la, la. When you say, oh, oh, okay. That, that’s the technology internally, how are you? Mating it to human beings. And do you, do you have, do you have a human factors component to that digital transformation strategy?
What’s the human factors analysis? Right. Because if you wanna build the, the most awesome new models of human computer, AI complementarity. Mm-hmm. You had, you have to begin with the human factor. You have to begin with the human brain. And we so often begin in the, the exact opposite. And, and, and the level of knowledge is very cursory, right?
So if you say, how do you build trust in data, right? You want people to make decisions. We wanna be a data driven organization. You wanna, you want to drive, drive, data-driven decision making into the DNA of the firm, right? One of those you know, over spoken things in the last 10 years and you said, okay.
How are you creating trust in data? And unless you happen to have spent, you know, many, many years studying this mm-hmm. You, you just generally don’t know. And so some people say, well, well we, we create traceability in the data. Traceability doesn’t build trust. Mm. We know that from study after study. We’ve seen that at the decision suite where data scientists or, you know, business intelligence specialists will present all the data and they’ve got, you know, beautiful analytics and beautiful graphs and charts and even look at a compelling story.
And the decision maker after listening to all of that, still looks at them and says, yeah, I hear you, Adam, but my gut tells me to go that way. Yeah. And I’ve learned to trust my gut, Adam. So good presentation. Ladies and gentlemen, we’re gonna go with my gut. Yeah. And you’re sitting there saying, what? Wait, wait a minute.
We did all this work. We did all this. What happened? What happened here? And you’re right. And, and you know, that was one of the things that embarked me on this career and, and what you just saw was that complex dance of things happening in the brain. Mm-hmm. Of how we analyze data and how we make decisions on the tactical level.
Right. The implementation level. There are many, many things that we can do. Again, with, you know, with some, with some of these newly developed first principles, right? That, so we’re bringing 3D into visual analytics nowadays. Mm-hmm. And and someone says, well, what’s the value of 3d? And say, well, the human brain learns through movement.
It learns through vertical, vertical, horizontal, and hierarchal explorations of the world we live in. Mm-hmm. Okay. And it does this through movement. Well, there’s no two dimensional traditional dashboard that allows you, allows you to do anything but click from one graph to the other. Yeah. And that’s helpful.
That’s helpful. But it’s a huge barrier between, you know, technology. There is a barrier. We, we, we overcome it in many ways, but again, we resist the data in many types of decisions. So can we, one, can, can we develop user interfaces that allow our analysts and people to explore data in exactly the way that the human brain.
Learns, and that’s a whole, that’s a whole different set of, that’s a whole different beginning to the problem than, oh, we’ve selected this technology and this stack and, and, and here’s the data that we’re getting. Great, but you left the human being out of it. Hmm. Well, Dr. Marty first off, I already know as we’ve been, you and I have been working with each other and kind of prepping for what’s coming next.
So, just for everybody watching this on June 7th Dr. Marty’s gonna be flying out to, to LA for LA Tech Week, and he is gonna be doing the keynote for an event that we’re holding. Just to give everyone a flavor of of what you plan to, to bring what, what, what can the, what can the audience expect Dr.
Marty. Yeah. Well some inflammatory statements like this, I’m in. Hey, you’re a wildcard. I love it. Yeah. I’m like, I don’t, most tech guys I get on the show are I see on stage. They’re not wildcard. You’re a wildcard. I love it. Yeah. No I, I will make the argument that the single overarching determinant of uniqueness and success for all current and new businesses being funded for the next few decades is one thing.
Human technology, AI models of complementarity, that is where we’re going to get the overwhelming majority of our goodness. And so maybe we can change thinking just a little bit from its current to something, to something that helps us discover, you know, the art of the possible. Yeah. All right. And I’m, I’m gonna cut you off there.
Why? Cuz I want people to show up. Man. We’re not gonna, we’re not gonna you all and give it all today to them. But switching topics from that. And, and by the way, for everybody watching this, there’ll be links and other things like that so that you can just really click on the links and you can see the registration page and l love to have you come out and to see you and to meet you in person.
But that being said, Dr. Marty I mean, you got a lot going on. There’s no, no shortage of. Of C-suite execs, V suite VCs that you work with and really tech ideas and whether it’s AI or otherwise that people are vetting. And I know that’s one of your specialties. Just have to ask, I mean, what’s next?
What’s next for you? What’s next for, for your career? Oh wow. Do really awesome things for people every day. You know, so I, I currently work with a couple Silicon Valley firms that, that range from, from cyber, cyber and enterprise risk. Right? How can we fundamentally, At the enterprise and its uniqueness differently.
So, you know, bringing in events, concepts like high dimensional space and, and associations with hypergraphs and three dimensional exploration you know, to to that, that will fundamentally change their, their, their, their digital, their digital transformations. Mm-hmm. You know, to, can we develop this, this entire set.
Have underlying first principles for, you know, for those investing in companies for venture capitals, they will give them a wonderful set of questions to dive two layers deeper, you know, than, than, than what’s traditionally presented. You know, at, at like a, a series A, you know, you know, type, type you know, funding event that, that are gonna help them pick out that.
That one or two firms that are going to yield 10 x you know in terms of their investment because that, that’s what makes or breaks. Mm-hmm. Fantastic. And and Marty, if somebody is, if somebody’s listening to this and they want to follow up and they want connect and learn more and to follow your work, I mean, what’s the best way for them to do that?
You know, LinkedIn is always fantastic. I’m on LinkedIn and I think you guys have, have the link. Yeah, if you’d publish that. And again, I’m, I’m one of the easiest guys to talk to. I, I’m not concerned you know, with minutes of my time or, you know, anything like that. So, so just send me, shoot me something on LinkedIn and say, Hey, would like to talk more and I’m happy to, happy to have a Zoom coffee conversation with anybody.
Fantastic. And we’ll definitely put your LinkedIn link in, in the show notes so that our, our audience can just click on the link and head right on over and connect with you. And thank you. Speaking of the audience, if this is your first time with Mission Matters or engaging in an episode, we’re all about bringing on business owners, entrepreneurs and executives, and having them share their mission, the reason behind their mission, you know, why they do what they do, and what we can all learn from that.
So that we all can grow together. If that’s the type of content that sounds interesting or fun or exciting to you, we welcome you hit that subscribe button because we have many more mission-based individuals coming up on the line, and we don’t want you to miss a thing. And again, Dr. Marty meant really been a pleasure.
Look forward to seeing you next week. Thanks again for coming on the show. It’s my honor. I look forward to seeing you, Adam. Stay out of trouble.