Luis Perez-Breva Explains How to Be ‘Productively Wrong’

big data, artificial intelligence, et cetera is progressing. I think you will find this to be a surprising and fascinating conversation. UH. Luise approaches the idea of UM problem solving an innovation in a different UH concept and a different order and in a different construct than I think most people think of in terms of technology and UM innovation. He really looks at this as a problem solving an iterative process as opposed to something driven purely by technology or purely

by capital UH. He in fact, he specifically thinks most people are doing this wrong because they're focusing on the concept of big ideas as opposed to thinking about hunches and small incremental changes that solve problems as opposed to what we discussed, the grand pivot that seems to be so popular these days in Silicon Valley. So if you're at all interested in venture capital or technology or the future direct action of tech, I think you'll find this

conversation quite fascinating. With no further ado, my conversation with Luis Perez Breva. I'm Barry Riholts. You're listening to Masters in Business on Bloomberg Radio. My guest today is Luis Perez Breva. He is an expert in the process of technology innovation. He holds multiple degrees from multiple countries, including Physics,

Business artificial Intelligence from Spain, France, and the US. He is a professor at m I T and he is the author of Innovating a Doer's Manifesto for starting from a hunch, prototyping problems, scaling up, and learning to be productively wrong. He currently directs the m I T Innovation Team's program and advises organizations on artificial intelligence and innovation. Luis Perez Breva, Welcome to Bloomberg. Thank you, thank you for having me. So you've said a number of things

that I find fascinating. Let's jump right into the comment you made about impossible projects. You said, I'm drawn to projects that look impossible. What are impossible projects? And if they're impossible, what can you do with them? Well, they're they're really not impossible. They just looked like that, And it's mostly because of the way we think, we think in our silos and our disciplines, and so a bunch of stuff then all of a sudden, so it looks like no one knows how to do it. But everything

you love about the innovation started out looking impossible. So give us an example of something that looked impossible but turns out not to be My favorite one because it's been a long time and it's still mesmerizing is Henry Ford. But I'll bring it to the present for you. So, if Henry Ford was life today, what he would have said is that he wanted to make jet planes private jet planes affordable that because that's what a car was back then. So this seemed like a completely impossible thing

to do. Actually, no one believed him. Everyone thought he was wrong, and yet he somehow they didn't change the America forever. So that kind of problems, whether they be that big or smaller, but that people cannot seem to be able to bring together what draws my attention every single time. And I noticed you said affordable. It's not just that he wants to manufacture cars. He wants to

manufacture cars. It's such a scale that they were affordable to anyone working in his factories that that seems to be an interesting That's the key when you actually look at the history of him before, as historians tell it, just different from how you may read it in a book. In a business book, you hear that all he wanted was make cars affordable because his experience living and growing up in a farm made him realize how hard it was to make supply runs to the city. So that

was the objective. Everything else, the scale, manufacturing, finance, increasing wages, was a means to an end, which is make cars affordable. It's like problem solving all along. So let's let's address problem solving a little bit. The title of the book you reference being productively wrong? How is a person productively wrong? You know the way. I've actually even come to realize

that even more ever since I had kids. When you're a kid, When we were children, you spend all your day being fundamentally wrong, trying things out and mostly not getting everything right, and just you don't really care, just experiments, just experimenting, No one seems to care, and so on. Then eventually we learned just enough to believe that everything applies by formula, and then we destroy the magic. Effectively,

we destroyed the spirit of angry. But the way we seem to learn as humans, and this we know from neuroscience from how hard it is to do ourtificial intelligence and so on, is by fundamentally being wrong, so officially many times, until we figure out what was wrong about it. So we don't learn by being right or by formula. We learned by fundamentally being wrong. I'll give you one quick example which I learned from my daughter. When she

was starting to play violin. She played out of tune pretty much time until one day she didn't, and then she figured out when violent itself was out of tune. And this happened gradually to a point that she never actually realized that she was playing out of tune until that one day in which all of a sudden she did. So she actually learned to play in tune mostly by

being wrung every single time. And I bring this up because playing an instrument is such an intuitive thing depending on how you learn it, that it brings this about how we learn even when you're an adult. So I started to learn violin with my daughter. Really, and you know, the violin is unique, or or at least different from a piano or something where each note is defined. It's fretless, and so you could be off by a quarter of a tone. It's a very different experience. But that leads

the question. We think of child's play as things kids do for fun, but you're really implying that child's play is a form of experimentation and learning. Yeah, or you can look at it the other way around. We adults should play much the same way, because that's how we acquired a bunch of things we use every day. Language, your surroundings, your sense of taste. Everything was acquired that precise way through experimentation. Is experiment wrong play, but it was play. Now we grow up and we kind of

are afraid of being wrong. We need to be right, and so before you know it, you're just not using your brain for what it was, for what it evolved to do best, which is learning through this kind of play. Let's talk about innovation a little bit. What is innovation and how does it work? Funny that's innovation has been said to me so many things. It's an overused word.

So I'll tell you what I think innovation is. Innovation is the end result, meaning you go about trying to solve some obstacle, solve a problem, and uh, most people will think you're wrong, and one day they stop thinking you're wrong and they'll call it an innovation. So innovation is how people certify what you did. But at first it looked preposterous, it was fundamentally wrong, and did it because you felt there was something to it that other

people couldn't see. Give us an example of something that was preposterous and then adapted by everybody I love. I'm just going to use big examples. So let's see how prepostors they wear. And hope logical isn't today. So Bill Gates talks about a computer in every desk and at the end at they were every home. Right. So I'll go back to right where there are maybe a few main frames here and there no internet, no no internet.

No one knows what to do with it. There isn't even spreadsheet yet that would come a bit later you can read the entire history I mean at the time and and somehow today because you have a computer in your pocket, and probably another in your desk, and another at home, and maybe five iPads, and who knows what, maybe your phone is a computer as well. Now it seems perfectly natural. So that is what makes it look like an innovation. It's even better because by the time

it's gone through its cycle, it actually looks old. The idea of a computer and every desk and every home seems old all of a sudden, And yet it was a brutal innovation that has created so much economic progress in all sorts of fields. Like we're sitting in a room where there's a cusident of computers. The idea itself was prepators in nineteen every actually so prepastors. It didn't matter. That's fascinating. Let's talk a little bit about technology and innovation.

But I want to start with the idea of ideas. Where do innovative ideas come from? It's that's a trick question. It's a true question because over the last two years we've placed such an importance on the word idea that in my book, I decided to give up on it. And I actually talk about hunches because now ideas have become so important that it's actually burdening most of us. We think we need to come up with this innovative

idea before we even do anything. So what's the difference between an idea and a hunch other than people don't judge hunches as harshly as they might judge idea. So the basic difference is an admission practical sense. Nothing ideas come from pretty much anywhere. And as I've told you, the best ideas start out being just preposterous combined two

things that that are not meant to go together. But from a perception standpoint, from how you go and see people pitching ideas and investing in ideas, people should not be investing in ideas. People should be investing in project in organizations, in in dreams if you want, if you want to take it to the extreme. But ideas just they are born bad. All ideas are effectively born bad. Ideas are born bad. Yes, go into more details about

what why do you believe all ideas are born bad? Well, you know if you truly have one of those ideas that in the futures, when someone will say they were innovative right, What you realize is that there is a lot to learn ahead of you, and it's just impossible for you to have figured it out all in your head. So the first thing that needs to happen to that idea is change, because it's in your head and it doesn't exist anywhere, and for it to exist, you need

to scale something up to the world. And it would be amazing if you had figured everything out perfectly in your head. So you need to almost assume that your idea interesting, enticing as it seems to you, it's just fundamentally wrong in more ways than it is actually right, and that's how you figure out how to get it the scale. So, in other words, an idea is almost a conclusion, and you need all the intervening steps to

get there. And by the time you're done your idea we only look like the initial idea to you, but to no one else. So how does one develop innovations hunches? I don't I won't say ideas. How does one develop the skills to produce better hunches and lead yourself towards greater innovation. It's actually much simpler than people think, once you remove the obsession to come up with the earth

chattering or disruptive idea. Then you realize that all you need to start is something that doesn't seem to be right, So you might as well start by putting trying to put together two things that actually don't simp to fit together. And then that causes you to ask the question, Okay, this doesn't work why, And as you start from there, you realize that all you need to do is continue to put these pieces, these parts together, to prove to

yourself that this will actually not work. Slowly, you increasingly either build up scale just give up on it, mostly because you lose interest. And that's fine. That's how we humans operate. It's actually very simple way to do it, and you can practice it. So as you practice, you start to see opportunities that are essentially emerging things that you and perhaps only you see that are meant to go together. But then what else does just yet? That's

quite interesting. What do you think the differences between ideas and execution, because they really are two completely different skill sets. There are two completely different skill sets. But you know, my experience when when I've taught over years, is that paying too much attention to those two words actually gets you into linear thinking, because then it because as you to ask the question when once should I stop ideating and then start executing, meaning to linear, not to line,

flexible or exactly. And what we know from innovations, and every single treatise and innovation tells you this is that innovation is fundamentally nonlinear. If you endeavor set you up to try to predict the future so that you know when to start executing, you are starting the wrong way. So what I tell my students and what we the way we teach it and the way I explained in the book is your challenge is to scale up something that's the only thing that matters. And you cannot scale

up by mostly dissociating an execution from idea. Execution will change your idea, and your idea will change what you execute on continuously at different scales. So is that from whence comes the infamous pivot or you get all these startup companies and Silicon Valley and they look like they're going to be one thing, and then halfway through suddenly the point in a different direction from a fundamentally similar

technology or idea. But but the problem they're trying to solve seems to be something completely different, any original idea. I love that you called it infamous pivot. It wasn't me, you did it. Yes, well, haven't we heard that phrase a million times in the past. You know a lot about the innovation we're just chatting about. It depends on

from where you're looking at it. So if you are at the receiving end of it, and you're just looking at what a company does without all the knowledge of what they're doing every day, it looks at as though they change direction all the time. Now that's just a perception from the outside, which means it's not what you

should do. It's what people think you're doing. But what you are doing is effectively continuously changed incrementally how you're thinking about it, reformulating it continuously, and as you start to get traction in different directions, it seems as though you're doing different things. But every time you look at any of those stories, the way they really happened, not

the way they are told. There was no pivot. Nobody started pivoting and changing in their mind every ten seconds, And the advice to pivot constantly makes no particular sense to me. So they're they're working on something. It's evolving, it's rating over time, and suddenly, I think you use the phrase traction, something starts to gain traction and scale. So what we're hearing after the fact as a pivot

is really a normal evolution towards something that's that's working. Yes, except that some companies have taken as a mantra to take pivoting as a as a thing they do. And so every now and then they say they try to cause them themselves to think, how should I change direction today? And that's a really hard question. Actually, the field of entrepreneurship, which is different from innovation, is full of really strange questions. Give us another example we've just discussed, when should I

stop be the aating versus executing? I don't know how to even pose that question meaningfully. Should I pivot today? Maybe maybe not? I just I have no data, no evidence to kind of grasp some other advice. You hear a lot of this focus on the user, but really, if what you're doing is that new, is there already a user for it? If not, you're just making it up.

By the way, I'm all for making stuff up, I'm not for ignoring the fact that you just made it up, right, So it's concealing the assumption you make is actually the big mistake you would do. So there's an apocryphal story about Steve Jobs and the iPhone, and people at Apple kind of challenged what he wanted to do, saying the user doesn't have any idea what what a glass phone is going to be like, and Jobs famously said, I'll

tell the user what they want. Is that what we're talking about in terms of not focusing too much on the user experience and instead, if you really want to innovate, you have to forget about the user for a while. So I think that we went back ten years ago, right, maybe fifteen, and anybody came to us and said you need to be listening to more podcasts, the answer would be,

what is this person talking about? Right? So I don't think you can expect anybody, neither the innovator, nor the entrepreneur, or the investor or anybody to predict the future, right. And so at some point, if you truly are looking for or five years ahead, and you're going to users and hoping they have an answer of what the future beholds five years had, I think you're delivering yourself like nobody, nobody has that answer. Someone has to make up that future.

That's the way I hear what Steve Jobs might have said. Right, I wasn't in the room. So let's talk a little bit about what's going on in the world of innovation today. How can we tell if a good idea or a hunch is going to succeed? That's a question I get every semester, and the answer, I'm afraid is you can't. You just got to try it out. Just try it out and see what happens. Now, the good news is

that you also get to define what success is. So there's no way you can fail unless you make it a purpose like many people do, meaning meaning that, well, how do people define success if they have an idea? Well, what I propose people do, and what I talk about in my book is, you know you have a hunch. How about we try to figure out what problem is it that you three you really think you're solving. There's

a way to think about problems that's pretty straightforward. And what I tell my my my students and they look at me funny, is that, uh, if an alien species where to come down to Earth and show you the solution, would you even know that that's actually a solution to your problem, because if not, then you will never find it on your own, and that's how you fail. So you start working backwards, what do you think solves the problem, and then before you know you realize you actually get

to define everything. So you continue to do that, and before you know it, you succeed. Maybe it's a different way you thought you would, but that's how you succeed. You try and you go through scale. You're the director of the m I T Innovation Team's program. Yes, what does that program do? What are its goals? And what has come out of that program? So it's a very usual entity in academia. A few years ago we thought about, well, you know, we want to etiquate people to actually meaningful

to innovate as a career choice. How do we do that? So most people think that you you want technologies from academia to live and have an impact in the world, and of course we want that. But what I really want is for every single student at m I T and wherever I've taught this now worldwide, to learn how to do this as a career choice, and then they can choose to do it or not. That's their choice.

So I thought, how do we do that? And it occurred to us that you could actually get a Mighty Technologies, which is a real tangible thing, and then ask students from all domains. So I may get an engineering technology and the students are from science, business and architecture, and then try to teach them what it actually means to innovate with that tangible starting point. And the process is very simple. So someone in a lab at M I. T.

Has discovered that a new thing is actually possible. So I of my students, Okay, somewhere they're hidden is a superpower. We just don't know what the superpower is. And obviously that superpower is going to solve a problem somewhere. We just don't know where nor what the problem is. So we need to solve for those two things. So people are really approaching the concept of ideas and innovation backwards. They're starting with the idea as opposed to what problems

to solve exactly. And that alone takes me about a month for STEMS to appreciate that we're actually turning things on its head because it's actually simpler problem and solve it exactly. And of course there's no change we're going to find the perfect problem at the start. But as long as you understand how to do it, you can do it increasingly more quickly. And that's what led me to believe that you could actually practice this even when you don't have a technology at the input, which is

what the book covers. Um. But beauty is that the result is actually very clear path to action to take this technology, change it and address a problem that even the researchers hadn't hadn't about. And so a bunch of startups have actually come out of this, even though it's not my objective, right, My objective is to educate students, so they do this continuously. Right, So you write in the book that people and again to reference Silicon Valley,

they do it backwards. They as soon as they have an idea, they try and um get funding, They try and go out and raise capital. You suggest not to do that until way later explain the thinking. So there's the ways to think about about that. Um, I think that I while you have is an idea, which as you know, I think they tend to be born not so great, not to say bad ah, and you obsess

about pitching it and selling it. You're putting yourself in the worst negotiation position you can possibly ever be, which is someone else is going to decide what your company is going to look like. They may give you money, You may look like great because you've got the money, but then you may soon realize your idea. UH needed a whole different process. So I asked in the book, I asked everybody who has an idea to think of themselves as investors zero because the first time he's going

to be spent by them. And instead of spending six months touring vcs or asking for money, what can you accomplish in those six months to spare yourself the agony of going for money with a bad idea, and in the process, can you actually make that idea better? And

that's what I mean by exploring at first. Now I've got to say that nowadays, UH, and a good friend of mine alerting it to this, UH, nowadays capital has become cheap in the sense that there's an abundance of capital for investors, and so now it's even harder for people with good ideas or with a desire to produce good ideas to not be drawn into this frenzy of asking for money and then going and creating a company on top of something that's really maybe not that great

starting point. The name of the program you wrecked has the word teams right in it. What is it about teams that's so important? And doesn't that kind of contradict the idea of the loan inventor toiling away in his lab or her lab until late at night. Interesting, So I'm not sure the lon inventor at the lab will actually become the innovator, right. Sometimes they do somethings they don't, But in order to become an innovator, they have to

become something else, right. That's something else is they are required to talk to other people for some purpose, even if to understand what the world looks like outside of the lab and learn about the stuff they haven't learned in the lab. They have to be ready to change the idea. They have to be ready to use science or technology or their discipline, whatever it may be, a different way, uh than they were used to do it in the lab, or if they are in a company,

in their company. Right. And so once you do that, sometime along the process, there's got to be a team because there's no company of one, right, So it not so much that the team is important is that you need to learn how to connect with other people and let other people go and along the path discover how to interact with people to actually bring the idea at

the scale. So we call it teams to emphasize the fact that we're going to bring people from different disciplines together and they're going to learn because remember it's a medicational experience, that's a trick. They're going to learn how good or bad they are and interacting with other kinds of people, and they're going to learn how to either change that or they're going to learn who do not to work with again in the future. Let's talk a

little bit about your career in academia. How did you find your way to m I T the first time. So I was finishing my master's degree in Spain and I decided I wanted to try something new, and a friend of my family said you should go to the United States, and I said, okay, And so I looked around and I found these people working on a mix of artificial intelligence and math, and I really wanted do that, even though I was just a chemical engineer at the

time or not even that yet. And so I sent an email Ah, asking to meet, and then another and then another, and I kept on being told a bunch of things, but none of them was no. Everything was a challenge. So well, we may not be able to get you a visa, and then I answered, I'll figure that out, even though I didn't know how, and blah blah blah. You can imagine. That went for nine months. And at the end of nine months, I responded to

this professor who's since become a good friend. Uh, you know what, Just tell me now, I said, because if you don't tell me now, I'm just going to keep going at it. And I needed to say no, Ah, And they don't like to say no. Dude, that apparently not. I thought that I thought he would. I thought he would immediately say no and then uh, And I told him, you know, I have lots of offers to stay around here and do my master's thesis. I just want to go work with you. I've told you all these things.

I've said we would sort it out, but say no, or I will continue forever. I will never graduate. And so he he's said to me, Okay, give me three days, which was not the response I was expecting. I was respecting the response no, and then he in the end

he said, okay, you can come. And that was the first time I made it to M I T, mostly as a visitor to work on artificial intelligence, being a chemical engineer, which was the first time I realized that what your study should not constrain you, h makes a lot of sense. And yet I'm not sure everybody would actually realize how much they led their background constrain them

instead of actually empowering them. So so that's the way I first made it to a M I T. And ever since they've come and gone six or seven times, right, so you gotta you ended up getting a graduate degree from M I T. Yes, But later first I did a startup in Silicon Valley. I actually spent some months at M I T. Then they offered me to stay for a PhD. I applied and I got accepted, and then I said, no, I'm not doing it. I've studied for too long. I need real world experience, and I

went need the startup in Silicon Valley. What was the start up to look itself? Phones in case of emergency actually exactly to this day, when you call in any one one in most of the states in the United States. You were being located by the company we founded with the technology WIN and oh, that's fantastic, it's phenomenal. And then and you're using triangulation between cell towers or some

formula based on that, I'm like, we're using AI. So it's artificial intelligence based on factors, not the old way, which was the way. It turns out the triangulation would actually not work, but it would take me a long time actually to persuade you that that doesn't work. But it actually links to a lot of what I discovered since that the way we use science is very constraining, we use it as a model. We tried to feed

the world to the science. But with AI, you can do it the other way around, and you can make science much more playable. And that's what I've been doing for years in my reality. And then you find out where it takes you, and you find out where it takes you, and you can actually work and operate directly on problems, which is what we didn't did then back then. The real problem was and this is like already twenty years ago, so you've been located by AI ever since

to help you. Right, So we realized the only problem was that we didn't know where you were and you needed us to know, and then we don't care. If triangulation works, right, the problem to solve is where are you when you call anyone one? Right? That's it. If triangulation that work, then we need something else. And there is data, and the data we have is rich because

it contains everything that's surroundings. So we built an AI that would actually learn from that data how to locate you for the purpose of any one one of course, and so that worked out to this day. It's the most phenomenal technology that does this. It's incredibly scalable and it works and it looks near magical because it's not based on model thinking or science based thinking of those. Science plays a role, but it's not the way we

typically use science. So after that company, did you then go back and get your PhD from M I T or I went back to I did everything in the wrong order, So I got I did a company in an AI, and then I went to do a pH d in AI. People typically do a NBA, but somehow I I got my cables crossed. Do you have a business degree? Yeah? That I got after before I actually

did the company. So so as I said everything in the wrong worder, I did my PhD. Half the way through my PhD, I needed more challenge, so I took a year of sabbatical from my PhD and went to live in France, and I continued working for my company, and at the same time, I took a degree in quantum mechanics because I thought quantum computing was going to be hot, and I needed to understand that hot. It is becoming hot. It's actually a fascinating field and uh.

And then I went back to m I T, finished my PhD, did a number of startups on the side, and as I was leaving m I T I was approached by a faculty who had taught me, who had seen me teach in context, and said, would you help us set up this program innovation teams that needs revamped to truly do what it's meant to accomplish. And you've done this, he said, because you've you understand you have

a PhD and the sounds to be rigorous. And at the same time, you've done this in the real world with real technologies from scratch, and you actually are not afraid of any deep attack as you can imagine with physics, engine chemical engineering, and and and intentions as a background, I'm not scared of technology anymore if I ever was right, uh, And so I see all kinds of fantastic technologies and I actually can help through that process. And that's how

I stayed in academia. So that's a really interesting arc of a career. M I t is well known for having a very savvy, intelligent student body. What have you learned from your students? All sorts of things. First of all, that the better I get, or actually should put it into reverse, the the more I see them do what I teach them, the more I realize I can teach more. I know that in the general world sometimes less is better,

but might t more is better. So so I've gotten to actually teach so much more throughout a semester than I thought possible before, to the point that I now believe that I can anybody, no whether their background, can be trained to innovate starting from what they have. And that's why I wrote the book. And that I learned from the students by actually pushing the envelope. Um. The other thing I learned, and this is shocking, This is still shocking to me. Student body changes every two years.

And what I mean by that is that the mindset of students changes radically every two years. I would have thought it ten years or five or generational twenty every two years. If you have not completely done a blank slate in your head as to who the people are in front of you, you're going to miss the bout. So is that a function of the state of the economy. Is that a function of technology and social networks? What's driving that those changes? Or is it just a perennial backdrop?

Things are always changing. I've tried to all sorts of explanations in the back of my head. Sometimes I thought it was emergency of cell phones and so on. Uh, sure those play a role, but there is something new like that every two years. So every year, every two years is different. Every semester is different already, But every two years you need to entirely clean the class and redo it from the grounds aps so that you can

actually communicate meaningfully with students, which makes me better. Right, that's how I get better. That's pretty pretty wild. Let's let's talk about innovation around the world. Where are some of the most significant innovations being created globally? It's hard to answer that question because if you believe what I've what I've said about innovation before, we won't know it until it's done, and then we'll call it an innovation in hindsight. But what it's doing it looks preposterous. So

so let me ask that question slightly differently. We're very much biased, and here in the United States we think of ourselves as a capital of innovation. Is America still a leader in innovation compared to its recent history? If you were to talk to a number of historians and economies, they would tell you that innovation is over. Actually, every thirty years someone says that, uh so, there is something

very unique and amazing about American culture. And I say that from the perspective of someone who came here for what he thought was just a year and could not getting stuff to leave, actually because I love it. Ah, American culture combines ingenuity with a kind of attitude, with a trying things out and not being afraid to not get things right the first time. And noticed I avoid the word failing. Well, I was gonna say I look at failure in the United States as not a black

mark that it is elsewhere. And if you look at some of the world's great innovators, but it's Steve Jobs or Henry Ford or Toms Ederson. All of them have had substantial failures and that failure didn't operate as a constraint for them going forward. And I don't maybe this is my hometown bias, but I think around the rest of the world, I think failure carries more of a stigma than it does in the US. So I've had

to do a lot with that question. So I think the word failure, which has become incredibly popular in the last ten years, and only in the last ten years, is being overused and it doesn't mean exactly what what I perceived my students and the people I see in the United States actually do. So failure is is the word the rest of the world actually use it to

describe their fear. Their fear. Yes. So the first time I went and I started teaching abroad, Uh, they asked me what about failure with this kind of panicky eyes, and I said, what about it? I said, it makes no sense, it has no meaning, And they looked at me and said, what do you means that? Yeah, why do you even worry about that? I said, like it's just the world has no meaning. You try it, it works, or it doesn't work. That's it. And this doesn't work,

you move on to the next. Either fix it right or you figure out you can't fix it. But then it probably means you are no longer interested and you move on. So the keyword failure that speaks over years. He's actually destructing you from what I believe the true American values, which is you just dry it up. It works, great, doesn't work, you fix it, you don't care. You move on. We have been speaking with Professor Louise Perez Breva of m I T, author of an Innovating a Doer's Manifesto.

If you enjoy this conversation, be sure and stick around for the podcast extras, where we keep the tape rolling and continue discussing all things innovation. Be sure and check out my daily column. You can find that on Bloomberg View dot com. Follow me on Twitter at rit Halts. We love your comments, feedback and suggestions right to us at m IB podcast at Bloomberg dot net. I'm Barry rit Halts. You're listening to Masters in Business on Bloomberg Radio.

Welcome to the podcast. Thank you, Louis for doing this. I find your work fascinating and I have so many questions to get to. I don't even know where to start. What motivated you to write the book? Because writing a book is a challenge, and then going out and talking about it afterwards is a slog. What made you say? I know, I'll put three d and fifty words pages of words down to sum up my past twenty years worth of work. So I can give you two stories,

the one forward and the one in kindsight. So looking for what they had a clue what I was doing. Let's be seriously. I figured stuff as I go because learning is my thing, so so I didn't know what it would take to write a book, nor how much more work there wasn't after you're turning the manuscript that second that's second half is you think you're done and it's like, oh no, you've got six more months of work.

But in hindsight, the motivation was the true motivation was that I've been teaching this for now a decade, and uh, I know of all the problems, confusions, paradoxes that forming my students heads, and the month I spent trying to disabuse them of prejudices so that they see it's actually far simpler, which doesn't mean it doesn't take a lot of work. It does take a lot of work, but it's actually far simpler to do and you can actually practice it. Whereas people start to think about are you born,

are you made? And strange questions. That was what motivated me to say, Okay, fine, I need to write this down because there is no way they could ever get it anywhere because all the other books say ask you to fail, and I rather they succeed. So so that was one piece. In hindsight, what this allowed me to do is realize why I've been camping in academia. Uh. It kind of helped me bring a bunch of thoughts together.

So if you look at my funny story arc, there's just one constant all throughout, which is at I've always made computers do my bidding. I've always used computers ever since I was eight to have them do what I wanted, and I've been obsessed about how to make that dumb machine work for me forever. So and every time everything I've done has actually, to some degree or another involved computers.

When I got into AI, I want to take this to the next level, which is I need AI to have me do and continue and play with the science I still don't know, so I can reach further and make up new stuff. Um so I never got that from my PhD, and I spent a number of years trying to figure out what I thought I was missing, which is, how do you actually solve a real world problem? What does it actually even mean? And how did I

bring this into the equation? So that motivation is what kept IN going for the last ten years, though I could not phrase it as such until I finished the book and said I figured it out right. So now I can actually go to that next kind of AI that no one is thinking about, because it really is obsessed with data as opposed to what we can have computers do for us, which is what I really want. So you you wrote that innovation has been commoditized. What do you mean by that? I actually mean it in

a in a in a very good way. It's like it's never been so easy for you to get another kind of education altogether. You go online and you can find information about whatever you want. You can build any kind of contraption, you can put it to your service. The science were done, what everybody else has experimented before. This was not available when I was a student. Actually, I was one of the first people to play with the Internet when I was a student in Barcelona, and

this was not there. If it had been there, it was fantastic. Why I go through all these degrees and so what what I what I feel is like if people understand how easy it is to put technology to your service, which I hope I can get to do eventually with this form of AI technic science and technology more playable, then it's never been easier to just drive your education based on the project you want to do today. And if you actually understand how to scale things up,

you can actually make a living of it. And I think it's a responsibility of all of us to take advantage of the fact that innovation or the tools for innovation have been so commoditized, to bring it to all of America right and kind of erase the chasm that exists there today. So let's talk about that scaling up. Because you could solve a problem, but that doesn't mean it's going to scale. How do you take a solution

to an issue and and make it scale. This may not sound immediately intuitive because there is nothing intuitive about scale app so ideas, per say, don't scale. What scales up is organizations, organizations organizations, which is that you started with five people and doing a few of those. And it's not about how many you do. Is being able to do the same for less money with more people in some way. So you get to fifty people and you have more products, but each of them cost you

less money. This should not be logical, right, doing more products should cost you more money. So even though we've gotten used to the idea that with volume comes shippening up, you know, kind of scale, we call it that way, but we don't really understand why. I'll tell you an example. You make eight cookies, you make sixteen cookies, you're spending more money. Actually, the only reason why you're not spending much more money is because you're still using the same women.

So it's not necessarily intuitive about what it means to actually scale things up. But what scales is the endeavor, not the idea, And so what you need to do is think about it the way astronauts go to the moon or International Space Station, which is the only way you can scale up is you catch. If you catch everything that would look like a failure at the skate at which is only an ever and so you don't fail,

So why do I bring astronauts? But that's what they do, according to Chris Hadfield, as I explain in the book and many others, they just go through every excruciating detail about what will kill them right, and they plan for it.

They either suggest modifications to the engine, they come up with protocols, They do something so that by the time they bring their endeavor to scale, which is getting into the International Space Station, they are prepared for whatever may happen, so that if it all fails, it's because it was not predictable. That's what it means to actually achieve scale. And then it may well be that the problem your targeting just lives at the small scale. That's fine. You

learn that through this process. You talk about leadership and innovation. Why is it that we see a lot of people who create ideas, who create haunches, who create concepts, aren't always the best person to lead organizations to implement the scaling of those ideas. And pick pick a company, be it it could be Uber, it could be the Weinstein Company, it doesn't matter. It seems that the people who create or or crucial to help drive the idea, only take it so far and there are better people to manage

those scaling businesses or or or Is that wrong? I think it's neither right nor wrong. It's true for some people. Steve Jobs was able to, Bill Gates was able to. In the case of Uber, it didn't happen at least now that we know, maybe you know it will happened like with Steve Jobs and come back, come back in the future. It's hard to make those general statements about people.

But it's also true that some people, and have plenty of friends that have shared this with me, entrepreneurs that that just like to build it and get it going and bringing to a given skill and then they're better after doing the next one than they are actually doing this, And that's actually a career choice. But I also want to distinguish I don't know who the innovator was in the Uber story. We talked about the CEO, which may be the entrepreneur, but was he the innovator he was

the founder, we don't know if he was. So it's those two are necessarily always the same, right, And sometimes I would say that in the case of many daring innovators. They've actually started some and they've stayed. In some cases they have actually gotten. Bosniak left Apple and he was key to the innovations that god Apple started, as was the Steve Jobs right. So I think it's more of a personal choice and a career choice than it is

a rule. So there's a there's a general fear in in the population about technology and that automation is taking jobs away. I don't get the sense you look at it quite that way. What do you think about big data AI and what it means for the broader economy? Is technology gonna turn us all into um unemployed or is technology going to help us continue creating the next generation of jobs. So on that when I'm rooting for human so I think we're going to see amazing things

coming up. I would also like to bring up what we actually call technology, because the definition the t at M I T what God m I T started is the idea of using science and knowledge to help humankind reach further and gain control over nature. So if it is not helping us, it's not technology at least according

to this definition. So the way I and many of my friends think about technology and what I think it's my next passion now is what we need to do is make a better effort to bring this technology so that more people can play with it and benefit from it. And that needs to be done. It needs to be brought to scale. I think we don't haven't done such a great job at that for the last ten twenty years,

but we can. But I don't think that on its own, big data or AI the way you see it implemented today is going to do any of those things that the fearmongers say are going to happen. So what does it mean in terms of artificial intelligence? Can we really help machines acquire intelligence in a human like fashion? If you have to look out fifty or a hundred years, what what are these machines going to look like. I'm

actually going to surprise you with this. The idea of artificial general or generalized artificial intelligence was proposed at the beginning of the field, and the presumption was that if we ever got a computer to beat a human a chance or strategy game would have achieved general I started dificial intelligence because back then we thought that that was

super hard for a computer. And I guess what we now know is that you didn't need artificial general generalized division intelligence to that, even though the progress has been remarkable, but it's only been machine learning. And it also means that we're done in an odd way. We need a new objective because the way we define that generalized started difficial intelligence, which is the touring test and these problems problems is gone. I mean, like we don't know what

we're doing anymore. So I would rather think of an AI that actually helps us directly in the sense of we need a new objective, and to me, the objective is AI that helps us the way Jarvis helps Tony Stark become a superhero iron Man. So in that movie Iron Man, everybody talks about Tony Stark and whatever, but the great, great, great tool is Jarvis, which is the

AI that powers the suit and helps Tony Stark build stuff. Now, imagine you had some kind of a system that's way more powerful than Google but still is helping new problem to alve things so that you can accomplish something new. That's what we need an I to do. At least that's what I want an eye to do. So that that's quite fascinating if, in other words, are our focus is really on the wrong thing, and we should actually be thinking about AI as a problem solving tool and

not a means in and of itself. Am I am I getting that right? I think? So that's the way. But by the way, that's actually much closer to the way you are benefiting from AI today. So, with the limited capabilities of Netflix in terms of intelligence as broadly understood, you're benefiting from how Netflix collates what other people have looked at without having watched a single one of those movies Netflix itself, and you're getting new recommendations of movies.

The same for Google. You're actually accessing Google typing a few keywords, and you're getting to see how other people have sorted out the web. Right. So the way AI has been helping us has already been that way, even though it's limited, it's still only machine learning. One of the questions that someone I mentioned somebody I was interviewing you, and they said, ask him if innovation has become concentrated in too few hands? Oh, I think money has become

concentrated into few hands. Uh, money in terms of capital for technology or money generally or both money generally. And what you see is that um, if you don't have good ideas that you've actually kicked the tires for yourself

before going out for money. You're just going to be subjected to how those people think about what innovation should be right, and so you're going to go through a path that may not be the best now because money is more concentrated, either it being companies that are pushing more research I would say, not so much innovation, or

in the hands of a few philanthropists. UM, you sort of need to figure out a way to make a case appealing that even though it may not match how they think about innovation, they agree with you that the problem can get solved. So if you do your homework, it's okay. But I think the problem is that money has gotten too concentrated in the hands and that may create the perception that it's harder. So let's let me

pull an example out from the real world. UM. Google very famously tells its engineers you could take of your time one day a week and think about problems that have nothing to do with the work you're you're doing. Can you organize and structure a workforce to be innovative that way? Or is are they just wasting time? What? What does that directive from management actually end up accomplishing.

It boils down to what you asked them to present at the end of those Uh, time is spent on on ideas if they are just presenting ideas, I don't think it's efficient. But you can actually guide that works an entire workforce that actually to innovate continuously if you place the interest in can you please tell me how we will direct resources to prove this thing that you have at the next scale. And that's actually a different

way to think about the innovation. We've actually done it outside of m I T and proving it to myself that you can truly get highly motivated people and prepare them to do this and innovate continuously in this way and create the organizations that work. Whenever we think of innovative companies, the same couple of names seemed to come

up over and over again. I was struck not too long ago when someone had asked Jeff Bezos about the Amazon phone which failed, and instead of getting defensive about it, he very much embraced it and said, we need more failures. If we're not failing frequently, then we're not trying enough stuff. We're playing it too safe. I want to see a lot of things tried, and by definition a lot of them are going to fail. I think that philosophies is

quite insightful. What companies or leaders do you look at that you think understand innovation and know how to uh solve problems using technology and are likely to be the innovators of the future. Uh. It's always hard to know exactly what's going on inside the company, right. We have unusual visibility unsum and no no visibility thought or not,

so it's hard to make a blanket statement. The few examples we know of our companies that are still starting up and so they are not so good at keeping secrets,

and so you actually get to see more. So there's a lot to like and not to like about how things are developing from many I certainly love everything Jeff Bezos does, and even though I will not use the word failure because they kept moving, they just moved on, I agree and sympathize with the idea of try, and of course if everything works out, you're not trying hard enough, right um so uh I am I admire the way Elon Musk has gotten around to create the company he

has created, but I've actually developed the appreciation by reading the biography more than what the news say about about him. I am not particularly impressed by any web company that we see nowadays, even though there is lots of incubators and things out there. I actually feel that they've proven kind of the opposite that if you just start with have web idea, it takes very long, it is too costly,

and uh, no one makes a profit. So I'm actually if at all they've proven that there is a way to the web companies if everybody thinks they're easier and only create perceived value but not real value. Well, Airbnb, I guess you can hold out an app company like Uber. What about Netflix, they pretty much exist. Well, Netflix is from a different breed, right of companies. They started physical right, so sending DVDs, sending DVDs and which, if we remember

the idea, sounded ridiculous. It sounded completely ridiculous at first. Actually, Netflix, which I talk about in the book, is a great example because they too have been exposed in the press, and every four years someone says they're ridiculous and they're wrong, and then it four years later it turns out they weren't so that's why the mechanic is so great. But Netflix also shows you the idea that there's a difference between coming up with an app and just counting users

and actually scaling up a company. The way Netflix gets to where it is today is by actually becoming various different companies on the way. When you look at what they actually do today, they produce movies, right, and the day they sold DVDs, actually they rented div so they went from DVD rental to content streaming to content manufact

and some things are kept along the way. So in their case, it's a very clever use of machine learning that's kept along the way and allows them to think about the next scale up, and that's the piece they keep on growing. So they are building a very incredible

capability that gets to be incredibly versatile. It's like the perfect example of proper financial wisdom, which is, you know, you want to diversify in the face of uncertainty, You want to actually diversify and not do the opposite, which is focus just on one idea and spend all your money in it. That sounds financially wrong advice, and so uh, there's companies like that that are incredibly nov that if that, we just don't know what they're doing. Apple, for instance,

is what is the prototypical example. The typical question is with Steve Jobs, are they still innovative or not? I don't know the answer to that. But in the meantime, while we're not looking, they became a services company, right, so they keep on reinventing themselves. So rather than looking at who tries and fails a lot, which implies a degree of visibility onto their process that we may not have, just look at how subtly they actually change the company

they are. And every time you look at it, it seems like perfectly incremental. And yet it's completely different Amazon the Everything store than producing movies the elastic cloud along the way. Uh, they use what they have to change who they are and we may not see how they do it, but that's what happens every single time. So what about Facebook, which is a web or I guess you could go on an app company, but it's certainly

an internet company. Um, and they have a bunch of other properties like Instagram and go down the list of things that they've purchased. Or are they a company that's innovative or they is social? Their only thing and and that's going to be Um. They'll either live or die

on how popular social networks are. I've got I mean, I have to confess that when it comes to companies that are just purely social, I have a hard time understanding, ah why they have any competitive advantage, also whatsoever acceptive where they are already, which means that if someone else comes around with something that's fundamentally different, it might be wiped out. But that's my own shortcoming. It's other shortcoming

of Facebook. Uh uh. In the case of Facebook, I see lots of ideas, they see lots of chaos in many ideas, many companies, a use of machine learning for many things. But I also see mostly an advertising company right in everything they do, much to some degree like Google, though Google has tried more actively to branch out from that.

So how long can we withstand that? You know, if you were in in in business school ten years ago, they would have told you that the secret of Google was that they ended the banner tyranny of the Internet. You should remember that in the nineties Internet was just mostly ad banners and eventually some content. Now look at the Internet today, it's exactly the same as it was a bunch of ads over there of stuff that most likely you bought already, and that's why how they know

you like it, and so they advertise it again. So we're getting I believe we're getting to the same point. Maybe I'm wrong, which, as you know, I don't care much about. But so when I look at these companies, I just don't know how to assess what they're doing. And this is not to say that they are not doing great things. Maybe tomorrow Facebook will make an announcement and I'll say, oh, look, I was wrong in Bloomberg, and I'll move on right. So you keep coming back

to the idea of not caring about being wrong. And before I get to my my favorite standard questions I ask all our guests, I have to ask you one more question about that. Most people have so much ego tied up in being right it prevents them from um either admitting error or trying things that have a low probability of success, or just you mentioned earlier, you're just

playing and seeing what happens. How did you evolve to the point where you became very comfortable with I know failure is a loaded word, but being wrong, trying things out, moving on? I don't want to claim massive insight or foresight on the matter. So part of me I'm just I wasn't aware that I was supposed to not care. I mean, part of it was just I don't know something about my upbringing that that and then seriously, if I don't get to know every three days, uh, it's

not my life. I've been told no about the craziestuff I proposed to do or literally every three days. Some of it is crazy, some of it I was right. But even super dear mentors that they take in high steam have told me time and again, what are you doing? This is not the normal path? And I tell them I just don't understand really the normal path. The fact

that it's normal doesn't make it logical to me. So call it that my head is wired the opposite directions because I'm dyslexic and so certain things that seem obvious to other people are not obvious to me. But I don't claim to know to have a secret that all of a sudden I got inspired. Maybe it was just wrong one too many times to realize that it's not that bad. But you don't take no as I think most people's intended intention. When someone says no to you.

It's almost the challenge. Yeah, what I what I tell you my class two students is that as long as no one is hurt, and that's very important, you should not take the first note for a note, right. And that doesn't apply to relationships, right, it disapplies you're talking technology, abology, business. You should not take the first note for an answer because sometimes people need a second chance to think it through. And so maybe two right is a good good starting

point to get yourself trained. And then I develop all these funny games. I I call him credit Kid carate kid tasks for the movie. You probably remember the first Credate Kid movie in which there was walks on, walks off that stuff, and he the kid learned karate by actually kind of waxing cars and painting fences. So I developed a few create kid tasks to kind of train them to be around. One of them, I asked them to just call a pizza um, and I mean some

pizzeria and ask for a doctor's appointment. Uh. Of course they think it's going to be embarrassing, but it's just a phone call, right, and uh, and then once they do it, you don't know who's more surprised if the person who called or the person who receives the call, right. I asked them to please not have used the pizzeria just to try it once, but to get the feeling of put themselves in in the shoes of that extress

moment and realize it's not that bad. Right. And once you realize that, and you train yourself to these tiny mistakes, they call them near missus. If you want, uh, then you get a whole different sense of what the actually means to be wrong. It's the example I gave you earlier. If the violin is out of tune, it kind of still sounds Okay, it's not as great, right, But it's not. It needs to be really bad, bad, bad for you not to even recognize the song, and after a while,

that helps you play better. So let me jump to my favorite questions. These are the ones I ask all my guests, UM, tell us the most important thing that people don't know about your background? Uh? How do people normally answer to that question? Well, usually it's some little tidbit that people um that is surprising. But you have a lot of interesting, surprising things in your background already.

So I learned the program by accident. My mom had taken a class in a computer science because it wasn't and she went next door and took a class and we had the K computer and she told me, look, they've given me the master remind her game only that needs to be called in the computer. So the first time she wrote it in the computer for me, and I played, but it was one of those computers like really old, like you could not say so every time you want to play, you have to red to re

write it. And so I wrote it and then wrote it again, and then wrote again and modified it so I could win always then and before you know it, I actually knew how to cod it. Basically, I was eight years old, mostly because I just wanted to play um Mastermind. And that has defined the way I think about AI and everything I've told you before in ways that keep on coming back to my head. The ability to play make things that seem complicated playable changes how

we actually approached them. And that's define why I keep on jumping through field seemingly in a way that's quite fasting. Tell us about some of your early mentors. Hard to say. I've been through so many countries and I've met so many interesting people, and uh that it's it's hard for me to say it. Clearly the person and M I T who who you had a long email relationship before you has to be a significant mentor. He's a significant mentor. We haven't spoken in a few years now because directions

takes different ways. Ah, but that's much later in life, right, So, uh, he was certainly a great mentor. More recently, what was his name, Tomaso Poggio Um, he's still a professor at m I t UM. The recently Charlie Cuney has been a great mentor because he sort of told me I think you have a book in your hands when I

wasn't even thinking about it, and I guess I did. Uh. And even earlier a lot of family friends essentially a family the friend of my family was quoting earlier that I was talking to me and said, what are you going to do? The next time, I said, I don't really know. I haven't learned enough to what I want to accomplish. And he said, you you you don't know what you're doing. You need to leave this country and go to the United States. And said, okay, So I guess he's had me in this path So who um

in the worlds of innovation? Who influenced your thinking? What philosopher, thinker technologists affected in a fundamental way your thoughts on innovation? Many I'll give you two. One is Thomas kun Um, which is very known in the United States and hardly known in Europe. Surprisingly, in Europe people talk about paper, which is the competing school of thought. Uh. I think Thomas kun explains the scientific method in a way that resonates with me. And Papa doesn't Um what is that?

Papa is formulaic and uh And Quen essentially admits one thing that I've come to come believe as a mantra, which is that the beginning of any new theories fundamentally ill conceived, h mostly wrong by any traditional standard, barely work works, and yet somehow it becomes a standard afterwards. And that beginning starts with people putting together what seems preposterous, mostly because they have a hunch that something isn't working.

I'm putting my own words on Kim, right, So so don't Qun doesn't use tounch and I'm not sure he would agree with the way I interpret his writings. And I think it's a real hard read a book to read it took me. I read it at first, at the age of twenty three, I didn't understand it. I only understood it at the age of twenty nine when

I read it again. And by the way, that's because your brain keeps are involving, so you're not it's not fully matured and able to understand every single thing until you're close to twenty nine by some of the latest research. The other thing that actually influenced me is that the opposite extreme. I've had this question in my head about why does Warren Buffett. Why does Warren Buffett not invest

in innovation? Not technology startups, but innovation? You know it should he should mean, I'm not, you know, I'm not want to say what he should do with his money, but it's a fascinating question. It's a seems like a bit of a dichonomy, right, but he invested in long term only for value creation, and he also does philanthropy right, and innovation is all about removing obstacles to progress in the long term that I actually create benefits from society

and value. So it's like he should be investing in that, and yet he doesn't. I'm not I don't think he should. But trying to answer this question has cost me to think about more carefully about what innovation actually is and how it is different from just creating a company or doing a startup. It's much more ambitious. So you mentioned qun tell Us about some of your favorite books, so

those change all the time. But the latest breed is The Hitchhiker's Guide to the Galaxy, which I keep I'm coming back to, and and the reason I love it is just it's just absurd in such a profoundly logical way that it's just hilarious. Another a book that I devoured was The Martian two years ago when I first got it, and I've still read it again because it is the way science really is, not the way it is being taught. It's not about the model. It's about

using nature to help you. And that book, every page is literally a person trying to survive making science and nature work for him. Right. It's a series of problem solving, problem solving, no solution real and and and lots of what you might call failures. But really, if he failed, he died, right, So that was not an option. And and the mechanic of the book, the richness of it. Even if you don't fully understand the technology, you can

tell the story. It's enormously vibrant. And the last book I keep on coming back to every now and then is what if? From random unders sure and you can tell the trend right it's I'm techie. I love sci fi, uh because I want to create the sci fi so it becomes real and but just a touch of absurdly. And it needs be absurd because otherwise you cannot get good ideas. They need to look absurd at first, not because just because and this is something I realized over

over time, ideas look absurd because of your training. They were not absurd per se. So if your background taught you to ignore certain things and assume certain things, anything that challenges that will look absurd only until you show it works. So, since you came into the fields of filling the blank artificial intelligence innovation some years ago, what has changed? And is for the better or for the worst. Many things have changed. I'll give you one for the

better and one for the worst. We've become way more siloed. Siloed, yes, and that creates enormous amount of inefficiencies in medication, in investing in innovation that I myself avoid with IT teams, which is crossed disciplinary across the entire institute. Um, that's that's something that I believe it's going to change. At

the same time, the opposite has also become true. You could indicate yourself on whatever online if only you had a project or a means to guide you with a project to acquire that knowledge, which is the reason why I wrote the book to start with. And so those two things have happened. One people more siloed and more formulate.

More students asked me today for formulas for innovation, and they did ten years ago, which makes no sense because if there is a formula, there is a recipe, it's then you're just going to bake the same cake someone day. How is that an innovation? It's a great copy by all means, eat the cake, But um, it's not an innovation,

right so Um. But then on the other side, more and more people I believe can actually start to learn on their own and ignore recipes or said models because there is such an abundance of information that wasn't there ten years ago. And AI is only making that or will only make it if I get my way would only get it make it even easier to put that to your service, so you can solve whatever problem you anty. Tell us what you do outside of the office to

relax or for fun. I spend as much time as i can with my kids for not just because I'm a family man. It's just they're hilarious, but it's it's but it's not going with my kids as in traditional playing. Of course, as you can imagine, we build contraptions. I'm having them build computers. There are five and eight. But it's okay, it's good early enough. Um So having them assemble the computers, we are doing all sorts of absurd things. Ah. And we played together and I'm even learning violin with

both of them. Uh. And that's incredibly enriching for me. So if a millennial or recent college grad came up to you and said, I'm interested in a career in technology, innovations, startups, what sort of advice would you give them? Interesting question. So my first advice is find a problem, right, because technology is what you use to make the problem go away. Right.

An innovation is the process of doing that to some degree. Uh. If you can find a problem and look harder, but if all you intend to do is get money, you know the current cycle is going to end. Eventually, it's going to become impossible to create this multibillion dollar investments that take ten or fifteen years to show a profit, if not more. So that's not going to be there forever. And when that goes away, if you just adopt that view of the world is not going to help you.

So just find a problem and work backwards from that problem to get the education you want, rather than obsessing about what do I become computer scientist, stores, so on, so forth? And our final question, what is it that you know about technology and innovation today that you wish you knew years or so ago when you were first starting out. So I think of myself as a different person every so often, So I'm not sure what myself of twenty years ago really thought, right, I can't chat

with him to figure that out. So I'm not sure that that's what I wanted. But what I wrote in the book gives me the answer. I think I was looking for what I didn't know what I was doing, So I guess that what I did is that answered. If not the question, I would have phrased what I thought I needed to understand to make it to the next leap for myself, and that has been a really enreaching experience. We have been speaking with Luis Perez Bravo. He is a professor at m I T and the

author of Innovating a Doer's Manifesto. If you enjoy this conversation, be sure and look up an Inch or down an Inch on Apple iTunes, overcast, Bloomberg dot com wherever final podcasts are sold, and you could see any of the other nearly two hundred such conversations we've had over the past few years. We love your comments, feedback and suggestions right to us at m IB podcast at Bloomberg dot net. I would be remiss if I did not thank my crack staff who helps put together this podcast each week.

Medina Parwana is our audio engineer and producer and keeps me honest each week and moving along as these conversations progress across ninety minutes. Taylor Riggs is our other producer slash booker. Michael Batnick is our head of research. Attica val Burne is our business producer. I'm Barry Retolts. You've been listening to Masters in Business on Bloomberg radio