When we thought of the year 2020, many of us may have thought we would be flying in our cars and getting our coffee served to us by robots...
While we are still working on getting the wings working on our cars, Brain Corp is steadily driving us towards seeing more robots in our daily life. This week on Mr. Beacon, we sit down with Dave Ross, VP of Business Development at Brain Corp, to discuss how robots are changing the industry today, and plans to revolutionize many of the places we visit frequently like the grocery store and airports. Founded in 2009 by a world renowned computational neuroscientist, Brain Corp is the world’s leading technology provider for the autonomous floor care market, with over 10,000 BrainOS-powered active cleaning machines and many more shipped, getting ready for action. While Brain Corp is focused on the world’s largest commercial autonomous fleet of cleaning robots, they are also planning for a future that includes many other services other than cleaning up the split juice on aisle 12. Cameras and radios (such as Bluetooth) built into these robots, can enable many other use cases like notifying out of stocks, locating items, and creating location and temperature maps, to name a few.
The Mr. beacon podcast is sponsored by Willie, scaling IoT with battery free Bluetooth.
Steve Statler 00:16
So, welcome to the Mr. beacon podcast. This week, we're going to be talking about the internet of robots or something like that. I'm really pleased. I've got Dave Ross, who runs business development for a company called brain Corp. So Dave, welcome to the podcast.
Dave Ross 00:33
Thank you for having me here.
Steve Statler 00:35
Yeah, well, it's a real pleasure. You work for this very cool company. And actually, you've worked for several cool companies done some had some amazing experience over your, your years of doing deals and business development. So we might get into that if we have time. But first of all, just tell us who brain Corp.
Dave Ross 00:56
So brain core is 10 year old company, it was actually started at Qualcomm where you and I met. And to two neuroscientists from a local neuroscience Center in San Diego, which is now gone, I think we hired everyone out there, and so there's no one left. But, um, they came, they were hired by Paul Jacobs, and Matt Rob, our CEO and CTO of Qualcomm at the time to come to Qualcomm to develop a processor that would model the way the human brain processes vision. And what's interesting about that is 95 plus percent of information coming into our brain, as human beings is his vision is his visual information. And, and so they were successful in implementing a really interesting processor that could really effectively or efficiently process information in that way, very similar in it's more of a matrix, if like, if you could think of like a CPU as kind of a few cores, like, not very good at multiple, multiple processes. Whereas the GPU or graphics processor may have 4000 cores. And each core is responsible for a small portion of the screen or a VR or something. But a the processor, a neural processor, which they're known as now, very much of a matrix kind of thing very much with memory sort of laced throughout it, just like our brains are I mean, you imagine having a stroke, and then you still remember some stuff because it doesn't just destroy your all your memory takes a part of it out. And so these neural cores are currently in the newest version of Snapdragon. So the big fancy processors that Qualcomm chips for smartphones, just appeared in the work of 10 years ago, is now just appearing commercially as neural cores, as part of Snapdragon, which is being shipped out into many of the smartphones. And, and, of course, they built this custom chip, there was no software to run on the chip, you know, so they actually had to create ways to test the chip. And one of the ways they tested it was through robotics. So they had robots that would figure stuff out and would through vision. So they, they figured their way through a maze like a rat, or do these kinds of things. And, and then about five years ago, Eugene and both on who really started brain decided to leave Qualcomm and start a robotics company. And both one of the early focuses was on something very not sexy. Not like autonomous driving, and all this romantic notion of autonomy, but basically, floor cleaning. So if you think about no one wants to be the janitor, really, or maybe, maybe some do, but the point is, and janitors are cool, we love janitors. In fact, I would say today, the brain has elevated a janitorial position into that of a robot overlords, because robots are managed by janitors, and trained by janitors. And they help janitors. They don't replace the janitor, they help them. And so it was really a smart vision. And just like Qualcomm initially, if, if you recall, Qualcomm used to make phones. Why didn't Qualcomm make phones? Because no one else would, you know, we had this wonderful technology that would allow for 20 times the number of circuits or phone calls 100 times the amount of data, and no one would want to build a phone with that because there was a competing digital technology that was still supported by Motorola and Nokia. Have you have you heard those companies because they don't just but remember back at the time, they were the behemoths and they had refused to build any kind of device that would support the Qualcomm digital technology. So we got in the business of making phones and selling phones and competing with them. Within Samsung started being building phones with our technology. We had to get out of the phone business because Didn't want to compete with Samsung. But much like that brain kind of started out building with a partner in China, a floor care robot that was scrubbed floors, pretty big thousand pound type of robot like you currently see them running around in airports and malls and they clean up to 90,000 square feet a day. In some cases, we see reports from like the hospitals that are using them now or using them almost half the day. But that irritated a lot of the people making cleaning machines from manual use. So that you know, and you'll see a lot of brain robots have a seat in them because we basically have helped a number of OEMs to automate their existing four carriageway. And so we got we quickly got out of the robot building business. And now we have our partners the Samsung of, of floorcare. robotics currently is a company called Tennant. 150 year old company and amazing company. And they quickly got in and started selling robots directly. And we've been scaling quite rapidly With their help and a number of other new OEMs coming on board too. So very similar to a Qualcomm model, and that we're enabling other OEMs to build the products. And I want to say Qualcomm probably ended up putting a smartphone in the hands of every single person on earth with the help of maybe 12. Major OEMs. Currently, brain has seven OEMs in the four carriers as an example. And we're rapidly growing just like walking dead. So it's amazing strategy and amazing company.
Steve Statler 06:34
Fantastic. Let's tweezer apart a few of those things and just go back and recap. So brain Corp started as research on site at Qualcomm, you're now venture funded, right? You have Qualcomm's an investor, SoftBank, invested investor. And my memory of brain caught was it was they were creating a brain on a chip, which I think is what you said, is it? Is it a neural network or the word neural was in there, but is it a
Dave Ross 07:04
neural neural processor. And so, and this now we're outside of my understanding of technology, and usually I, I'm hanging out with one of the one of the co founders, a guy named botond, from Hungary, who I would say, is a really good engineer with a personality, if that makes sense. And he would be here laughing at all the stuff I'm saying right now. So I dare to tread into these waters of neural net,
Steve Statler 07:31
small viewership, so he probably won't
Dave Ross 07:34
really understand it, and botond won't help me understand it. And every time I talk about it, he laughs So he wouldn't be laughing. I'm sure he laughed, and I sent him this.
Steve Statler 07:44
But, you know, we're not talking about just to conventional CPU, arm type CPU, we're talking about a radically different approach to developing a processor. And then the question is, you know, what are you going to do with that, and, and it seems like you guys pivoted, or at least you decided you were going to focus on the LS route. My understanding is, you're an LS company,
Dave Ross 08:06
that's great. Right? On the, the opposite the operating system of robotics, essentially. And robotics actually works really well and very safely. Um, there's a lot of a lot of statistics in operating robots safe. And leveraging sensor fusion of various kinds with LIDAR and cameras, and we don't even need a graphics processor or a neural processor, we use a CPU to navigate safely and have a very good safety record, so far knock on wood. And, and, but it's more about the system, it's a system level kind of solution. If all we had to do as humans is navigate safely around, I think, you know, our brains would have not much of a load to carry. And so we don't need the neural processors, but we're getting more and more into solutions, mobile IoT solutions, where we're collecting a lot of data around us. And we're processing that data, we want to do it on the robot itself, to say that's a box of Froot Loops, that's about that's a 22 ounce jar, peanut butter of Skippy peanut butter. That is a Polish hot dog with a weak bond, you know, these kinds of things. And, and that takes a lot of a lot of the neural type of processing, even even graphics type of processing where you're using multiple cores. And somewhere in that question about neural networks, and the multiple cores and a GPU and a neural chip is why that would work. But it's beyond my understanding at the time and I I don't mind being laughed at but I'm pretty sure that the giggles haven't stopped at this point. So I wouldn't be here.
Steve Statler 09:45
So I'm from my memory of robotics. The first law is don't kill people. How's that going? You doing great with that?
Dave Ross 09:54
It's awesome. what's what's interesting about a non sexy janitorial Job is I don't have to go 80 miles an hour to do it. And I think that's a problem when you start talking about autonomous driving. Is that what what happens if someone sideswiped you? And wipes out half your sensors? And you're going 80 miles an hour? Do you lock up the brakes? Well, what happens to people behind you? Do you slowly pull over to the side of the road? Well, what if those sensors are missing or damaged, you know, so there's all these problems at speed, with safety. When you go three miles an hour, if anything happens, that's weird. Just stop, just stop. And we can stop much faster than a human can. Because we're really good with brakes and really good with instantly stopping and an example, my son was going into his high school one morning with his new car, and he hit the gate of the school. And I said, Why don't you hit the gate of the school? He said, Well, the son got in my eyes. And I'm like, sighted, if the sun got in the robots, sensors, it would stop. So the robots are already better than my son at driving at slow speeds. And so I tried to point that out to him that he should drive more like a robot does. Yes. And stop
Steve Statler 11:11
often. I need to try that with my son as well. He's got several several dents that have appeared and what has now become his car because no one else wants to, to drive it. Okay, so robots, pretty safe so far. Can you give a sense of, you know, who's using these things, it sounds like you've got a whole bunch of OEMs. And I want to go into a little bit more about what that means and how that works. But how's business you finding people want these things,
Dave Ross 11:44
business is great, we, we got another round of funding in the middle of this pandemic, which is, as newsworthy, I'd say, because of the pandemic has increased demand, for autonomy. And for because a lot of a lot of people aren't going to work. And things still need to be kept clean. And in going back to work, the demand.
Steve Statler 12:10
They really want. They want it to be like not just quite clean, they want it to be very, very clean,
Dave Ross 12:15
very, very, very clean, right. And so we're even looking at solutions to add higher levels of cleanliness approaching, approaching more of a disinfection level of cleanliness. And we're exploring a lot of those solutions and having conversations with a lot of our customers now. But our robots currently you can find them in malls, airports, schools, many of the major or most of the major retailers in the United States use our robots at night to clean their floors, especially when they have large, shiny floors. Because our robots weigh 1000 pounds, down to 100 pounds. The vacuums currently are 100 pounds, working on some interesting interesting mops that will be in the smaller physics range. But unlike roombas thousand pound things can't bump into stuff. So we have to steadily guide ourselves to clean and then also make sure we navigate around people or any objects that are unexpected and that sort of thing. But we have, I'd say the fleet is the active fleet is over 10,000 units. And then the inventory that's been shipped in waiting to be deployed is is a much higher than that.
Steve Statler 13:23
So that's a lot of stores. And I'm guessing that typically these are in larger stores if I've got like tiny boutique probably don't need a massive, artificially intelligent robot. But if I'm big bookstore, good idea.
Dave Ross 13:40
30,000 feet and up for a larger robot. And then we're working on a number of smaller robots to fit the the smaller square footage stores. That makes sense. And usually what happens is, again, the janitor, nothing happens to the janitor. What happens is the janitor gets to clean everything better. And now that now that now the COVID hit or the pandemic is here, you take the bulk of the work of cleaning the floor and you know can take two to three to four hours for a robot to do that bulk of that work. The janitor can spend that time now cleaning the bathrooms better disinfecting the back bathrooms better disinfecting the clean floor better. So the janitors are freed up to do more to keep things cleaner, because you're taking the bulk of work and having a robot do it that's being managed by a janitor.
Steve Statler 14:30
So and is it safe to have these guys going during the day? Obviously no brainer middle of the night. These guys are gonna stick to what they're supposed to be doing. They're trustworthy, and they can work hard constantly. But what about doing it during the day? I imagine that there's reasons why you might want a robot to be roaming around your store during the day is that feasible.
Dave Ross 14:56
So it's up to the stores to manage it however they want. What What mostly people run them at night because there's less people and the robot gets it done quickly. It's also the time where the janitors are cleaning anyway, because janitors tend to clean when people aren't there. So the store manager, what I've noticed is a lot of stores or some stores are running the robots so people can see them. Because then people can see Oh, wow, this, this place is being kept clean robotically. That's cool. And so it's helping people be confident to be in the store, that it's being kept clean, and that sort of thing. So I've noticed some retailers are running in at that time, just so that people see it. If there's a lot of obstacles and people in the way it might take the robot longer to clean the store, right? Because it's you know, it goes it has to slow down and go carefully around people. And so it can do it a lot faster if they're not around.
Steve Statler 15:45
And what else can you use this robot for that I'm imagining, it's kind of pretty expensive bit of kit, you, there are other things you can do with it, other than have it clean the floor?
Dave Ross 15:57
Absolutely. So we're working now on adding more use cases to the robot, we've got several prototypes out that we're testing to collect data. So as robots are cleaning the floors in different places, they're building their own maps. And so every day they build a new map of the environment, so that they know where they're going to navigate to, and they have a understanding of a janitor basically trains the robot how to clean the store. So the robot knows generally what it should do, maybe it goes around the food section five or 10 times because it's dirtier because the janitor would do that. And but maybe there's enough, maybe someone put a chair or a pallet of stuff in the middle of the floor. So it has to build a map every day of what what it's doing. And because it's building a map that's has to be pretty accurate down to the centimeter, we can map data on that same map. So I can collect temperature data around the same place and give you a map showing the temperature throughout this, this, you know, understanding of the store. We can take photographs of things and run AI models and then locate localize, we say or localize points of interest at the airport, we actually did a proof of concept where we took camera data and built a map of the airport where the men's rooms were and where the those screens that give you information about flights and ATM machines, and all the kinds of things you might be interested. And that stuff moves around quite a bit actually, even harder. We're doing this in retail environments. So we're taking pictures of inventory in stores. And we're able to tell the story exactly what's out of stock exactly what where stuff is. And and it's very powerful, especially with the with the pandemic, we were actually able to tell some of our proof of concept customers, you know, we said to one of our customers said, You've got $400 stops, and they're like no, and then we showed him the photographs, look, you know, a robot found 400 out of stocks, and we're all scratching our heads. And then we looked through the photographs, and you could see empty, just empty everything right? Beyond toilet paper, you know, the whole time we're going who's buying all this toilet paper, right. But then all of a sudden, everyone started buying all the Nutella and then it was then it was something else, you know. And luckily, they didn't buy all the beer because that's what I was buying anyway. Because but, but they were buying lots of things wrapped up,
Steve Statler 18:14
this stocks are doing pretty well in these stools, despite all this. So that's a very compelling use case, spotting out of stocks, because that way you can drive lift and sales, the better job you do of having product on shelves. And presumably, you can do that with all sorts of auto ID technology. So RFID and all that kind of thing doesn't just have to be cameras. I wonder
Dave Ross 18:38
if there's a company that has set the technology we're actually working in as you know, we're working with William now. Um, we've had a lot of conversations that you don't know about internally that we're you know, we're gonna build the sensors, we're already actively looking at where we're going to mount it and do that kind of stuff. So that we can just help discover stuff with with your Bluetooth technology, which will be awesome. And there's a lot of things that can't be localized or located with with vision, for example, it as a human, I have to manipulate an item to know what it is like it could be a shirt, is it long sleeve or short sleeve? Is it large, smaller, I can't I can't do that I can't look at the side of a shirt as a human and say, Well, that's a small shirt. And a robot can't do that either. So if it has to be articulated in any way, um, something a tag like like you guys make is perfect, because then I just look and I can say, Well, I read the I read these RF signatures of all these items here and there's for extra large shortsleeve this skew of shirt and so we can exactly talk about things that are really hard for robots to see using vision in packaged goods on a shelf pretty easy like canon campbell soup or a box of Jerry Pop Tarts, pretty easy to use computer vision for that kind of thing. The clothes and tires and all the kinds of things that you would have to inspect closely as a human. You know, we're Looking at you guys to help us with that,
Steve Statler 20:02
why I think it's actually a fascinating business strategy that you've got, you've found a use case, which is very, I mean, it's compelling, people need to have stores clean and clean more often now. So that's kind of like your base of getting the system in there. And then you can hook all of these other kinds of sensors on. And yeah, it can be very challenging, whether it's Bluetooth tags, Bluetooth beacons, they're really not battery free Bluetooth, or even RFID. Typically, to blanket a massive store with scanners and readers that's going to cover everything is kind of expensive. But if you have a mobile reader, that's dependably scanning on a given cadence, then I think you have great opportunity to provide something that is cost effective, and can extend the reach of the Internet of Things to places where it hasn't been before. So obviously, we love what you're doing. But I'm sure that you know, like any new technology, people get a bit scared. They get scared of a number of things, people losing their jobs and people getting hurt. We've already talked about the safety thing. And I guess you've you've already preempted, maybe you've already preempted the people losing jobs. But what's your general observation about what people are scared of? is fear an issue that you have to deal with? Is the the business development guy.
Dave Ross 21:41
I think there's always a lot of fear, I think the biggest fear has been, there's always fear of new technologies. My dad was afraid of the internet, you know, and he always call the stockbroker, like, Dad, you can look online. It was like, nope, don't trust it. It's my money. So there's, I think there's when you bring on any level of innovation, that there's going to be a fear. I think people losing jobs is a big question that everyone has, some people are convinced that it it's happening or going to happen with with all kinds of I mean, imagine at one point, there were ladies plugging wires in to connect phone calls. And now there's a computer that does that. And that was a level of automation. The cotton gin is a level of automation, where people are afraid of the cotton gin, they probably were at the time. Now we have eight of one now. No, we're not. Why because we have cheaper cotton we have what what is the result is we have cheaper clothes, because as a result of automation, automation around food processing, and shopping and things like that help things help the price come down and things and give people more access to things. And there's a guy at our company, Phil Duffy, who says it best robots are meant to do the three DS of human work, the dull, the dirty, and the dangerous. And if you think about that, if we take away the dull the dullness, what is what is, is that good for human humanity to take away dull things and dirty things, and especially dangerous things. It seems like a good thing, right? It's it seems like that is a good purpose, to take the those parts of a job out, it's not taking a job away, it's taking those parts of a job out it. And I realized all this one, I got my own Roomba, so to speak here, because I clean my own house. And I left that room ago, it gets most of the stuff, I got a little hand back to get around the other areas, but then I get to clean my bathrooms and wash the clothes and do all those other things. So and that's, you know, taking care of all while that thing's going around vacuuming, vacuuming up most of the stuff. And I'm always surprised when I empty the bucket on that thing. How much dirt in there, you know, it's like pretty, pretty incredible. And I don't want to push that thing around, then I don't want I don't want to spend my time doing that. And it just enables, like I've said it's, no one's got no one's gotten fired that I've known about, you know, someone's got to manage that robot to its robot overlords. Now, in the airport, they the janitors, a robot Overlord, and they're keeping the other parts of the airport clean.
Steve Statler 24:23
So from ethics to one more geeky question, so we're rushing from one side of the boat to the other. But I realized we're kind of running a little low on time. So I want to make sure we get to this. How does the robot know where it is? Yeah, like if I was to spin this thing around in the store, would it like get lost and stop plowing through the shelf so that
Dave Ross 24:46
so the robots have cameras and LIDAR is and sensors and they also have just like your cell phone has all six axes kind of thing. So it kind of knows orientation. robots have that to compass of which way it's going So the way it works now, I call this version one. It's a teaching repeat sort of model. So a home marker is placed in the area in the airport or store or wherever, which is origin 00. Think of Cartesian grid back to Calculus or no back to algebra. And, and 00 is a known home marker, the robot stands that marker been the janitor drives it around the way they would normally clean, and they come back to the home marker, and then they hit the Save button, and then that saves that path or that cleaning method. And then to do that, again, the janitor pulls up to the home marker and says, Do route number one. And then the robot does exactly what the janitor did the first time. So the janitor has taught the robot how to clean. And there might be a way that the janitor cleans when it rains, or the way the janitor clean when it cleans when it snows or just a daily sort of quick clean, or you know, a heavy traffic clean or during pandemic clean, where we've got only certain people in certain parts. And so all those can be stored the janitor teaches teaches it. And basically, it doesn't get all the way to the edge. And so there's still just like roombas don't quite get everything perfectly, there's still a little spot cleaning to do on the floor. It frees up the janitor to clean other other surfaces and other places, which you know, especially now is becoming more important. But it's called teaching repeat. That's version one. Um, just before the pandemic started, I walked in my office and there was a little vacuum RTD to look at 100 pound robot in my office. And I'm like, what, what do you what is this? What are you doing in here? Yeah, people actually want to talk to them, we that's why we don't have that user interface. Because I always thought it would be cool, like, Hey, what's up, you know, but But apparently, then you want to talk to the robot, and then it doesn't do its job. But um, with version two is we're now working on an AI which is called self discovery, where you can a janitor now can just turn the robot loose, and it'll explore the area, it'll know, I'm a vacuum, this is carpet, that shiny floor. So and then it builds its own map of the area. And then it's it goes around and cleans the carpet only. And the janitor doesn't have to spend the time training multiple routes, they can always go back and do that if they want. Because they may know something that is too hard to automate, they may know well, if it rains, or it's actually extra dirty over here, because there was a horrible accident of some kind. And then the robot can go into full manual mode. And then the janitor could do that with the robot.
Steve Statler 27:36
So what happens if someone, you train the robot, it gets the lay of the store and then someone puts some kind of display the blocks one of the aisles is what's the result of that.
Dave Ross 27:51
So in this is back to version one. So version one, we've taken a manual machine and put it and put sensors and compute on it so that it can be automated. Well, if you and then there's another version of a robot that we built under contract for a company that basically can spin around on itself. So it can go and reverse essentially, okay, the sensors and computer pretty expensive and generally forward facing. So while a human can drive these men, big manual machines in reverse, it doesn't go into reverse automatically come so if a robot goes down an aisle that it previously went is completely blocked, I mean, the robot will look for a space that it can fit through safely. And if it can't, it'll stop, and it'll text the janitor. And as we call that an assist, they'll say, Hey, I'm stuck, come help me. And so then the janitor comes and either moves the thing out of the way, and then restarts the robot or gets up and drives the robot back onto the path and sets it about its path. Again, that's still version one, you know, at some point, the people making these big manual machines will make a more autonomous version that can spin up around on itself, and then we'll have less less assists. But the reason we don't have sensors on the back is because it's expensive. It's you know, a lot of expensive stuff looking forward to have all that stuff look backwards to when it becomes economically prohibitive to to make a robot work well. And so ultimately, the design of the mechanical design will follow the abilities of the sensors and you know, expense will be optimized in the design, I believe, but we've done it already with a small vacuum. And I assume that that will extrapolate into the larger form factors.
Steve Statler 29:32
And where do you think this is all going to go in 10 years time or whatever?
Dave Ross 29:37
That's my favorite question. I'm really good at the long term. I'm not so good at like, What do I have to do today? Oh, shoot, I forgot to call that customer. So I believe it. We went through this experience at Qualcomm, where phones used to go like this. And they did one thing, they make a phone call. That's it. I remember starting the App Store back in the 90s Going out going to Silicon Valley going, Hey, all you developers, you can write code on this phone, it's a computer and people just don't. But that's a phone that, what? What doesn't make sense. And then watching that, ultimately, so we had a single use case phone, I remember working on the first camera phone with the inventor of the camera phone, and helping the code work on that thing. And that all of a sudden, now I have a camera in my pocket all the time. And as that camera got better, I stopped carrying my really good camera around why Paul Jacobs used to say it's a camera that's which with you, that matters. You know, if you got this big, heavy thing, and it's not with you, there's a beautiful picture, what you know, what are you going to do, even if it's not a beautiful, great resolution, you're still going to use what you have. And so that was sort of the first dual use case. And then, as it grew into a platform, thank you, apple, thank you, Android and Google, as it grew into this platform, all of a sudden, a phone has become this thing, that it's a guitar tuner, it's a, it's a navigation device, it's all these things with Snapchat, and Uber, what the heck, who even thought of Uber, even the platform enabled this whole business to be created, which employs millions of people. No one, no one even thought of those things, it became this thing that no. So robots in 10 years, I'm sure there's going to be all this stuff we never thought about. Also, multiple viewstate, we're already tracking down multiple use cases, I'm cleaning floors, and I'm collecting data. And what happens is ROI goes from this amount of time to this amount of time. So pretty soon, you know, it's like a very valuable thing. And, you know, I always imagined like a humanoid robot with a mop is cleaning the floor, you know, and that that's what and then it does, and then we get to talk to them at some point, you know, but the smartphone to me is sort of the, the, the analog here with the what's going to happen is much more use cases are going to happen, more value is going to be piled on there. And I believe that things are going to happen with robots, most importantly, that people can't do. And even now, with Shell scanning, people can't possibly go around and stand the stuff in the store as quickly as a robot can't. So providing this inventory report is already a first example of something that I believe people can't do. Didn't take him a week to do that work. And by the time and they need it every 24 hours. So they're still working on it while the reports needed. So there's going to be this whole Paul Bunyan effect if you remember that cartoon where Paul Bunyan had the oxen the axe, and then there was a guy with the chainsaw number cartoon when I was a kid. But I think that it's going to elevate truly elevate into a place that is going to create businesses we can't imagine right now create all kinds of stuff that if I, if I even had a time machine and came back and told you what would happen, you wouldn't believe. And so you know, I'm just excited. And to me, making it more and more of a platform to enable more creative people to come in and partner and do stuff like we're doing with with your sensors. And with our reader and all these that's just a small step in many more steps, heavily partnering, just like the app store was in the app store we had your Apple currently has 2 million apps. And I remember when Verizon told us at one point, no more than 30 apps on the phone. That's too many apps. And it's like 30 apps is too many apps who believe that and so but now look at what look at that smartphone and to me robot same sort of path.
Steve Statler 33:28
Yeah, super interesting. Brain Corp definitely company to watch he you have kind of this knack of, of sniffing out really cool technology and working with it. I kind of think of you a bit like the zelly give of high tech you were there when you know the first app stores. You know, Qualcomm did billions of dollars of revenue through app stores before,
Dave Ross 33:53
right? dollar fear and expect but but it's not me, I just put myself in the orbit of people like you. That's you just get smart people in your orbit and you're having a magical life. You know, and it's people are praying are so amazing. The boat on Eugene, the co founders, all those people are just such amazing people. And I'm just in I'm just in their orbit.
Steve Statler 34:19
Excellent. Well, thanks very much for giving us a glimpse of what you guys are up to. It's it's really clever. It's practical, but it has so much potential and I wish you well, thanks a lot.
Dave Ross 34:32
Thank you. And by the way, I am going to Mars so that you know, Henry Ford said it best whether you think you can or you can't. You're right. And I'm going to Mars.
Steve Statler 34:45
Love that attitude. Dave Ross. Brain Corp. Thank you very much. Thank you. You're quite musical, aren't you?
Dave Ross 34:59
Ah I love music. I play guitar. I don't know if you're a Qualcomm because I kind of snuck my band back at the time and do a few events. And so, love music always have. And but I, I'm not, I want to say I'm not talented, but I tried to do my best. I haven't had my 10,000 hours
Steve Statler 35:24
yet. Okay. Malcolm Gladwell, great, great author. So So what are the three songs that you would take on a trip to Mars?
Dave Ross 35:34
So the three songs so the wakeup song I got so so there's always a background song, you know, just kind of at lower volume. And that would be Rocket Man, of course. Because that's, that's what you're doing is you're in a rocket, and it just kind of like background elevator music, many versions of it by many different people. Hopefully I could, you know, rotate and make it sound different. But if I only got one person to choose from. That person is Taron Egerton his version, but it's my favorite version of that.
Steve Statler 36:15
Have you have you seen elton john, perform?
Dave Ross 36:18
I've seen him a few times. Live it. My favorite live performer is elton john, by far. Ah, and the Rocket Man is always everything's great. Like he's true to the, you know, he knows people want to hear it. Like he knows people don't want to hear a funky version. And so he's just amazing. And his version is fine. Also, but Taron Egerton has got sort of a nice sort of relaxing kind of version of it that I think is kind of caught make might make a heart rate go down a little bit, which would be nice. Huh, that's and then to wake up in the morning. And to, which is a very energetic song. It's a song by cowboy mouth called disconnected. And it's, you're disconnected. So I mean, there's no GPS, there's no, probably no way to really talk back to Earth all the time. So you're disconnected. And then falling asleep? Of course, free falling, but I like the john mayer version of
Steve Statler 37:18
this. All right. Fantastic. And do you play those when you're on stage?
Dave Ross 37:26
I don't know that we've ever played those maybe freefalling. or something. I'm not a singer. Um, if I if I sang them. I know, because I'd have to memorize them. But I remember that we all used to kind of cheat and have like an iPad or something worked on it. Or a teleprompter thing. But uh,
Steve Statler 37:45
cool. Well, thanks for sharing that.
Dave Ross 37:48
Awesome. What are your versions? Does anyone ever asked you for yours? I want to know your three.
Steve Statler 37:53
Oh, well. Very rarely, actually. Yeah.
Dave Ross 37:58
Steve Statler 38:01
I probably have some elton john. Because, you know, when I was a kid, I just really got into Captain fantastic. The album cover was hypnotic and, and so I probably choose Captain fantastic and the brand that that cowboy. I think I would also have some David Bowie, for I did a radio show when I was at college called Brubeck to Bowie. And he reminds me of lots of different incidents and people that I met through the radio show and, and the radio station. And so probably have hunky dory. But so many different songs that I would love. I loved his last album, I thought that was pretty amazing to make that knowing that you're headed off into the wild blue yonder, and so forth. And I think I might choose Dave Brubeck for sentimental reasons I saw him play live when he was alive. And he was a real favorite of my parents. And so because of a nice family thing, so
Dave Ross 39:06
you know, music is connected to memory and how we want to drag our memories with us to Mars, right?
Steve Statler 39:11
It is, and it's a personal thing. There's this show called Desert Island Discs where I borrowed this device from, and it's one of the best interview shows in the world. And I think one of the reasons it's been going for it's the longest running one, it's been going for like, over 70 years, since during the war, they had variable name their land on and author ASCII and a whole bunch of people that no one's ever heard of now, but because they're dead, but it's such a great show because people relax and it gets personal and people let their guard down a little bit. And so it's just my way of learning a bit about the people I'm talking to and as probably my favorite part of this whole exercise. So there we go.
Dave Ross 39:56
And I never knew you had you were different Jackie I mean, and when you talk about album covers just like who even who even knows what that is? I mean, you got to be a certain age to even know what an album is and an album cover or even you know even CD ROMs no one cared about the art so much but I remember always looking through the album covers and just like could never afford them. You know, they were always too much money I could barely afford the dollar singles and and it just was the album covers for so Boston was the one I remember the most just that one. Oh,
Steve Statler 40:29
yeah. Was that the flying saucer thing?
Dave Ross 40:32
It was a guitar also. It was a flying saucer was like a particular view perspective of a guitar. So and it was just cool. I just for some reason. That one sticks in my mind. But
Steve Statler 40:45
yeah, but it did. Alright, thanks a lot.