AI & Robotics: On the Edge

Scheduled for: September 7th, 2021, 12:00 pm PT / Category: Interviews

How does layering in AI on the edge of robotics systems save lives, improve efficiency and simply return an ROI for the stakeholder?

Pramod Raheja, is the CEO & Co-Founder of Airgility, Inc., a company focused on artificial intelligence and aerial autonomous systems based in the Washington DC Metro area and a spinout from the University of Maryland. He is an entrepreneur of 20+ years and a longtime member and past president of the Entrepreneur’s Organization of Washington DC.

He is a graduate/mentor of the Founder’s Institute, Mass Challenge US Air Force Labs and the Fedtech Accelerator Program. He holds a B.S. in Aerospace Engineering from the University of Maryland and is a graduate of the Entrepreneurial Master’s Program at MIT. Pramod thinks of himself as half geek and half sales guy and believes Airgility is at the forefront of an aerospace revolution. He lives with his wife in Potomac Falls, VA and just became an empty Nester with two awesome boys attending Virginia Tech.

Podcast

TRANSCRIPT

Tullio:

Good afternoon, everyone. Welcome to another episode of dojo.live. Today is Tuesday, September 7th, 2021. I’m Tullio Siragusa broadcasting from Southern California, and I’m joined by Kim Lantis in Hermosillo, Mexico and Carlos Ponce in Cuernavaca, Mexico.

Kim:

Hello.

Tullio:

And, of course, our guest Pramod Raheja also known as “Mod” – nice to for you to join us – is the CEO and co-founder of Airgility. Joining us just outside of just north of Virginia. Thanks for joining us today. It’s good to have you as our guest, and we’re talking about robotics and AI today. You know, a lot of people have this fantasy about robots and AI taking over the world. That’s mostly fantasy, but there’s other value for AI and robotics, like valuable things that could improve our lives right now today in practical ways. So we’re going to dig in and see what we can learn today. But before we do that, let’s get to know our guests a little bit… Pramod, please introduce yourself. Thank you.

Pramod:

Thank you. Yes. As Tullio mentioned, I’m the co-founder and CEO of Airgility. I go by “Mod” and happy to be here. Thank you for having me today. I have been sort of, I wouldn’t say immersed or passionate about anything “future tech”, since I was a little kid, mostly spaceships and airplanes adored my walls for about age or five onwards. And so my pedigree kind of followed that path… went to an engineering and science school and actually did aerospace projects as my projects typically; that followed up with a aerospace engineering degree. I have probably now at this point, you know, as you get older, you, you know, lots of, lots of experience in aviation operations and aerospace in various capacities from the business side to actually flying, the flying side to the engineering side at this point as well. And that all parlayed into what I’m doing now which I’ll talk about in a minute.

Tullio:

All right. Well, thanks for giving us a little background. What is it that you’re doing now? What does Airgility do? What gave birth to this idea?

Pramod:

Yeah, so a few years ago I’m so… a little more background on me, which I didn’t say is, I’m a serial entrepreneur of about 25 years, I started a number of businesses and at the university of Maryland, which I’m an alumni of sits – in any research university, in fact – sits something called an “entrepreneur in residence”, and they are typically, they’re, they’re experienced entrepreneurs and they’re there to help faculty and students start businesses. So, in many cases out of universities come great ideas and great intellectual property. And typically, if faculty wants to start a business out of that the university essentially claims ownership to the initial intellectual property because it came under their umbrella, right? That’s sort of normal, works at most universities. But every now and then maybe more often these days that faculty member or researcher wants to start a business. So, my co-founder and our CTO of our company of Andrew Valenti, was a faculty member at Maryland had created some intellectual property and was starting to work on it. And their EIR at the time was somebody I knew. And he said, Hey, you’re going to start a company. You need, you’re going to need a good co-founder and CEO. And that’s how so we were, we had an “arranged marriage”, basically. That’s how we started the company in 2007, middle of 2017. And we, you know, we started with really nothing, just his ideas, a prototype that was starting to get built, but there was no mob business model. There was no product to sell just yet. It truly is the story of something from nothing where we created from scratch and kind of pivoted and found our way around into what we’re going to be, what we’re doing now, which I’ll talk about obviously on the show.

Tullio:

So, what does the company actually do today?

Pramod:

Yeah, so we do artificial intelligence. We build artificially, artificial intelligence and autonomous robotics systems, unmanned robotic systems, really. And that could be ground, air and sea. We happen to have a lot of pedigree with aerial. We like what we call “aerial assets” or what most of the audience probably knows as is drones is where are most of our experiences? However, we’ve done some ground prototypes too. And so, so we kind of play in all those areas. However, we are truly experts on drones.

Tullio:

Okay. We have to dig in and see what we can learn today so much. And that’s in that space – pun intended. I know Uber’s testing some self-flying autonomous vehicles. I mean, there’s a lot of things going on there. Let’s go right into it. Let’s kick off the conversation today. Kim, please introduce the topic and let’s see what we can learn.

Kim:

Yeah. Thank you for being here with us today, Pramod. It’s nice to meet you and to learn about Airgility, the topic as chosen by you is AI and robotics on the edge – how does layering in AI on the edge of robotic systems save lives, improve efficiency, and simply return on ROI for the stakeholder. So the question for today is, yeah. So why that topic? Why did you choose this topic? Why is it timely?

Pramod:

It’s very timely because when we talk about artificial intelligence, I’ll use, I’ll use a Tesla as a, as a simple example. Not everybody has been in a Tesla, but they’re in the news these days. So most people have seen a Tesla. I know a little bit about it and know that there’s some sort of autopilot, etcetera, and that it’s maybe cost a couple of accidents, maybe not, probably, probably debatable, but the bottom line is your car, as it’s that Tesla, and actually many other cars these days, as they’re driving on the roads, they are collecting tons and tons of data. So, when you stop at a red light, that’s a data point when somebody crosses the street, that’s a data point, okay, that looks like a person or I’m driving, and there’s a truck next to me, all that looks like a truck. And, and so millions and millions of data points now get collected into the brain of the car, the brain really, of Tesla. And then that gets dispersed into how they make the software and make the software smarter. So, on the, in the same, when they were doing that with drones, we’re actually putting in both autonomous artificial intelligence, which means “I’m a drone. I have a little brain in my, in my little drone body, and I’m going to make sure that I don’t hit anything”, just like the Tesla, Tesla. You know, if you’re driving on autopilot, theoretically, it should avoid all objects, right? So it’s the same thing here with, with, with the drone. That’s more, the navigation specific, we’ll call it, but then now there’s more of the mission specific. Okay. I’m on a mission. I’m an example would be, I am trying to find somebody that might be alive in a search and rescue situation. And I am the drill and I’m the robot here. There’s no humans around me. I need to go do this, or it’s too dangerous, and we don’t have somebody that can come in here just yet, or I need to go and lead, lead the team before they come in, and I tend to tell them where to go. So, I, the drone, with a fusion of algorithms and sensors can see that maybe somebody is alive under that rubble by using an infrared camera, as an example, or a WIFI finder, where somebody with their cell phone and they’re trying to, you know, send a signal out, we can detect that. And so those are just a couple of different examples. There’s, there’s other means, but that’s one way […] an ROI of saving human lives. On the, on the public safe [sic] I’ll call it, on the public safety side of things.

Tullio:

I would love to unfold some of the applications. I years ago, I worked with an industrial design firm that was looking for an easy way to track apple orchard crops, apparently in huge farms of apple orchard. If something goes bad, you can lose an entire crop. And so they manually travel up and down thousands of acres to track this stuff. And with drones and cameras and sensors, they can actually monitor this proactively. So, I’ve seen some of the application in agriculture and agro-tech. What are some of the applications that are evolving today that you’re noticing?

Pramod:

Yeah. So one area that we, we are becoming specialists in is inspections. So, imagine, and specifically inspections in dangerous places, we like to call it. There’s a whole bunch of D’s -t they’re dangerous, distant, dull. You know, these, these, these D’s I’ll, use that I’ll use that terminology. And what I mean by that is imagine a tank or a nuclear facility or something where it’s probably pretty hazardous for humans to go. And that’s how, that’s what the status quo is. Hey, I got to go climb this ladder. That’s a couple hundred feet up or, or which – I can show you pictures of that. And I don’t know that any of us really want to climb that ladder, right? So the drone can go do that. Like you go fly up and, and not only that, forget, forget, just look having a drone, just to be an eye in the sky. We can design it to be autonomous where it’s flying a predefined path. And it is, you know, looking for something specific, you know, in the, in the case of an inspection, maybe it’s looking for infrastructure that could fail. And I’ll give you an example of about maybe two or three months ago, now it might be four months in fact, there was a bridge in either Alabama, Alabama, Arkansas – I’m sure if we Google this, we’ll find it – that collapsed. And they had paid a small engineering firm to fly their drone around this bridge, to look for signs of whatever – erosion or cracks and things like that. So, the way that things are done today is that drone flew around and then the engineering firm took the SD card out of the drone and put it into their computer. And now they have five hours of footage they’ve got to go through. Guess what happens if you have five hours of footage and you’re a human, it’s probably pretty boring. And you’re looking for that needle in the haystack, right. And you might miss something. And guess what? In that case, the engineer did miss something. And so if they’d watched the video properly, they would have seen that there was a crack there, a big crack that they should have caught. And unfortunately the bridge collapsed, you know, after, after all that. However, if you layer in AI, the AI could tell you right then and there, “Hey, there’s a crack here. You might want to pay attention to this”. And then we can actually send a video right then and there to the, to the operator. The key here is of course you have to have a trained and labeled data set. And what do I mean by that? Just like in your brain. We know that one car is a Honda and another car is a Tesla. We already have labeling in our heads. So you have to train the computer to do that as well.

Kim:

I have a question is, I imagine this, this training is, – what’s the word – transmissible, I don’t know, like it’s, it’s software and its data that you have, and you can hook up to any actual drone. So, let’s say that individual drone is destroyed. There’s an explosion and the bridge collapses, it’s crushed, whatever… you don’t lose that data, right. There’s cloud and you can put that into another set of machinery. Unlike let’s say an individual where we get paid, because we’re an expert because we’ve gained all this knowledge yet we can just become more and more, these drones can become greater and greater experts regardless of what happens to the physical entity.

Pramod:

Yeah. That software can be aggregated, right? So, you could even theoretically – to build upon your point – you could have again, just going back to the Tesla example, thousands of drones in the field, and they’re all pushing their data back to a central place, whether it’s the cloud or what have you, most likely it is. And it’s being pushed to a central place and then aggregated and trained, right? So you’re getting all these data points. So it doesn’t have to be off of one drawing. It could be off of any drones. And, and yeah, that one drone crashes or something, yeah, the data is most likely, you know, depending on how you, if you’re storing it on the drone itself and there’s a card, if it’s retrievable or if you’re pushing it to the cloud, in most cases you are, and, or can, and so there, you can have the data

Kim:

And can that be a real time data, like in high, tense situations where it’s just, it’s fast, it’s going from between drones to drones.

Pramod:

Yeah. So go ahead.

Tullio:

I guess that’s the promise of 5G, right? Every drone could be an IOT device.

Pramod:

It, depending on how, you know, your, what your communication methods are, would really depend on that answer. But what I was going to basically say was that that data, the question you asked was around really, you know, can you get some information real time? And the answer is yes. So, so in our case in many, in many situations, people want a real-time video feed, and they want to be looking at everything. That takes a lot of bandwidth and a lot of computational power, which means a lot of battery, so you’re using a lot of energy. What we’re saying here is there are many situations where you don’t need to look at dull, boring video for hours upon hours only be notified when you really need to. Think about a security setting, where you have the old, if you remember the – and they still have this- the security guy in the guard shack, and he’s got six cameras he’s got to look at, is he looking at all six of those cameras? Is he doing his homework from night school? I, you know, I don’t know what he’s doing. He might, these days, he’s on his cell phone, probably doing social media. So, think about that. You don’t need to look at all that video, but you do need to know “Hey, somebody’s trying to hop the fence”. Or somebody is trying to unlock that door. Or somebody got within five feet of the perimeter, whatever, whatever the criteria is for that organization that can be trained to be AI, that now the guard is sitting there, but they’re being proactive. When the, when the, you know, when they’re told, “Hey, there’s something going on here, there’s a breach. You need to, you need to go check this out”. We’re actually, we’re actually talking to organizations, both in the military and outside of the military about these security applications, where you have something on the ground, it could be a camera. It could be, in some cases it could be a robot dog, or a little robot, like you guys were showing me earlier. And it could be that “Hey, I see something”. And then it automatically sends a message to a flying drone to say, “Hey, come take an overhead, look here”, right? And then if you see something, let’s go ahead and let the real human know what’s going on. Maybe, you know, this is, that’s just one scenario, but those are scenarios that are actually the future

Carlos:

Pramod. It’s interesting though, we’re discussing a technology that – at least yours – that has a, was inspired initially by a cartoon character, right?

Pramod:

Yeah, yeah.

Carlos:

CatDog.

Pramod:

Yeah. Hey, that’s great. I’m glad you brought that up. Yeah. So, so the, you know, the, the drone that we have right now that we’ve launched into the market as a product for, and I, I didn’t say this earlier, but it can also fly into any situation anywhere, including GPS-denied environments, which is kind of a big deal these days, autonomously, by the way. But yeah, so it has two sections on it, which means you can have two types of payloads and two different things which also makes it fairly unique. So, we have a strong intern culture within our company in terms of we have great relationships with the university of Maryland and Virginia Tech and Northeastern University in Boston. And yeah, and, so they named it, the CatDog and we’re interns. Now we can’t use that publicly because that’s actually a trademark name, but internally we call it the CatDog.

Kim:

I had to Google that that’s a bit before my time.

Carlos:

Back then, when I, when I, I mean, I, I, I knew I know what cat dog is because I have a kid, so he knows what the cartoon is. So, it kind of, it was kind of creepy, right? You have one animal in, two animals in one body. It was like, great. But anyway, I understand the concept. So thank you. I got – before I pass it on to, sorry Kim just one more thing. [Kim chimes in] Yeah, I realized that, you know, our viewers and ourselves, we’re all familiar with the drones and with high-end robotics, because we, we know the space, you know, we’ve had a lot of conversations on dojo.live. But there just might be someone out there who’s watching. Who’s fairly – let’s call it “new” – to the world of robotics. Okay? And specifically, to drones. So, my question to you in that regard is, if we have someone in the audience watching this, what would you tell these people who are more concerned about things like information security, or were concerned about maybe data breaches, as it pertains to being a, you know, watch or even the information that is used to use, what kind of security measures are taking in the world of drones to make sure that, that we’re all that to make help people understand that these devices are for the good, you know, to help us, to make our lives easier and more convenient and even save lives. So what would you say to these people who might be concerned about these aspects of air drones technology?

Pramod:

So, if you’re asking about what’s being done to protect the information and the data, is that the question Carlos, I want to make sure.

Carlos:

Yes. That is correct.

Pramod:

Yep. Yeah. So, so I’d say that cyber and robots is still relatively new in terms of how, how you, you know, how you work with that hardware and software, however you know, you can absolutely, we call it harden in the world of robotics. We call it harden the robot, right. We make sure that its data is protected. So, you start by really doing a vulnerabilities assessment, you know, really understanding where you might have some holes, then doing some things, they call penetration testing, where you’re actually testing and poking holes, so to speak and, and then fixing those relatively. So the fact that you know, we, we’re a dual use company, so we’re, we’re working with the government and we’re working with the civilian sector. The government is of course, very serious about their data. And of course, many commercial entities are as well. So, that’s not something to be taken lightly. So, it is something that we address, like, you know, as far as within the design of our robots, it’s something that we think about right from the beginning, how is this going to be protected? So, I would say, you know, to give somebody out there, that’s listening some assurance, I would say the data that’s on these things is taken very, very seriously and absolutely has to be protected.

Kim:

My question actually goes in line with Carlos’ and mine was more in the sense of one thing is protecting the data that you’ve collected. My question is more towards the right of being able to collect that data in the first place. How are you able to determine, or what, are there any regulations or laws around where the drone is able to fly? What you are able to look for, what you’re able to record, etcetera, etcetera. So I think that would be my primary concern. More about the privacy of what happens before you have the data rather than what you’re doing with the data. Well, they’re both important, but the pre-data, how do you get the permission to have this data in the first place?

Pramod:

Well, Kim, you just opened up a whole another topic, I think for dojo.live That you could probably talk about it in one episode just by itself. Yeah, there’s a couple, there’s a whole […] That’s a whole lot to unpack there. Number one there is this trust with robots and autonomy, right? And, and there, you know, people sometimes confuse autonomy and automation. They’re two different things and automation just something’s being done automatically, but autonomy has a little more brains in it, a little more intelligence. And, and so going to the question of privacy, which is really still a, I would say a gray area in many ways, in many cases, is trust, right? So, you know, we, working in the public safety sector have spoken to police departments about this. And there are, I’d say that depending – it really depends on where you are – the rules, the laws are different, but in general there are privacy laws. Like, I can’t legally take my drone, for example, in flight over the airspace of your house, in most jurisdictions, that’s breaking the law. So there are laws, there are a lot of gray areas to areas to. I know that when, when from a, from a practical standpoint, when the police officer was asked in, in a Smart Cities program we were part of about the privacy stuff, he said, “look, we don’t have time for that. We’re just trying to help people or catch the bad guy. Really that’s, that’s it, we don’t have time for this”. But, you know, there has to be some trust there. And you know, there’s facial recognition, software, there’s all these things out there, right? And it really depends on where you are. An example might be on a military base, pretty much anything goes, you might as well assume your privacy’s gone because you’re being watched, right? There’d probably be a camera.

Kim:

I think, unless you’re inside your house, we cannot simply assume that we’re being recorded somewhere.

Tullio:

They’re in the public domain. It’s free for all there’s cameras, everywhere, tracking everything.

Pramod:

So, it is great in a lot of ways. It’s a really, you know, what is, you know, what goes and what doesn’t go.

Tullio:

Okay. So, I just want to unpack a little bit, I see the military or defense applications of this, and people think of drones, sometimes we think of these little drones or homemade drones of some of the military drones and they’re like billion-dollar piece of device, right? Very complex device used in [INAUDIBLE] applications. So, we understand this value in that because you’re saving lives, you’re putting, where normally you would have to send people, you can send drones and do all kinds of reconnaissance work. In the private sector, we could certainly see – for construction or engineering purposes – tracking bridges or buildings, or what have you, to look for anomalies and things of that sort. Right. I mean, we had the incidents of what happened in Florida. Could that have been caught earlier, could that have been avoided? Those are all great questions and hopefully some of this technology can help answer those questions in a positive way. So, where else will this go? Would we see the commercial application allowing you to get to places that would otherwise put humans at risk? Can it be used for things like scanning now that we have a virus that doesn’t seem to be wanting to go away, right? Can it, can it be used, can a similar technology be used to go into a place and scan and see if there’s particles in the air? You know, if the coronavirus is in the air and warn people about it, I mean, what are, what are some of the other applications that this could be used for to improve people’s lives and in many cases save lives.

Pramod:

Yeah. So you know, the, the applications are endless. If we use the corona example, there actually are companies that are utilizing drones to third, relatively large, and they have tanks and they, they have like Clorox or what have you in them, and they’re spraying stadiums, for example, right? So, for example, if, if, if, you know, imagine if you will, in the future, if this is an application that, that, you know, people go with, but I do know right now, they’re, you know, they’re using these big tanks to spray, but imagine, imagine in the future, if you had a [drone] … a small fleet of unmanned drones, that one would take off, or a couple would take off, whatever, and they would start flying a pattern around the stadium. And then, as they land on their wireless charging pads, two other ones or three other ones, or whatever the number is, take off and continue until they finish the whole thing. That’s one example. We actually last year built a prototype with another company that had UV technologies and the UV technologies, we actually put our sensors on our ground robot. We built in the intelligence into the robot, and the idea was that it would drive around and basically disinfect, right? And so, if it was an office or school, or what have you, that it would disinfect. So those are a couple of other use cases where you could use some autonomous robotics, unmanned technology to really be defensive in that case, right? In the case of your direct question about particles, I actually saw, I don’t know exactly the answer to that, but I did see a video that somebody in South Korea put out, I think some medical Institute, this is right when COVID started, about how the particles travel and things like that. So, yeah, theoretically, yes. If you’ve got a way to detect, now, they did a visually, they had like some sort of visual detection, but if you’re able to detect it that, and then, you know, basically say, “Hey, there’s these particles in the air”, you theoretically could, I haven’t seen that done with a drone application, but I don’t see why it couldn’t be as long as you have the right camera or right sensors on board.

Kim:

Are you using your drones at all in a delivery sense? I mean, I know that there’s probably the commercial sense of like Amazon just dropping the package at your door or whatever, but let’s talk about, like, search and rescue. Let’s say someone’s lost in the mountains, what she pointed on no GPS or whatever the drone is able to find them, but it’s still going to take people two, three days, let’s say to hike in and rescue or whatever. So can your drone, now that the [INAUDIBLE].

Tullio:

I think we lost Kim. I was wondering if, was like in your drone and delivered those guys pizza or water while they, I think it was probably the question of can some of these drones be…actually be strong enough to be used as a rescue, you know, where they can send you a rope and pull you out of there. I mean, they, could they be strong enough to do something like that.

Pramod:

Yeah. So, there are the drones out there that are being built – we’re not building one of them – we’re going […] the direction we’re going as a company is we’re we want to put the intelligence into all of these drones. Right? There’s so many use cases. We do have a small drone that’s on our product roadmap. When I say small, it’s relatively large still, or these delivery and logistics types of missions that you’re talking about. And then if you get specific with, “oh, hey, can we lift this person out of here?” You know, instead of a helicopter yeah, there are some heavy lift drones that are being designed that I don’t think they’ve done that ever yet, that they’re theoretically, you know, could lift that kind of weight, you know, I’m seeing drones that can lift, you know, a couple of hundred pounds as an example, right? So again, how far can they travel? Well, that’s the problem, right? Long as you know, depending on their propulsion system and some of the better systems out there these days we’ll, you know, go out and, you know, fly for an hour and max, but you know, if you’re going out in the mountains and things like that, you probably need a little bit more time than that, just depends. So, but the bottom line is the, this is the future. The future is that yes, you, you should be, you theoretically should be able to do these things. It’s all about the technology. It’s all about the use case. It’s all about the demand as well. You know, who’s demanding this, so, you know, delivery, logistics, absolute no brainer. Yes. It’s happening already. On the battlefield, it’s happening in the medical world. And it’s in most cases, it’s small little pockets of pilot projects and things like that, but I absolutely seeing it being ubiquitous. There is still a lot of challenges left to get to where it’s ubiquitous, you know, regulatory challenges is probably the biggest one. Right now, in the U S if you’re going to do this sort of thing, you have to be able to merge the national airspace system with what we call the “unmanned traffic management system”. And that’s still a work in progress.

Tullio:

Yeah. I think we had a guest about that, AirMap, a couple of years ago.

Pramod:

I know those guys. Yeah. They were pioneers on that whole idea. And since then, there’s been a proliferation of companies that are attacking that world in different ways. But AirMap was definitely a pioneer you know, for like, “Hey, the vision, here’s the vision”.

Tullio:

Well, we’re coming up on time. In fact, we’re up on time, but it sounds as though when it comes to what was otherwise difficult to accomplish with human beings, you know, getting to location, tracking, just the logistics of doing the things that we talked about with drones and the fact that AI makes them intelligent, and the autonomous drones allows to do things that would otherwise be impossible to scale, at least to scale from a human perspective, or even get to, it definitely is creating a better quality of life or improving the management of risk to life with these technologies. So, it’s fantastic to hear that. Tell us a little bit about, as we come to an end, the company’s culture, what kind of people might want to come work with you guys? What do you look for?

Pramod:

Well, you know, we’re very fortunate to have, I would say a great culture. And we have […] you know, we have some values and things that, that, that really guide us, right? So we look for those kinds of people. I’ll give you a couple examples. We look for people that are self-starters. You know, they’re accountable for themselves and …but at the same time accountable for themselves, but also good team players. We have a lot of aviation themes in our company. So, one of those core values that we have is something called “check your six”. So, if you remember where that, I don’t know if you know where that came from, but that came from World War One, when we first started seeing fighter planes, people using airplanes to fight, and they couldn’t, they couldn’t see behind them. So, their buddies would say, “Hey, I got your six”, you know, so not “check your six”, but “I’ve got your six”. I’ve got your six implies I’m going to be there to back you up and help you out, right? So, we want, it’s really a team, very team, a team-oriented culture. We look for team players that will contribute and be part of the solution and aren’t necessarily there just for their own individual glory. And you know, individual glory comes along with being part of the team. So…

Tullio:

Awesome. Thank you for sharing that with us. Thanks for being with us today. We wish you a lot of success doing a lot of good here to help improve the lives of people using technology. It’s always great to hear that stat, just bear with us as we go up the air and, and just a minute, Carlos, what do we got coming up for the rest of the week?

Carlos:

We… thank you, Tullio. We have one more guest that’s tomorrow. Remember folks that on Thursday, we’re not going to have, we’re not going to be airing a dojo.live, But tomorrow we’ll be speaking with Paul Hanges, The CEO of JibJab, which is a digital entertainment company. The topic is going to be innovating in a box, how to push the limits while remaining true for the business mission. So that’s exactly what we’ll be discussing tomorrow, right? Tomorrow, right here on dojo live at 12:00 PM Pacific folks. So join us and be safe.

 

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