Artificial Intelligence And The Impact To All of Us With Appvance CEO, Kevin Surace

There’s no denying that Artificial Intelligence will take the lead in the future economic landscape, and the race among companies to harness its immense potential is just getting started. For enterprises to dramatically improve the quality, performance and security of their applications, while transforming their efficiency and output, they need the world’s first AI-driven, unified test automation system: Appvance.ai. Kevin Surace, the CEO of Appvance, reveals how his company is revolutionizing software testing with their premier product, Appvance IQ. Mr. Surace discusses AI, robotics, automation and the future of jobs – all from the perspective of an innovator and technology pioneer.

We have an interesting show because we have Kevin Surace here. He’s a CEO, innovator, artificial intelligence expert, board member and speaker. You look up the list of what this guy’s done. It so impressive.

Listen to the podcast here:

Artificial Intelligence And The Impact To All of Us With Appvance CEO, Kevin Surace

I am here with Kevin Surace who is the CEO of Appvance. He sits on seven boards and has been awarded 28 US patents. Kevin has been featured in Businessweek, Time, Fortune, Forbes, CNN and the list goes on and on. He has keynoted hundreds of events, from Inc. 5000 to TED to the US Congress. It’s so nice to have you here.

Thank you for having me, Diane. I’m happy to be here as well.

This is going to be interesting because you have done so many things. I was having a difficulty trying to figure out what I wanted to ask you first. You are so known in Silicon Valley. You have pioneered the first cellular data smartphone. You’ve done so many different areas in AI and all that. AI is such an interesting topic for people that we’ll start there.

Everybody loves to start with AI, don’t they?

I know you do music, work and all the things that you do. There is focus and fear of AI right now because of the Stephen Hawking comments, Bill Gates comments, all the things that people are talking about, safety and the future. Nobody knows more about what’s going on in high tech than you in my opinion. Can you touch on the things that most people ask you about? You said that’s what they want to start on. Let’s just go with that.

I’m sure there are a lot of people who know a lot more of Silicon Valley than I do, but I’ve been here since ’85. They’ve built, sold, and killed some companies along the way. It’s what you do here. I was fortunate enough to meet all of the amazing people. AI has been on and off in Silicon Valley and in tech circles for more than 50 years. This is not something new. In the last handful of years, it has come back alive. There was a nuclear winter of AI that happened several times where people just abandoned the field and ran away.

Lately, with some new math, cloud computing and in leveraging something called GPUs to make things faster, we’ve been able to do math faster and some deeper math. Also, we’ve been able to model the brain a little bit better and so we’ve got things like deep learning that have changed some of what we can do. Speech recognition, speech translation, image recognition in the last two or three years are hundreds of times better than we thought we would ever achieve because all the old algorithms couldn’t do that.

We can learn from all of the image, data and voice information that we have recorded and that’s something new. Where computers struggled to get better than 70% image recognition accuracy up to about five or six years ago, now we are at around a 97% or so. It’s better than a human can do. That’s amazing. We learned how to make the computers train themselves and that was the important difference. If the database is large enough, the set of data that we have is large enough with answers, it will go train itself on how to get better and better. It scores itself and judges itself.

As scary as that sounds, it’s actually incredibly easy and I’m going to give you an analogy. The analogy is everyone knows about the mouse in the lab. When the bell rings, it runs and gets the cheese. The most didn’t do that on the first day in the maze. You put the mouse in the maze and on the first day the bell rings. It doesn’t know what to do, but eventually the mouse is starving and makes its way through the maze. Eventually in time figures out that when a bell rings, there’s cheese on the other end of this maze and it can run over, get the cheese, eat the cheese and come back and be full. It figures this out over the course of weeks and months.

We figured out how to program computers to learn by trial and error - by literally giving it a carrot. Click To Tweet

Think about that as AI. What it’s done is it had months to try and try again to figure out where the food is, but eventually it scores and it realizes where the food is. It knows that you hear a bell, you go get the food in this corner, and you come back. It has found its way. Let’s put a second mouse in. Let’s pretend the second mouse is you and me. We’re dropped in and the second mouse sits there. It watches the first mouse run and get full of cheese every time a bell rings. The second mouse looks at the first mouse and goes, “That is absolutely brilliant. That is the smartest mouse.”

Actually, that mouse isn’t any smarter than the second mouse. That first mouse just had two months and thousands and thousands of trial and error to figure it out. That’s all we’re doing with deep learning. It’s what babies do. They try and try to move from a crawl to a walk. After thousands of little bits of tries, one day, they stand up for a few seconds and then fall. That’s interesting and then it gets a little longer. Over the course of weeks and months, they walk and so they learn by trial and error. We figured out how to program computers to learn by trial and error by literally giving it a carrot. That is all we do is teach it what a win is and the loss is and the rest it just tries millions of times. It builds up something called a neural net to remember how to get to the good paths versus the bad ones. That’s a very fascinating thing.

It’s not that scary when you think about it, it’s just like training a mouse. It’s modeled after that. The last thing is that it happens to be good at very big data problems. Google recently announced that they’ve had a trial running at San Francisco General and at Stanford to evaluate incoming patients and decide to see if they could is the patient likely to live or die in that hospital stay? It’s very interesting. They’re not telling the patient because that’s not the point. The point is can the computer figure it out? You’ll say, “How could a computer know?” The first thing is that doctors already do this in their mind. It’s the edge of the bed test. They look at a human that might be morbidly obese, has been smoking for 25 years and now has a touch of pneumonia.

They’re already thinking, “I’ll try,” but the chance of this person going out the front door versus the back isn’t very high. We fundamentally even you, I or our audience understand those basic tenants, but it gets very complicated when you start to look across hundreds or thousands of data points. What they did is look 186,000 of incoming patients’ data of who survived and who didn’t and because it could look at 186,000 patients, it found other pathways that indicate if this patient is going to make it or not. It’s just a big data problem that’s too big for your mind. That’s the way we’re using AI today.

It’s not what you see in the movies. It is not what people are trying to scare people about. AI has no real emotions. We don’t know how to create emotions. We don’t know how to create love. We can program in Alexa to say I love you too, but it’s fake. It’s just the program. It is just running that tax that we recorded. That was work I did back in General Magic. We invented all of that work that eventually went into Alexa, Siri, and everybody else. All the personality worked eight, nine, or ten, pounds in there and everybody else that’s licensed to do this work. The net result is we are a long, long way from what we call General AI, which means I can replace Dr. Diane. I can’t do that. The complexities of which you bring to the table, you’re going to have your job for a very long time, as long as you want it. As long as the voice and the ears work, you’re going to be doing this show as long as you want, unreplaceable. Even in our lifetime, we can’t imagine how to get there. It’s that far away.

TTL 225 | Appvance
Appvance: All of us in the software and the vast majority of that software and the enterprise runs the enterprise, not the website. The website is one percent of what they do.

When you brought up the doctor scenario, I think maybe the concern might be in that situation that the computers will decide who should live or die rather than you know what I mean?

I think that might be but we have laws to protect against that.

In terms of what treatment? They’re past this age of Canadian medicine thinking that sometimes you hear about.

Here’s the thing and let’s look at it another way. Let’s say tomorrow you could go to a computerized doctor where there was no human involved. That computer doctor would look at every symptom that you have and immediately request the right set of tests and shortly afterwards give you the correct diagnosis. We’ll just think about that for a second because that will happen in our lifetime. We all know people who have had some kind of symptom. They’ve been to the doctor, the specialists, to this and that, and they cannot be diagnosed. No doctor can figure out what’s wrong. Eventually, someone comes around and says, “I’m sorry, did you travel in the Amazon ten years ago?” I go, “Yes, I did. I think you have this parasite.” They treat them and it’s gone. I know people who have had that.

This is where a computer could not possibly make that error. The problem is a doctor who’s human. We love our docs and yes, they save lives, but they can only remember a small handful of ailments or of symptoms and they can look some things up, but again, that’s a big data problem. It happens to be a great problem for a computer to give you the right diagnosis, get the right tests and ask the right questions and no doctor ever asked that person, did you go to the Amazon. He wasn’t even thinking of that. They’d say, “Maybe you just can’t digest. Maybe you’re lactose intolerant.” No, I have a worm in my stomach.

Here’s what I want you to think about AI. AI is becoming very good at theory, repetitive and vertical tasks. Everyone in business today is focused on AI completing vertical tasks that will augment humans. It will replace some people and we’ll talk about that, but it’s augmenting most human work because it can’t replace humans in everything else that we think about. It can’t replace humans in our emotional intellect but in certain vertical paths, it’s very good. No different than Excel as a spreadsheet is way better than a pencil and paper could ever be for us, but we’ve come to just embrace that. It’s what we use.

You have to finance things, create graphs or charts. I go to Excel, I put in the things, I create a table, I’m done, I don’t want to do that math. It does it for me. This is just an extension of that, except it’s very good on millions of pieces of data and learning how to do those really well. That’s all we’re doing. To us it looks incredibly intelligent but it’s actually only good at performing one task. Anyone of these things and it’s only incredibly intelligent at that one task.

To us it looks incredibly intelligent, but it's actually only good at performing one task. Click To Tweet

It’s interesting that this brings up some of my research emotional intelligence for my dissertation. I’m researching curiosity. Some of the things that’s in my current research is what holds us back from being curious. Some of it I’ve looked at is technology doing things for us. What impact do you think that technology has on us either that we’re afraid to use it so we don’t bother or it does it for us so we don’t bother?

It’s the old adage of 20 or 30 years ago. If you are playing a game with your friends to answer obscure questions, you would have to have that mental knowledge. There was no place to go look it up, etc. It was pure statistic, or who was on the baseball team in 1946 who hit the home run in October and May? I don’t know. Google has dumbed us down because Google will just answer all those questions. Arguably today, Alexa can do the same thing just by asking many of those questions. We’re no longer curious about trivia questions, you just answer them. It’s no longer useful for the human mind to spend any time on it.

The same is true with phone numbers. Do you remember twenty years ago we had to remember a lot of phone numbers? Remember ten, twenty or 30 of them anyway. Do you remember party lines? It would save $6 a month with a party line and pick up the phone and your neighbor was asking you to hang up. Now, trivia has been answered. That’s a closed book but it doesn’t keep us from being curious about other things that there are no answers for like where did we come from? How big is the universe?

There are a lot of things that we can ask about. “Can AI help us with X?” is a curiosity question in Silicon Valley today. Often the answer is no. It’s not applicable to that but sometimes now the answer’s becoming yes but only if you have great domain knowledge. That is we’re moving to a time when it isn’t about developing the AI algorithms, that’s important or the math. A lot of that work has been done. It’s about how do I apply that to this problem? That’s really hard as it turns out because you need domain knowledge about the problem. You need clean data to even analyze the problem and come up with some answers. Then you need a practical UI to get it to humans. There’s a lot of work in what we call the applied AI, which is applying those concepts to real human experiences that are going to be useful, but none of this will be applied to EQ and so I love the fact that you’re focused on that.

As I like to say to college students because they’re graduating, “The big question is how can I become a VP and a CEO?” I say, “Look around the room. You’re all graduating from this amazing program. You’re all graduating with high grades probably because of GPA appreciation over the last ten years. Let’s ignore that for the moment and just say that you earned those grades. Everyone to your left and every one to your right has about the same IQ plus or minus ten points. Then IQ is not going to differentiate you becoming a CEO,” and they go, “I never thought about that.” In college and even after college, a lot of people are like, “I’m smarter than the next person, guy, gal.” Probably not.

Humans are in a very small range of IQs and yes, there are the Einstein’s and people at the other end, but in general it’s a bell curve and we all sit plus or minus about ten points, maybe fifteen. It turns out that does not differentiate those who make it to the top. What differentiates them is EQ and they’re not taught it in school, they’re not taught in college, they’re not taught of it at work. In fact, with the advent of video games twenty years ago, they’ve been taught less of it than we used to have to do when we were young because we didn’t have video games. We had to go across the street and make friends with the neighbor.

I do give a lot of talks about soft skills and the importance of emotional intelligence and all the things you talked about. People are hired for their knowledge and fired for their behaviors. I think that there’s so much to be developed. When I was the MBA Program Chair at Forbes School of Business that was the biggest thing I thought that we needed to add and in any of the schools for which I’ve taught. It’s the same thing.

You want to develop critical thinking. You want to develop all these things and as we talk about what computers will do for us, there’s some foundational thinking. That’s my concern a bit is I think that soft skills are the glue that holds everything together because if you start taking education in bits and pieces like people want to learn a little bit of this and of that, but then they leave all the humanities, the critical thinking and the soft skills. Do you see that as the glue or are we going to lose that in the future of education?

It depends on the school. I’m on the Board of Trustees at RIT and we talk about this all the time. It is a core focus. We have an endowed chair of critical thinking. We believe critical thinking needs to be put into every set of coursework in every program because we can’t just graduate kids who code and then they come out, they go to work and it worked. They say, “We’ve got this big problem and we got to solve it.” The kid looks up and goes, “I don’t know how to do that. Give me an algorithm and I’ll code it.”

The critical thinking skills are about problems. I’ll use an analogy. In Silicon Valley, we talk about walking through walls. When you start a company, they can walk through a wall. You stand up and walking through a wall as an analogy to you. We’re together going to invent something that hasn’t been done before and it seems like magic. It seems impossible but it’s not. We’re not going to break the Laws of Physics.

If I came to you and said, “Diane, you and I are starting a company and we’re going to walk through this wall.” Literally, it’s a wall. I can’t walk through a wall. You go run into it. You push against that. You do all kinds of things and you throw your hands up and go, “Kevin’s a nutcase,” which you might. However, I did not give you any limitations on walking through that wall. It turns out it’s quite easy to walk through. You can get in your car, go down to Home Depot, pick up a chainsaw, come back with a chainsaw, power up the chain, saw a hole through the wall and walk through the wall.

If you have the right tools, you can walk through any wall, provided you’re not breaking the Laws of Physics as we know them. Most people will look at that wall and say, “I can’t walk through a wall,” but the people on your team go, “Of course, I can. I can use a bomb, a chainsaw or a sledgehammer. You didn’t tell me I couldn’t use any tools. You just said walk through the wall. I’ll walk through the wall. Give me the right tools.” This is true for all of these things, not just in technology but also when EQ comes into play and that’s part of where you can easily define and figure out who’s got critical thinking skills.

A critical thinker says, “Of course, I can walk through a wall. I just need a sledgehammer.” A non-critical thinker quits and walks out. The chance of the non-critical thinker being successful is already zero because they eliminated themselves from the pool. They walked out. A critical thinker says, “I’ll get a sledge hammer and a saw. Then I’ll get a bomb, an acid and do all kinds of things. Something will get me through this wall.” They’re critically thinking about the problem that you presented to them in. They’re trying different things because they intend to succeed at that problem and that’s a different attitude.

Critical thinkers intend to solve the problem and succeed even through experiment, they’re going to do it. We want critical thinkers. They rise up in corporations provided they come along with the right soft skills and emotional skills so that the people around them push them up and don’t push them out and say, “You’re a critical thinker but you’re crazy. You drive us nuts.” Nobody pushes up the person who drives them crazy.

Can computers have critical thinking skills and if so, will EQ be considered a wall to a computer?

TTL 225 | Appvance
Appvance: The planet will survive. It’ll still go around the sun, whether we survive on it, it is a different story.

Yes. When we look at AI today, critical thinking in the way that you and I are thinking about it is not something AI can do today. Let me explain why. What AI is not good at is learning in one domain and applying it to another. If it learns how to identify dogs versus cats and you give it a picture of a chair, it is only going to choose a dog or cat. It doesn’t know what else to do. It will say, this chair looks closest to a chihuahua. It has no other data to go on. It will be better at identifying dogs versus cats versus foxes versus whatever than a human can, but it will not be better at identifying a chair because it has never seen a chair before. I don’t want to say this is a fundamental problem of AI but remember I said that today in general, AI is very verticalized.

When it learns in one domain, we are not yet good at applying those learnings to another domain. Humans are very good at that. It says, “One time I saw a video of a person using a chainsaw to cut down a tree.” We can immediately apply that and say, “I wonder if a chainsaw can cut a hole in the wall. I also went to a store called Home Depot and saw a chainsaw once. I have money in my pocket.” A human will put the ten different pieces together that you have to put together shown up with a chainsaw, maybe get gas for the chainsaw the whole thing in, and saw through a wall having never sawed through a wall before, kept all the pieces together and guess that it might work. AI does not do that today. There is no guess, it doesn’t know how to do that. It has guesswork and there’s estimation, but it doesn’t know how to apply all of those other learnings to a brand new domain.

Were you able to go and get to the point where it soon will get our memories almost, where you can upload our own memory somehow into a computer and they would have the memory and capability like the reverse Matrix?

Ray Kurzweil said in his first book it will be in 2020, and now he’s saying it’s probably ten or twenty years out. Maybe it’s 2030 or 2040. There are a lot of people thinking about how we extract our memories and put them into a computer. There’s a company out here in Silicon Valley that can do it, but it will kill you so they want to do it at your desk. They think they can do it. I think we’re ten or twenty years away from that, but just because your memories are there, it doesn’t mean that the computer will do anything but play those memories back.

This is a unique human thing we have learned over millions of years or hundreds of thousands of years. For example, we had to know that when a lion chased us, it was bad because the lion ate this other member of my tribe. Then we see a tiger chase us and we know it’s not a lion or an elephant or whatever. We say we don’t know this if this is going to eat a member of my tribe like an elephant probably would but this can’t be good.

Those of us who survived must have learned how to run from animals who are chasing us and how to stay away from the dangerous ones, even if we’ve never seen that one kind of animal. There were certain gestures that it made that said, “Don’t get near me,” and so we don’t for self-preservation. We’ve had hundreds of thousands of years to learn about self-preservation.

It is why humans are very sensitive to certain facial features and why it’s taken a long time for AI, for instance, to create artificial faces that don’t look weird to us because our eyes and our brain can sense even the minutia of facial detail. If it looks wrong, we’re scared of it and we don’t like that. We’ve seen people who’ve done things to their faces that did not work out very well. There’s something that’s wrong. You can’t even put your finger on it. It’s not these things in the wrong place, it’s just something is not right.

Our brains have learned how to figure out when something’s not right because it could be dangerous to us. These are the harder things for computers to do recently. Only in the last year has AI been able to analyze hundreds of thousands of faces and then build up an entire face from scratch over the course of a couple of days, which is a person who never existed. You and I could not tell that that’s not a picture of a real person. It’s that good.

I’ve had people on my show like Richard Stallman, people who have created certain technology and they’re not thrilled with the thought of having Big Brother listening. That’s one of the reasons they don’t have echo devices. Do you feel comfortable having them listening and whoever’s behind that listening not necessarily the device?

The truth is, and I tell people as they ask me in my talks all the time, what about privacy? I know you didn’t know this but you lost your privacy about 23 years ago around 1995 for a whole set of reasons mostly based in advertising and the value that the information has to advertisers getting over. Let’s get over it. I’m going to withdraw from social media. It doesn’t matter if your data has been taken and sold a million times. Did you ever wonder how you can be on your computer literally doing some things and you went through a website, this and that? An hour later on your phone, not on the web, but on an app and an ad comes up for the very sheets you were looking at. I won’t tell you how that’s done. It’s very trickily done but nevertheless, it is done. Let it go unless you’re a bad person trying to do something to harm this country.

People say, “What do you mean the government could be listening to all your phone calls?” They are. Yes. There’s a computer listening to all our phone calls. “What are you going to do about that?” “Nothing.” “Why?” “Because I don’t say anything.” I try not to use the word BOMB very often because when you use that, it flags something and someone says, “How is the person using this? In what context? Is it dangerous?” If you’re not intending to do harm, I think any government official would pick up the phone and listen to my conversations and would be bored to tears in about three minutes and hang up. There’s nothing interesting.

I have nothing that I’m worried about, but a lot of people do worry about these things. There’s a word that’s associated a lot with technology in general. I remember a selling system 36 or 38, 100 years ago and before the PCs even came out, everybody freaked out that they’re going to lose their jobs. Then we found out that there were other jobs because somebody had to run the computers. Old jobs went away and new jobs came out but you talk about a jobless future. What is that and what does everybody do? How do we make money?

I have talked about that but I did that original talking maybe 2013 or 2014. Lately, what I have seen is in fact a bit of the opposite. I don’t want to talk about 2015, 2016, 2017. I do believe there will be a time when AI can do the vast majority of work that humans do. It’s probably not in our career lifespan and that might not be in our children’s career lifespan, but it probably will be in our grandkids career lifespan. Then we’ve got to talk about the basic income and a variety of other things.

Learning is one domain, while applying it is another. Click To Tweet

When you look at, first of all, what the opportunities are and I’ll give you some examples. Drones have gone from a child’s toy to actual usefulness now. For example, in agriculture, all major farms this year are scanning their fields with drones and very sophisticated applications looking for hot and cold nitrogen spots so that they can reduce the amount of fertilizer. This fertilizer is one of the biggest costs the farmer has and if you can reduce your fertilizer by 10 or 20%, that is a pure margin for the farm. It’s a big deal.

All of a sudden you need writers of this software, analysis of the outcomes and you need thousands and thousands of drone operators, which is a job that didn’t exist two years ago. It’s quite possible that in the next five years there will be major drone control centers that have hundreds of thousands of people working in the drone business. Maybe millions of people in the drone business. It’s a business that didn’t exist a few years ago. That is 162 or so likely new jobs.

Here’s another one. The transitionist. I think transitionists are going to be some of the biggest, best and most important human jobs at high pay rates. It’s like a psychiatrist or a psychologist but goes into the workplace and says, “All of this work that you’ve been doing is going to be eliminated in the next two months, but you’re going to be doing this other stuff over here.” They’ll help transition organizations from what they were doing to what they’re going to be doing because people need help transitioning and there are no transitionists. There aren’t any. We’ve got to go build an entire category of people and we probably need a few hundred thousands of them worldwide.

By when? What are educational institutions or education? Are they going to have a masters of transitioning?

Probably but there will be behind and the demand will be higher than you can get it. Those are two examples. There are dozens and dozens of examples of the new jobs. What’s going to be eliminated? Mundane and repeatable tasks are the first to go. Is that bad for the US? It will affect the US last and that’s because many of our mundane tasks except for service-oriented jobs of needing service workers and food servers and things like that in the restaurant. Most of the mundane jobs that is customer support, software QA and manufacturing over the last twenty years were outsourced to other countries, India and China being the two biggest. We outsourced because our labor rates were too high to continue doing them here. We already outsourced to low labor, we just did.

We outsourced the mundane task. We didn’t outsource the PhD tasks. This is not a knock on anyone, it is just what we did. We’ve already rolled over much of our country. There was a time that this country was 98% agriculture and there was a time it was 60, 70% manufacturing and today, Ag is 1 or 2% of people manufacturing. It might be single digits of people now or maybe just barely double digits of employment, but it’s much lower than it was five decades ago. That’s because we already outsourced that. We’ve already handed that off. It might as well be automation, it’s cheap labor.

TTL 225 | Appvance
Appvance: The best thing you could do is come up with a real recycling plan, like we do for glass and tin cans.

The first cheap labor to be replaced is the cheap labor in mundane labor in China and India and those countries need to worry about that because automation is now cheaper than labor in China, just in the last few years. Some AIs are now cheaper than now what you can do in India for instance, for customer support, claims processing, and insurance. We’re seeing claims processing that’s going to be highly automated in the next five years with customer support, highly automated in the next five years. Manufacturing highly automated in the next five years. All those jobs already went offshore or a lot of them. Those are the first ones to go.

Then, you’re going to start getting taxi drivers, of course truck drivers. There is a question in this society, “What do you do with a million unemployed plus or minus taxi drivers and truck drivers?” We need them to do other jobs, drone operations and yes, I think we can train a lot of these people to do other jobs. Yes, the taxi driving job is mostly going to go away in three years, five years, seven years, somewhere in there because there’s no reason to pay $3 a mile when you can pay $0.35 a mile or even drive for free with Amazon Prime.

It is interesting to see what the ride of business is going to do to other areas. If you think that everybody’s not going to have cars possibly because you’re Uber or you’re going to get to places that impact maybe housing, not needing garages anymore and parking lots that’s needing to be built. It’s just the overall impact of what one disruptive innovation can do to other things. It must be staggering to think about. You’ve had so much experience in so many areas.

I’ve worked in agricultural, chemicals, in manufacturing, pharmaceutical sales and all the things you’ve mentioned are bringing up all my past jobs thinking will that be there? It’s interesting to look at some of the industries in which you focus because I was noticing you’re involved not just in AI and robotics, but you’ve got sustainability, sleep tech and different things. What draws you to a specific area that you’d like to work with? What’s your big passion now for your next company idea?

I think I have a personality flaw because I’m always drawn to things that people say can’t be done.

Do you want to get through that wall?

Yes, if that can’t be done I go, “Hang on, maybe it can.” It always ends up much harder than I and we thought to solve the problems. I’m involved in a number of companies right now. I spend most of my time at a company called Appvance.ai and we’re using AI to automatically test software. All of us in the software and the vast majority of that software and the enterprise runs the enterprise, it’s not the website. The website is 1% of what they do. It turns out that the software that runs the enterprise has gotten more and more complex. It’s not unusual for a large enterprise to have 10,000 applications that run their company. They have to upgrade them and fix them and still to automatically test them instead of using literally hundreds of thousands of people to test them, which is what they do now.

The tests ought to be good because they’re humans and they make mistakes. If we can truly automatically generate test, test them and report back, that is going to make the quality of software much better. It allows the software to get much more complex and let software test software so that was the vision and it’s taken us five to six years to design that vision and design the AI that does that. It’s showing promise in the hands of clients. It’s super exciting, but it was incredibly hard. $80 billion a year spent testing software, more than half of that offshore because we’re pushing that offshore. $80 billion a year to just test the software so there is a big opportunity that these dollars are being spent.

These are good people doing hard work. It’s manual labor but it turns out the best they can do is maybe find 20 or 30% of the bucks for a whole set of reasons. Run out of money, run out of time and stuff so we may be able to find close to 100% of the bugs for a 10th the cost, in a 10th of the time, 100th of the time or a thousandth of the time. That’s where you can find these little vertical $80 billion dollar niches and go after them. What looked insurmountable now seems pretty surmountable. That’s one example. We can talk about sleep. I think sleep is fascinating that tens of billions are spent every day trying to get to sleep and trying to stay asleep.

A lot of people have attacked this problem in a number of ways and so we’re looking at some great technology and some great results that would be a consumer-oriented product. The name of the company is Slumber Science. It would seem like it can have a real impact on people’s sleep. It puts you to sleep, but you can get back to sleep. This is not for the clinically, “I can’t sleep. Something’s wrong with my brain people.” This does not mean bad but like I have a chemical imbalance. I have pain.

This is for people who are normal folks that often can’t get to sleep and it’s just what we live with. It’s most people who are over 50 that have this problem where they wake up at 3:00 AM or whatever. It’s going after that market, not the clinically sleep deprived and need real doctors help. That’s a different market. These seem insurmountable but they’re addressable. In my last company, I did all the windows in the empire state building and they made their money back in three years, saving $440,000 a year. Bill Gates invented Windows and I invented windows, just different kinds of windows.

You do a lot of great work in the green arena. I saw even Beir, I don’t know if you’ve ever seen him talk at a Forbes event. He was great. He was using mushrooms to replace Styrofoam and plastic. He’s an amazing guy. You’re very interested in going green in what you can do to help the world in that respect. Do you see more companies focusing on that? How important is that right now?

Silicon Valley stopped funding that place around 2010 or 2011. I got out of it for a set of reasons, including the return was quite strong. It takes too long to build a company. Our generation and the generations before us have done some things that impact this planet and you can decide, if that’s plastics in the ocean floating in the oceans or it’s climate change or whatever you believe in. Humans have had an impact and we’ve reached the point where we had a deleterious impact and it’s very hard to dispute that. I don’t mean to make this a political issue. It shouldn’t be, it’s just science, just everybody get over it. It doesn’t mean that we’re bad people. It doesn’t mean that we meant to do harm, but there are seven billion of us and seven billion is a lot to generate a lot of waste, a lot of CO2 and a lot of other things.

Eventually, they have some impact on the livelihood of us on this planet. The planet will survive. It will still go around the sun, whether we survive on it and that is a different story. I think that we owe it to the future generations to do what we can do that’s within our grasp and that isn’t much. We can do a little in inventing some products that save CO2 and save materials being used. I’ve been involved in a company called Agilyx at Oregon. It’s a fantastic company that recognizes that styrofoam, these kinds of things or polystyrene isn’t going away. In fact, it’s used more and more every year regardless of the fact that some cities have banned it. The city banning it doesn’t, in the end, change the worldwide usage.

TTL 225 | Appvance
Appvance: Polystyrene is incredibly inexpensive. It’s a valuable thing for humanity. It’s insulation qualities are excellent.

To change the worldwide usage, the best thing you could do is come up with a real recycling plan like we do for glass and tin cans. We don’t think that glass is a bad thing anymore because you recycle it and make a new glass out of it. They developed a technology that takes polystyrene and it makes a styrene monomer out of it to make more polystyrene. It goes round and round in a big circle. Don Mcdonald wrote twenty years ago, cradle to cradle. Just do that and you could pull it out of the ground again. You keep going round and round and reuse the same thing.

That’s the smart activity because it’s not going away. Get over that. Polystyrene is incredibly inexpensive. It’s a valuable thing for humanity and its insulative qualities are excellent. It comes with all of the products that we buy in consumer electronics. If they can’t make it go away, then what we have to do is we got to reuse all of it. We’ve got to a reuse it or recycle in a cradle to cradle society and then it’s okay. It doesn’t end up in the ocean. That’s the problem.

I know they’re trying to make roadways and different things out of different materials because it’s already here. I was always a big Jetsons and Star Trek fan when I was a kid. Even the Wild Wild West, you’d watch all this stuff and you’d think, “This is so cool.” Did you have a favorite show when you were a kid that you just looked at and go, “I love all the future stuff?” Were you that kid?

I love the Jetsons and how could you not love the Jetsons? The little bubbles that they flew around seemed ridiculous. They could vertically take off and land pretty fast horizontally but there are twelve companies now, all with flying units, whatever you want to call them, that take off vertically and can go up to 200 miles in land an hour. They can get you at about $1 a mile. I’ve seen them fly. These are absolutely amazing vehicles. We will not be limited to the ground. All of these vehicles fly today. I’m not talking about futuristic technologies. They don’t look like the Jetsons bubbles, but they fly like the Jetson bubbles. They just land vertically.

They look a little more like planes that lift once you tilt rotors and things like this but also they’re built in. They’re meant for one or two people and they’re small. However, the only thing that’s keeping us from flying in once a day is not the technology, it’s the safety. They have all kinds of backup systems, extra lift and make it land by itself so they fly themselves. It’s the FAA. It’s how they’re going to get rules for the sky to fly from point A to there. You could imagine let’s say people in LA that want to get from the airport or the Hollywood. Instead of taking an hour to get there during rush hour, you could probably do it in the air in about eight minutes. I can imagine I’ve seen these things fly.

Transportation will be a service for sure. We’re going to own those and we won’t own cars because owning a car costs the average American about $10,000 a year including the depreciation of the car, the insurance, the upkeep and everything else. We’ll be able to get our transportation for between $0.35 a mile and free in some cases because people want you in their cars listening to their ads, let’s say. The net result is ten years from now or eight years from now, you’ll never own a car and it will be good for us. In fact, driving a vehicle will become outlawed in some cities certainly in the next decade.

It’s interesting that in your mind and in all these areas that you’re able to focus on all at the same time is hard to fathom. I appreciate that you shared your insights because I think so many people probably found this fascinating. I know I did. I’m curious if you have anything you’d like to share as far as how people can find out more about what you’re working on or any websites you’d like to promote. I would love for you to share them.

I don’t have much that I put out there. Obviously, you can read more about Agilyx at Agilyx.com. You can read more about Appvance, which does the software testing AI at Appvance.ai. I could go on and on as I’m involved in music and a whole bunch of other things. I would end with this is that we all have as far as one life to live, at least this life is the only life we know about now. There might be another one there in some form or fashion. We should all do the things, try to do some part of our life with the things we love and make that in some of your work or your career. That’s fantastic.

Go find the things that make you happy and spend some of your life doing those. Click To Tweet

You’ve clearly had many careers but in the end, you’ve ended up doing this radio show podcast, which is fascinating. This obviously brings you immense happiness to do this. Maybe this was your calling. You currently got to do your calling. My advice to everyone is to find the things that make you happy and spend some of your life doing those, whether the hobbies, the things on the weekend, or whether you can make it your work if you’re fortunate enough now in either the gig economy or startup economy because you don’t know when you won’t be able to do those things anymore. You don’t want to spend your life doing something that you simply hate that’s isn’t your calling. Find your calling and try to do it.

I think those are words to live by. Thank you so much, Kevin. This has been so exciting to have you on the show.

It was a pleasure, Diane. I’m sure we will meet and do another show sometime in the future.

That will be fun. I want to thank Kevin so much for being on the show. He’s such a fascinating guy. He’s won every possible award and he’s well thought of in terms of who to go to in innovation and for artificial intelligence information. He’s got a very interesting background. If you’ve missed any past episodes or you want to find out more about Kevin or other guests, you can find out everything you need to know on our website.

We’re finding out more and more information for that assessment that’s going to make it fascinating because we’re researching the things that hold people back from being curious. That assessment is going to be available on the site so stay tuned for that. If you want to get on the mailing list to find out more information, feel free to sign up to get to the show. You can contact the show if you have any questions in general. Hope you do that. Take some time to listen to some past episodes if you’ve missed any, you can sign up at iTunes to get them that way. We’re basically everywhere Roku, iHeart, and just about everywhere. Good places to find podcasts are available in addition to being on the AM, FM stations that you might be listening to right now. Please join us for the next episode.

About Kevin Surace

TTL 225 | AppvanceKevin Surace is the CEO of Appvance.ai, sits on seven boards and has been awarded 28 US patents. Kevin has been featured by Businessweek, Time, Fortune, Forbes, CNN, ABC, MSNBC, FOX News, and has keynoted hundreds of events, from INC5000 to TED to the US Congress. He was INC Magazines’ Entrepreneur of the Year, a CNBC top Innovator of the Decade, World Economic Forum Tech Pioneer, Chair of Silicon Valley Forum, Planet Forward Innovator of the Year nominee, featured for 5 years on TechTV’s Silicon Spin, and inducted into RIT’s Innovation Hall of Fame.

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