>>Okay, welcome back everyone to the cubes coverage here in Las Vegas for AWS re Mars, Remar stands for machine learning, automation, robotics, and space. Part of thehow is reinforces security. And the big show reinvent at the end of the year is the marquee event. Of course, the queues at all three and more coverage here. We've got a great guest here. Ryan re practice lead data analytics, machine learning at mission cloud. Ryan. Thanks for joining me. Absolutely >>Glad. >>So we were talking before he came on camera about mission cloud. It's not a mission as in a space mission. That's just the name of the company to help people with their mission to move to the cloud. And we're a space show to make that it's almost like plausible. I can see a mission cloud coming someday. >>Yeah, absolutely. >>You got >>The name. We got it. We're ready. >>You guys help customers get to the cloud. So you're working with all the technologies on AWS stack and people who are either lifting and shifting or cloud native born in the cloud, right? Absolutely. >>Yeah. I mean, we often see some companies talk about lift and shift, but you know, we try to get them past that because often a lift and shift means like, say you're on Oracle, you're bringing your Oracle licensing, but a lot of companies want to, you know, innovate and migrate more than they want to lift and shift. So that's really what we're seeing in market. >>You see more migration. Yeah. Less lift and shift. >>Yeah, exactly. Because they, they're trying to get out of an Oracle license. Right. They're seeing if that's super expensive and you know, you can get a much cheaper product on AWS. >>Yeah. What's the cutting up areas right now that you're seeing with cloud Amazon. Cause you know, Amazon, you know, is at their, their birthday, you know, dynamo you to sell with their 10th birthday. Where are they in your mind relative to the enterprise in terms of the services and where this goes next in terms of the on-prem you got the hybrid model. Everyone sees that, but like you got outpost. Mm. Not doing so as good as say EKS or other cool serverless stuff. >>Yeah. I mean, that's a great question. One of the things that's you see from AWS is really innovation, right? They're out there, they have over 400 microservices. So they're looking at all the different areas you have on the cloud and that people are trying to use. And they're creating these microservices that you string together, you architect them all up so that you can create what you're looking for. One of the big things we're seeing, right, is with SageMaker. A lot of people are coming in, looking for ML projects, trying to use all the hype that you see around that doing prediction, NLP and computer vision are super hot right now we've helped a lot of companies, you know, start to build out these NLP models where they're doing, you know, all kinds of stuff you use. 'em in gene research, you know, they're trying to do improvements in drugs and therapeutics. It's really awesome. And then we do some eCommerce stuff where people are just looking at, you know, how do I figure out what are similar things on similar websites, right. For, for search companies. So >>Awesome. Take me through the profile of your customer. You have the mix of business. Can you break down the, the target of the small, medium size enterprise, large all the above. >>Yeah. So mission started working with a lot of startups and SMBs and then as we've grown and become, you know, a much larger company that has all the different focus areas, we started to get into enterprise as well and help a lot of pretty well known enterprises out there that are, you know, not able to find the staff that they need and really want to get into >>The cloud. I wanted to dig into the staffing issues and also to the digital transformation journey. Okay. It okay. We all kind of know what's turning into the more dashboards, more automation, DevOps, cloud, native applications. All good. Yeah. And I can see that journey path. Now the reality is how do you get people who are gonna be capable of doing the ML, doing the DevOps dev sec ops. But what about cyber security? I mean is a ton of range of issues that you gotta be competent on to kind of survive in this multi-disciplined world, just to the old days of I'm the top of rack switch guy is over. >>Absolutely. Yeah. You know, it's a really good question. It's really hard. And that's why, you know, AWS has built out that partner ecosystem because they know companies can't hire enough people to do that. You know, if you look at just a migration into a data lake, you know, on-prem often you had one guy doing it, but if you want to go to the cloud, it's like you said, right, you need a security guy. You need to have a data architect. You need to have a cloud architect. You need to have a data engineer. So, you know, in the old days maybe you needed one guy. Now you have to have five. And so that's really why partners are valuable to customers is we're able to come in, bring those resources, get everything done quickly, and then, you know, turn >>It over. Yeah. We were talking again before we came on camera here live, you, you guys have a service led business, but the rise of MSPs managed service providers is huge. We're seeing it everywhere mainly because the cloud actually enables that you're seeing it for things like Kubernetes, serverless, certain microservices have certain domain expertise and people are making a living, providing great managed services. You guys have managed services. What's that phenomenon. Do you agree with it? And how do you, why did that come about and what, how does it keep going? Is it a trend or is it a one trick pony? >>I think it's a trend. I mean, what you have, it's the same skills gap, right? Is companies no longer want that single point of failure? You know, we have a pool model with our managed services where your team's working with a group of people. And so, you know, we have that knowledge and it's spread out. And so if you're coming in and you need help with Kubernetes, we got a Kubernetes guy in that pool to help you, right. If you need, you know, data, we got a data guy. And so it just makes it a lot easier where, Hey, I can pay the same as one guy and get a whole team of like 12 people that can be interchangeable onto my project. So, you know, I think you're gonna see managed services continue to rise and companies, you know, just working in that space. >>Do you see a new skill set coming? That's kind of got visibility right now, but not full visibility. That's going to be needed. I asked this because the environment's changing for the better obviously, but you're seeing companies that are highly valued, like data bricks, snowflake, they're getting killed on valuation. So they gotta have a hard time retaining talent. In my opinion, my opinion probably be true, but you know, you can't, you know, if you're data breach, you can't raise that 45 billion valuation try to hire senior people. They're gonna be underwater from day one. So there's gonna be a real slow down in these unicorns, these mega unicorns, deck, unicorns, whatever they're called because they gotta refactor the company, stock equity package. They attract people. So they gotta put them on a flat foot. And the next question is, do they actually have the juice, the goods to go to the new market? That's another question. So what I mean, what's your take on you're in the trenches. You're in the front lines. >>Yeah, that's a great question. I mean, and it's hard for me to think about whether they have the juice. I think snowflake and data bricks have been great for the market. They've come in. They've innovated, you know, snowflake was cloud native first. So they were built for the cloud. And what that's done is push all the hyperscalers to improve their products, right. AWS has gone through and you know, drastically over the last three years, improved Redshift. Like, I mean it's night and day from three years ago. Did, >>And you think snowflake put that pressure on them? >>Snowflake. Absolutely. Put that pressure on them. You know, I don't know whether they would've gotten to that same level if snowflake wasn't out there stealing market share. But now when you look at it, Redshift is much cheaper than snowflake. So how long are people gonna pay that tax to have snowflake versus switching over snowflakes? >>Got a nice data. Clean room, had some nice lock in features. Only on snowflake. The question is, will that last clean room? I see you smiling. Go ahead. >>Clean. Room's a concept that was actually made by Google. I know Snowflake's trying to capture it as their own, but, but Google's the one that actually launched the clean room concept because of marketing and, and all of that. >>Google also launches semantic layer, which Snowflake's trying to copy that. Does that, what does that mean to you when you hear the word semantic layer? What does that mean? >>And semantic layer just is really all about meta tags, right? How am I going through to figure out what data do I actually have in my data lake so that I can pull it for whatever I'm trying to do, whether it's dashboarding or whether it's machine learning. You're just trying to organize your data better. >>Ryan, you should be a cue post. You're like a masterclass here in, in it and cloud native. I gotta ask you since you're here, since we're having the masterclass being put in a clinic here, lot of clients are confused between how to handle the control plane and the data plane cause machine learning right now is at an all time high. You're seeing deep racer. You're seeing robotic space, all driving by machine learning. SW. He said it today, the, the companion coder, right? The, the code whisperer, that's only gonna get stronger. So machine learning needs data. It feeds on data. So everyone right now is trying to put data in silos. Okay? Cause they think, oh, compliance, you gotta create a data plane and a control plane that makes it highly available. So that can be shared >>Right >>Now. A lot of people are trying to own the data plane and some are trying to own the control plane or both. Right? What's your view on that? Because I see customers say, look, I want to own my own data cause I can control it. Control plane. I can maybe do other things. And some are saying, I don't know what to do. And they're getting forced to take both to control plane and a data plane from a vendor, right? What's your, what's your reaction to that? >>So it's pretty interesting. I actually was presenting at a tech target conference this week on exactly this concept, right, where we're seeing more and more words out there, right? It was data warehouse and it was data lake and it's lake house. And it's a data mesh and it's a data fabric. And some of the concepts you're talking about really come into that data, match data fabric space. And you know, what you're seeing is data's gonna become a product right, where you're gonna be buying a product and the silos yes. Silos exist. But what, what companies have to start doing is, and this is the whole data mesh concept is, Hey yes, you finance department. You can own your silo, but now you have to have an output product. That's a data product that every other part of your company can subscribe to that data product and use it in their algorithms or their dashboard so that they can get that 360 degree view of the customer. So it's really, you know, key that, you know, you work within your business. Some business are gonna have that silo where the data mesh works. Great. Others are gonna go. >>And what do you think about that? Because I mean, my thesis would be, Hey, more data, better machine learning. Right. Is that the concept? >>So, or that's a misconception or, >>Okay. So what's the, what's the rationale to share the data like that and data mission. >>So having more of the right data here, it is improves. Just having more data in general, doesn't improve, right? And often the problem is in the silos you're getting to is you don't have all the data you want. Right. I was doing a big project about shipping and there's PII data. When you talk about shipping, right? Person's addresses, that's owned by one department and you can't get there. Right. But how am I supposed to estimate the cost of shipping if I can't get, you know, data from where a person lives. Right. It's just >>Not. So none of the wrinkle in the equation is latency. Okay. The right data at the right time is another factor is that factored into data mesh versus these other approaches. Because I mean, you can, people are streaming data. I get that. We're seeing a lot of that. But talking about getting data fast enough before the decisions are made, is that an issue or is this just BS? >>I'm going with BS. Okay. So people talk about real time real. Time's great if you need it, but it's really expensive to do. Most people don't need real time. Right. They're really looking for, I need an hourly dashboard or I need a daily dashboard. And so pushing into real time, just gonna be an added expense that you don't >>Really need. Like cyber maybe is that not maybe need real time. >>Well, cyber security add. I mean, there's definitely certain applications that you need real time, >>But don't over invest in fantasy if you don't need an an hour's fine. Right, >>Right. Yeah. If you're, if you're a business and you're looking at your financials, do you need your financials every second? Is that gonna do anything for you? Got >>It. Yeah. Yeah. And so this comes back down to data architecture. So the next question I asked, cause I had a great country with the Fiddler AI CEO, CEO earlier, and he was at Facebook and then Pinterest, he was a data, you know, an architect and built everything. He said themselves. We were talking about all the stuff that's available now are all the platforms and tools available to essentially build the next Facebook if someone wanted to from scratch. I mean, hypothetically thought exercise. So the ability to actually ramp up and code a complete throwaway and rebuild from the ground up is possible. >>Absolutely. >>And so the question is, okay, how do you do it? How long would it take? I mean, in an ideal scenario, not, you know, make some assumptions here, you got the budget, you got the people, how long to completely roll out a brand new platform. >>Now it's funny, you asked that because about a year ago I was asked that exact same question by a customer that was in the religious space that basically wanted to build a combination of Facebook, Netflix, and Amazon altogether for the religious space, for religious goods and you know, church sermons, we estimated for him about a year and about $9 million to do it. >>I mean, that's a, that's a, a round these days. Yeah. Series a. So it's possible. Absolutely. So enterprises, what's holding them back, just dogma process, old school legacy, or are people taking the bold move to take more aggressive, swiping out old stuff and just completely rebuilding? Or is it a talent issue? What's the, what's the enterprise current mode of reset, >>You know, I think it really depends on the enterprise and their aversion to risk. Right. You know, some enterprises and companies are really out there wanting to innovate, you know, I mean there's companies, you know, an air conditioning company that we worked with, that's totally, you know, nest was eaten all their business. So they came in and created a whole T division, you know, to, to chase that business, that nest stole from them. So I think it, I think often a company's not necessarily gonna innovate until somebody comes in and starts stealing their >>Lunch. You know, Ryan, Andy, Jess, we talked about this two reinvents ago. And then Adam Eski said the same thing this year on a different vector, but kind of building on what Andy Jessey said. And it's like, you could actually take new territory down faster. You don't have to kill the old, no I'm paraphrasing. You don't have to kill the old to bring in the new, you can actually move on new ideas with a clean sheet of paper if you have that builder mindset. And I think that to me is where I'm seeing. And I'd love to get your reaction because if you see an opportunity to take advantage and take territory and you have the right budget time and people, you can get it. Oh absolutely. It's gettable. So a lot of people have this fear of, oh, we're, that's not our core competency. And, and they they're the frog and boiling water. >>You know, my answer to that is I think part of it's VCs, right? Yeah. VCs have come in and they see the value of a company often by how many people you hire, right. Hire more people. And the value is gonna go up. But often as a startup, you can't hire good people. So I'm like, well, why are you gonna go hire a bunch of random people? You should go to a firm like ours that knows AWS and can build it quickly for you, cuz then you're gonna get to the market faster versus just trying to hire a bunch of people in >>Someone. Right. I really appreciate you coming on. I'd love to have you back on the cube again, sometime your expertise and your insights are awesome. Give a commercial for the company, what you guys are doing, who you're looking for, what you want to do, hiring or whatever your goals are. Take a minute to explain what you guys are doing and give a quick plug. >>Awesome. Yeah. So mission cloud, you know, we're a premier AWS consulting firm. You know, if you're looking to go to AWS or you're in AWS and you need help and support, we have a full team, we do everything. Resell, MSP professional services. We can get you into the cloud optimize. You make everything run as fast as possible. I also have a full machine learning team. Since we're here at re Mars, we can build you models. We can get 'em into production, can make sure everything's smooth. The company's hiring. We're looking to double in size this year. So, you know, look me up on LinkedIn, wherever happy to, to take, >>You mentioned the cube, you get a 20% discount. He's like, no, I don't approve that. Thanks for coming on the key. Really appreciate it. Again. Machine learning swaping said on stage this, you can be a full time job just tracking just the open source projects. Never mind all the different tools and like platform. So I think you're gonna have a good, good tailwind for your business. Thanks for coming on the queue. Appreciate it. Ryan Reese here on the queue. I'm John furry more live coverage here at re Mars 2022. After this short break, stay with us.

>>Everyone welcome back from the cubes coverage here in Las Vegas for Aus re Mars. It's one of the re shows, as we know, reinvent is the big show. Now they have focus, shows reinforces coming up that security Remar is here. Machine learning, automation, robotics, and space. I'm John for your host, Michael Mike Miller here, director of machine learning thought leadership with AWS. Great to see you again. Yeah. Give alumni welcome back here. Back every time we got deep racer, always to talk >>About, Hey John, thanks for having me once again. It's great to be here. I appreciate it. >>So I want to get into the deep racer in context here, but first re Mars is a show. That's getting a lot of buzz, a lot of press. Um, not a lot of news, cuz it's not a newsy show. It's more of a builder kind of a convergence show, but a lot is happening here. It's almost a, a moment in time that I think's gonna be one of those timeless moments where we're gonna look back and saying that year at re Mars was an inflection point. It just seems like everything's pumping machine learning, scaling robotics is hot. It's now transforming fast. Just like the back office data center did years ago. Yeah. And so like a surge is coming. >>Yeah. >>What, what's your take of this show? >>Yeah. And all of these three or four components are all coming together. Right. And they're intersecting rather than just being in silos. Right. So we're seeing machine learning, enabled perception sort of on robots, um, applied to space and sort of these, uh, extra sort of application initiatives. Um, and that's, what's really exciting about this show is seeing all these things come together and all the industry-wide examples, um, of amazing perception and robotics kind of landing together. So, >>So the people out there that aren't yet inside the ropes of the show, what does it mean to them? This show? What, what, what they're gonna be what's in it for me, what's all this show. What does it mean? >>Yeah. It's just a glimpse into where things are headed. Right. And it's sort of the tip of the iceberg. It's sort of the beginning of the wave of, um, you know, these sort of advanced capabilities that we're gonna see imbued in applications, um, across all different industries. >>Awesome. Well, great to have you in the cube. Every time we have an event we wanna bring you on because deep racers become a, the hottest, I won't say cult following because it's no longer cult following. It's become massive following. Um, and which started out as an IOT, I think raspberry pie first time was like a, like >>A, we did a little camera initially camera >>And it was just a kind of a fun, little clever, I won't say hack, but just having a project that just took on a life OFS own, where are we? What's the update with racer you're here with the track. Yeah, >>Possibly >>You got the track and competing with the big dogs, literally dog, you got spot over there. Boston dynamics. >>Well we'll, we'll invite them over to the track later. Yeah. So deep razor, you know, is the fastest way to get hands on with machine learning. You know, we designed it as, uh, a way for developers to have fun while learning about this particular machine learning technique called reinforcement learning, which is all about using, uh, a simulation, uh, to teach the robot how to learn via trial and error. So deep racer includes a 3d racing simulator where you can train your model via trial and error. It includes the physical car. So you can take, uh, the model that you trained in the cloud, download it to this one 18th scale, um, kind of RC car. That's been imbued with an extra sensor. So we have a camera on the front. We've got an extra, uh, Intel, X, 86 processor inside here. Um, and this thing will drive itself, autonomously around the track. And of course what's a track and uh, some cars driving around it without a little competition. So we've got the deep racer league that sort of sits on top of this and adds a little spice to the whole thing. It's >>It's, it's like formula one for nerds. It really is. It's so good because a lot of people will have to readjust their models cuz they go off the track and I see people and it's oh my, then they gotta reset. This has turned into quite the phenomenon and it's fun to watch and every year it gets more competitive. I know you guys have a cut list that reinvent, it's almost like a, a super score gets you up. Yeah. Take, take us through the reinvents coming up. Sure. What's going on with the track there and then we'll get into some of the new adoption in terms of the people. >>Yeah, absolutely. So, uh, you know, we have monthly online races where we have a new track every month that challenges our, our developers to retrain their model or sort of tweak the existing model that they've trained to adapt for those new courses. Then at physical events like here at re Mars and at our AWS summits around the world, we have physical, uh, races. Um, and we crown a champion at each one of those races. You may have heard some cheering a minute ago. Yeah. That was our finals over there. We've got some really fast cars, fast models racing today. Um, so we take the winners from each of those two circuits, the virtual and the physical and they, the top ones of them come together at reinvent every year in November, December. Um, and we have a set of knockout rounds, championship rounds where these guys get the field gets narrowed to 10 racers and then those 10 racers, uh, race to hold up the championship cup and, um, earn, earn, uh, you know, a whole set of prizes, either cash or, or, you know, scholarships or, you know, tuition funds, whatever the, uh, the developer is most interested >>In. You know, I ask you this question every time you come on the cube because I I'm smiling. That's, it's so much fun. I mean, if I had not been with the cube anyway, I'd love to do this. Um, would you ever imagine when you first started this, that it would be such so popular and at the rise of eSports? So, you know, discord is booming. Yeah. The QB has a discord channel now. Sure, sure. Not that good on it yet, but we'll get there, but just the gaming culture, the nerd culture, the robotics clubs, the young people, just nerds who wanna compete. You never thought that would be this big. We, >>We were so surprised by a couple key things after we launched deep racer, you know, we envisioned this as a way for, you know, developers who had already graduated from school. They were in a company they wanted to grow their machine learning skills. Individuals could adopt this. What we saw was individuals were taking these devices and these concepts back to their companies. And they're saying, this is really fun. Like we should do something around this. And we saw companies like JPMC and Accenture and Morningstar into it and national Australia bank all adopting deep racer as a way to engage, excite their employees, but then also create some fun collaboration opportunities. Um, the second thing that was surprising was the interest from students. And it was actually really difficult for students to use deep racer because you needed an AWS account. You had to have a credit card. You might, you might get billed. There was a free tier involved. Um, so what we did this past year was we launched the deep racer student league, um, which caters to students 16 or over in high school or in college, uh, deep Razer student includes 10 hours a month of free training, um, so that they can train their models in the cloud. And of course the same series of virtual monthly events for them to race against each other and win, win prizes. >>So they don't have to go onto the dark web hack someone's credit card, get a proton email account just to get a deep Razer that's right. They can now come in on their own. >>That's right. That's right. They can log into that virtual the virtual environment, um, and get access. And, and one of the other things that we realized, um, and, and that's a common kind of, uh, realization across the industry is both the need for the democratization of machine learning. But also how can we address the skills gap for future ML learners? Um, and this applies to the, the, the world of students kind of engaging. And we said, Hey, you know, um, the world's gonna see the most successful and innovative ideas come from the widest possible range of participants. And so we knew that there were some issues with, um, you know, underserved and underrepresented minorities accessing this technology and getting the ML education to be successful. So we partnered with Intel and Udacity and launched the AI and ML scholarship program this past year. And it's also built on top of deep Bracer student. So now students, um, can register and opt into the scholarship program and we're gonna give out, uh, Udacity scholarships to 2000 students, um, at the end of this year who compete in AWS deep racer student racers, and also go through all of the learning modules online. >>Okay. Hold on, lets back up. Cuz it sounds, this sounds pretty cool. All right. So we kind went fast on that a little bit slow today at the end of the day. So if they sign up for the student account, which is lowered the batteries for, and they Intel and a desk, this is a courseware for the machine learning that's right. So in order to participate, you gotta take some courseware, check the boxes and, and, and Intel is paying for this or you get rewarded with the scholarship after the fact. >>So Intel's a partner of ours in, in putting this on. So it's both, um, helping kind of fund the scholarships for students, but also participating. So for the students who, um, get qualified for the scholarship and, and win one of those 2000 Udacity Nanodegree scholarships, uh, they also will get mentoring opportunities. So AWS and Intel, um, professionals will help mentor these students, uh, give them career advice, give them technical advice. C >>They'll they're getting smarter. Absolutely. So I'm just gonna get to data here. So is it money or credits for the, for the training? >>That's the scholarship or both? Yes. So, so the, the student training is free for students. Yep. They get 10 hours a month, no credits they need to redeem or anything. It's just, you log in and you get your account. Um, then the 2000, uh, Udacity scholarships, those are just scholarships that are awarded to, to the winners of the student, um, scholarship program. It's a four month long, uh, class on Python programming for >>AI so's real education. Yeah. It's like real, real, so ones here's 10 hours. Here's check the box. Here's here's the manual. Yep. >>Everybody gets access to that. That's >>Free. >>Yep. >>To the student over 16. Yes. Free. So that probably gonna increase the numbers. What kind of numbers are you looking at now? Yeah. In terms of scope to scale here for me. Yeah. Scope it >>Out. What's the numbers we've, we've been, uh, pleasantly surprised. We've got over 55,000 students from over 180 countries around the world that have signed up for the deep racer student program and of those over 30,000 have opted into that scholarship program. So we're seeing huge interest, um, from across the globe in, in this virtual students, um, opportunity, you know, and students are taking advantage of those 20 hours of learning. They're taking advantage of the fun, deep racer kind of hands on racing. Um, and obviously a large number of them are also interested in this scholarship opportunity >>Or how many people are in the AWS deep racer, um, group. Now, because now someone's gotta work on this stuff. It's went from a side hustle to like a full initiative. Well, >>You know, we're pretty efficient with what we, you know, we're pretty efficient. You've probably read about the two pizza teams at Amazon. So we keep ourselves pretty streamlined, but we're really proud of, um, what we've been able to bring to the table. And, you know, over those pandemic years, we really focused on that virtual experience in viewing it with those gaming kind of gamification sort of elements. You know, one of the things we did for the students is just like you guys, we have a discord channel, so not only can the students get hands on, but they also have this built in community of other students now to help support them bounce ideas off of and, you know, improve their learning. >>Awesome. So what's next, take us through after this event and what's going on for you more competitions. >>Yeah. So we're gonna be at the remainder of the AWS summits around the world. So places like Mexico city, you know, uh, this week we were in Milan, um, you know, we've got some AWS public sector, um, activities that are happening. Some of those are focused on students. So we've had student events in, um, Ottawa in Canada. We've had a student event in Japan. We've had a student event in, um, Australia, New Zealand. And so we've got events, both for students as well as for the professionals who wanna compete in the league happening around the world. And again, culminating at reinvent. So we'll be back here in Vegas, um, at the beginning of December where our champions will, uh, compete to ho to come. >>So you guys are going to all the summits, absolutely. Most of the summits or >>All of them, anytime there's a physical summit, we'll be there with a track and cars and give developers the opportunity to >>The track is always open. >>Absolutely. All >>Right. Well, thanks for coming on the cube with the update. Appreciate it, >>Mike. Thanks, John. It was great to be >>Here. Pleasure to know you appreciate it. Love that program. All right. Cube coverage here. Deep race are always the hit. It's a fixture at all the events, more exciting than the cube. Some say, but uh, almost great to have you on Mike. Uh, great success. Check it out free to students. The barrier's been lower to get in every robotics club. Every math club, every science club should be signing up for this. Uh, it's a lot of fun and it's cool. And of course you learn machine learning. I mean, come on. There's one to learn that. All right. Cube coverage. Coming back after this short break.

>>Okay, welcome back everyone. This is the Cube's coverage of S reinve rein Mars. I said reinvent all my VES months away. Re Mars machine learning, automation, robotics, and space. I'm John feer, host of the cube, an exciting guest here, bringing on special guest more robot robots are welcome on the cube. We're gonna have that segment here. Mike Dooley co-founder and CEO of Labrador systems. Mike, welcome to the cube. Thanks. >>Coming on. Thank, thank you so much. Yeah. Labrador systems. We're a company is developing a new type of assistive robot for people in the home. And you know, our mission is really to help people live independently. And so we're about to show a robot that's it looks like my, what used to be in a warehouse or other places, but it's being designed to be both robust enough to operate in real world settings, help people that may be aging and using a Walker wheelchair. A cane could have early onset health conditions like Parkinson's and things like that. So >>Let me, let me set this up first, before you get into the, the demo, because I think here at re Mars, one of the things that's coming outta the show besides the cool vibe, right? Is that materials handling? Isn't the only thing you've seen with robotics. Yeah. You're seeing a lot more life industrial impact. And this is an example of one of that, isn't >>It? Yeah. We just actually got an award. It's a Joseph EGL Bergo was the first person to actually put robots in factories and automation. And in doing that, um, he set up grant for robots going beyond that, to help people live in it. So we're the first recipient of that. But yeah, I think that robots, they're not the, what you think about with Rosie yet. We're the wrong way from that, but they're, they can do really meaningful things. >>And before we get the demo, your mission hearing, what you're gonna show here is a lot of hard work and we know how hard it is. What's the mission. What's the vision. >>The mission is to help people live more independently on their own terms. Uh, we're, there's, it's an innate part of the human condition that at some point in our lives, it becomes more difficult to move ourselves or move things around it. And that is a huge impact on our independence. So when we're putting this robot in pilots, we're helping people try to regain degrees of independence, be more active deal with whatever situation they want, but under their terms and have, have control over their life. >>Okay, well, let's get into it. May I offer you a glass of water? Well, you >>Know, I have a robot that just happens to be really good at delivering things, including water. Um, we just actually pulled these out of our refrigerator on our last demo. So why don't we bring over the retriever? And so we're gonna command it to come on in. So this is a Labrador retriever. These robots have been in homes. This robot itself has been in homes, helping people do activities like this. It's able to sort of go from place to place it automatically navigates itself. Uh, just like we've been called a self-driving shelf, um, as an example, but it's meant to be very friendly, can come to a position like this could be by my armchair and it would automatically park. And then I could do something like I can pick up, okay, I want some water and maybe I want to drink it out of a cup and I can do this. And if I have a cough or something else, cough drops. My phone, all sorts of things can be in there. Um, so the purpose of the retriever is really to be this extra pair of hands, to keep things close by and move things. And it can automatically adjust to any hide or position. And if I, even if I block it like a safety, it, it >>Stops. And someone who say disabled or can't move is recovering or has some as aging or whatever the case is. This comes to them. It's autonomous in it sense. Is that that what works or yeah. Is it guided? How does >>It, it works on a series of bus stops. So the in robotics, we call those way points. But when we're talking to people, the bus stops are the places you want it to go. You have a bus stop by the front door, your kitchen sink, the refrigerator, your armchair, the laundry machine, you won't closet it. <laugh>. And with that simple metaphor, we, we train the robot in a couple hours. We create all these routes, just like a subway map. And then the robot is autonomous. So I can hit a button. I can hit my cell phone, or I can say Alexa ass lab, one to come to the kitchen. The robot will autonomously navigate through everything, go around the pets park itself. And it raises and lowers to bring things with and reach. So I'm sitting and it might lower itself down. So I can just comfortably get something at the kitchen. I, it could just go right to the level of the countertop. So it's very easy for someone that has an issue to move things with with limited, uh, challenges. >>And this really illustrates to this show again. Yeah. Talk about the impact here. Cause we're at a historic moment in robotics. >>We are. Yeah. >>What's your reaction to that? Tell your, share your vision >>On that. I've been in robotics for 25 years. Um, and I started, I actually started working actually at Lego and launching Lego Mindstorms, the end of the nineties. So I have like CEO just last night again, they gush over like you did that. Yeah. <laugh> and again, I'm pretty old school. And so we've my career. If I've been working through from toys onto like robotic floor cleaners, the algorithms that are on Roomba today came from the startup that we were all part of. We're, we're moving things to be bigger and bigger and have a bigger >>Impact. What's it feel like? I mean, cuz I mean I can see the experience and by the way, it's hardcore robotics communities out there, but now it's still mainstream. It's opening up the aperture of robotics. Yeah. It's the prime time is right now and it's an inflection point. >>Well, and it's also a point where we desperately need it. So we have incredible work for shortages <laugh> and it's not that we're, these robots are not to take people jobs away it's to do the work that people don't want to do and try to make, you know, free them up for things that are more important. Yeah. In senior care, that's the high touch we want caregivers to be helping people get outta their bed, help them safely move from place to place things that robots aren't at yet. Yeah. But for getting the garbage, for getting a drink or giving the person the freedom to say, do I wanna ask my caregiver or my spouse to do that? Or do I wanna do it myself? And so robots can be incredibly liberating experience if they're, if they're done in the right way and they're done well, >>It's a choice. It actually comes down to choice. I remember this argument way back when, oh, ATM's gonna kill the bank teller. In fact more bank tellers emerged. Right. And so there's choices come out there and, but there's still more advances to do. What is you, what do you see as milestones for the industry as you start to seeing better handling better voice activation cameras on board. I noticed some cameras in there. Yeah. So we're starting to see the, some of the smaller, faster, cheaper >>It's it's especially yeah. Faster. Cheaper is what we're after. So can we redo? So like the gyros that are on this type of robot used to be like in the tens of thousands of dollars 20 or 30 years ago. And, and then when you started seeing Roomba and the floor cleaners come out, those started what happened was basically the gyro on here that what's happening in consumer electronics, the ability for the iPhone to play, you know, the game in turn and, and do portrait and landscape. That actually is what enables all these robots that clean your floors to do very tight angles. What we're doing is this migration of consumer electronics then gets robbed and, and adopted over in that. So it's really about it's I, it's not that you're gonna see things radically change. It's just that you're gonna see more and more applications get more sophisticated and become more affordable. Our target is to bring this for a few hundred dollars a month into people's homes. Yeah. Yeah. Um, and make that economy work for as many people as >>Possible. Yeah. Mike, what a great, great illustration of great point there now on your history looking forward. Okay. Smaller Fest are cheaper. Yeah. You're gonna see a human aspect. So technology's kind of getting out of the way now you got a lot in the cloud, you got machine learning, big thing here. There's a human creative side now gonna be a big part of this. Yeah. Can you talk about like how you see that unfolding? Because again, younger people gonna come in, you got a lot more things pre-built I just saw a swaping on stage saying, oh, we, we write subroutines automatically the machine learning like, oh my God, that's so cool. Like, so more is coming for, to, for builders, right. To build what's the playbook gonna look like? How do you see the human aspect, creative crafting building? >>I, I it's, you know, it's a hard Fu future to predict. I think the issue is that humans are always gonna have to be more clever than the AI <laugh>, you know, I, I can't say that enough is that AI can solve some things and it can get smarter and smarter. You task that over and then let's work on the things that can't do. And I think that's intellectually challenging. Like, and I, and I think we have a long way to go, uh, to sort of keep on pushing that forward. So the whole mission is people get to do more interesting things with their life, more dynamic. Think about what the machines should be working on. Yeah. And then move on to the next things. >>Well, a lot of good healthcare implications. Yeah. Uh, senior living people who are themselves, >>All those are place. Yeah. >>Now that you have, um, this kind of almost a perfect storm of innovation coming, and I just think it's gonna be the beginning. You're gonna see a lot of young people come in. Yeah. And a lot of people in school now going down to the elementary school level yeah. Are really immersed in robotics. They're born with it. And certainly as they get older, what kind of disciplines do you see coming into robot? I used to be pretty clear. Yeah. Right. Nerdy, builder, builder. Now it's like what? I got Mac and rice. My code. >>Yeah. My, my co-founder and CEO has a good example. Anybody we interview, we say we really like it. If you think of yourself as an astronaut, going on to a space mission. And, and it's really appropriate being here at R Mars is that normally the astronaut has one specialty, but they have to know enough of the other skills to be able to help out. In case of an emergency robotics is so complex. There's so there's mechanical, there's electrical, there's software, they're perceptual, there's user interface, all of those Fs together. So when we're trying to do a demo and something goes wrong, I can't say why. I only do mechanical. Yeah. You got it. You really have to have a system. So I think if any system architects, people that if you're gonna, if, if you're gonna be, if mechanical is your thing, you better learn a little bit electrical and software. Yeah. If software is your thing, you better not just write code because you need to understand where you're >>Your back. Well, the old days you have to know for trend to run any instrumentation in the old days. So same kind of vibe. So what does that impact on the teamwork side? Because now I can imagine, okay, you got some general purpose knowledge, so math, science, all the disciplines, but the specialties there, I love that right now. Teamwork. Yeah. Because you, you know, I could be a generalism at some point. There's another component I'm gonna need to call my teammate for. >>Yeah. Yeah. And you have to have, yeah. So it, yeah, we're a small team, so it's a little bit easier right now, but even the technology. So like there's a, what, this is, this runs on Linux and that runs on Ross, which is a robotics operating system. The modules are, are the, are sorry, the modules, I mean redundant there, but the, the part that makes the robot go, okay, I'm gonna command it to go here. It's gonna go around it, see an obstacle. This module kicks in, even the elements become module. So that's part of how teams work is that, and, and Amazon has a rule around that is that everything has to have an API. Yeah. I have to be able to express my work and the way that somebody else can come in and talk to it in a very easy way. So you're also going away from like, sort of like the hidden code that only I touch you can't have ownership of that. You have to let your team understand how it works and let them control it and edit it. Well, >>Super exciting. Dan, first of all, great to bring robots on the cube set. Thanks to your team here. Doing that. Yeah. Um, talk about the company. Um, put a plug in, what are you guys doing? Sure. Raising money, getting more staff, more sales. We're give, give a commercial. >>Yeah. So we, we closed the seed round. So we've been around it's actually five years next month. Um, did pre-seed and then we closed the seed round that we announced back at CS. So we debuted the retriever for the first time we had it under wraps. We had it in people's homes for a year before we did that. Um, I, Amazon was one of our early investors and they actually co-led on this last round, along with our friends at iRobot. So yeah. Uh, so we've raised that we're right in the next phase of deploying this, especially going more into senior living now that that's opening up with COVID coming down and looking at helping these workforce issues where there's that crisis. So we'll be raising later this year. So we're starting to sort of do the preview for series a. We're starting to take those pre-orders for robots and for Lois. And then our goal is we're and we're actually already at the factory. So we've been converting this, these there's a version of this robot underway right now at the factory that will probably have engineering units at the end of this year. Yeah. Goal is for, uh, full production with all the supply chain issues for second half of, of next >>Year. Yeah. Well, congratulations. It's a great product. And I gotta ask you what's on the roadmap, how you see this product unfolding. What's the wishlist look like if you had all the dough in the world, what would you do next? What would you be putting on there? Sure. If you had the magic wand what's happening, >>It's a couple variables. I think it's scale. So it's driving the, this whole thing is designed to go down in cost, which improves basically accessibility. More people can afford it. The health system, Medicare, those sorts of folks. See it one. So basically get us into reduction and get us into volume is one part, I think the other ones is adding layers. I, what we, when we see our presentation and the speech we're doing tomorrow, we see this as a force multiplier for a lot of other things in healthcare. So if I bring the blood pressure cuff, like we have on the retrieval, I can be a physical reminder to take your medication, to take the, my, my readings, or we are just con having a conversation with some of our friends of Amazon is bringing an echo show to you when you want to have a conversation and take it away. >>When you don't think about that metaphor of how do I wanna live my life and what do I have control over? And then on top of it, the sensors on the robot, they're pretty sophisticated. So in my case, my mom is still around she's 91, but now in a hospital beded wheelchair could, we've seen her walking differently early, early on, and using things like Intel, real sense and, and computer vision and AI to detect things and just say to her, don't even tell anybody else, we're noticing this. Do you wanna share this with your doctor? Yeah. That's the world. I think that what we're trying to do is lay this out as version 1.0, so that when folks like us are around, it'll something like decades from now, life is so much more better for the options and choices we have. It's >>Really interesting. You know, I liked, um, kind of the theme here. There's a lot of day to day problems that people like to solve. And then there's like the new industrial problems that are emerging that are opportunities. And then there's the save the world kind of vibe. <laugh>, there's help people make things positive, right. You know, solve the climate problems, help people. And so we're kind of at this new era and it's beyond just like sustainability and, you know, bias. That's all gotta get done a new tipping point around the human aspect of >>Things. And you do it economically. I think sometimes you think that, okay, well, you're just doing this cuz you're, you're socially motivated and doesn't, you don't care how many you sell it to just so you can accomplish it. It's their link. The, the cheaper that we can make this, the more people you can impact. I think you're talking about the kids today is the work we did at Lego. In the end of the nineties, you made a, a robotics kit for 200 bucks and millions of kids. Yeah. Did that. And >>Grape pie. I mean, you had accessories to it. Make a developer friendly. >>Yeah, no, exactly. And we're getting all those requests. So I think that's the thing is like, get a new platform, learn what it's like to have this sort of capability and then let the market drive. It, let the people sort of the folks who are gonna be using it that are in a wheelchair, are dealing with Parkinson's or Ms, or other issues. What can we add to that ecosystem? So you it's, it's all about being very human centric in that. Yeah. And making the other parts of the economy make it work for them, make it so that the health system, they get an ROI on this so that, Hey, this is a good thing to put into people's homes. >>And well, I think you have the nice, attractive value proposition to investors. Obviously robotics is super cool and really relevant. Cool, cool. And relevant to me always is nice to have that. So check that, then you got the economics on price, pressure, prove the price down lower. Yeah. Open up the Tams of the market. Right. Make it more viable economically. >>Yeah, definitely. And then, and what we're having, what's driving us that wasn't around seven when we started this about four and a half years ago. Uh, my joke and I don't mean to offend them, but after doing pitching the vision of this in six months, don't be, >>Don't be afraid. We're do we, >>My, my joke. And I'm sort to see more bold about is that VCs don't think they're gonna get old. They're just gonna get rich. And so the idea is that they didn't see themselves in this position and we not Gloo and doom, you can work out, you can be active, but we're living older, longer. We are it's. My mom is born in the depression. She's been in a wheelchair for five years. She might be around for a good, another 10 or 15. And that's wonderful for her, but her need for care is really high. >>Yeah. And the pressure on the family too, there's always, there's always collateral damage on all these impacts. >>There's 53 million unpaid family caregivers in the us. Yeah. Just in the time that we've grown, been doing this, it's grown 4% a year and it's a complicated thing. And it's, it's not just the pressure on you to help your mom or dad or whoever. It's the frustration on their face when they have to always ask for that help. So it's, it's twofold. It's give them some freedom back so they can make a choice. Like my classic example is my mom wants tea. My dad's trying to watch the game. He, she asks for it. It's not hot enough. Sends it back. And that's a currency. Yeah, yeah. That she's losing and, and it's frustration as opposed to give her a choice to say, I'm gonna do this on my own. And I that's just, >>You wanna bring the computer out, do a FaceTime with the family, send it back. Or you mentioned the Alexa there's so many use cases. Oh >>No. We talked about, uh, we talked about putting like a, a device with a CA with a screen on it so she could chat and see pictures. And it says, I don't want to have this in my bedroom. That's my private space. Yeah. But if we could have the robot, bring it in when it's appropriate and take it on go the retriever that's that's >>The whole go fetch what I need right now. That's and then go lie down. Yeah. >>That's what I, I called >>Labrador. Doesn't lie down >>Actually. But well, it lowers down, it lowers down about 25 inches. That's about lying. >>Down's super exciting. And congratulations. I know, um, how passionate you are. It's obvious. Yeah. And being in the business so long, so many accomplishment you had. Yeah. But now is a whole new Dawn. A new era here. >>Yeah. Oh yeah. No, I, we just, it was real. It was on impromptu. It wasn't scheduled. There's a, a post circle on LinkedIn where all the robots got together. <laugh> you know, and they were seeing to hang out. No, and you're seeing stuff that wasn't possible. You look at this and you go, well, what's the big thing. It's a box on wheels. It's like, it wasn't possible to navigate something around the complexity of a home 10 years ago for the price we're doing. Yeah. It wasn't possible to wa have things that walk or spot that can go through construction sites. I, I think people don't realize it's it. It really is changing. And then we're, I think every five years you're gonna be seeing this more bold deployment of these things hitting our lives. It's >>It's super cool. And that's why this show's so popular. It's not obvious to mainstream, but you look at the confluence of all those forces coming together. Yeah. It's just a wonderful thing. Thanks for coming on. Appreciate >>It really, really appreciate you for this >>Time. Great success. Great demo. Mike, do cofounder, the CEO of Labrador systems. Check him out. They have the retriever, uh, future of robotics here. It's all impact all life on the planet. And more space. Two is to keep coverage here at re Mars, stay tuned for more live coverage. After this short break.

>>We're here live in Las Vegas with a cubes coverage of Amazon re Mars. It's a reinvent re Mars reinforced. The big three shows called the res. This is Mars machine learning, automation, robotic and space. It's a program about the future it and the future innovation around industrial cloud scale climate change the moon, a lot of great topics, really connecting all the dots together here in Las Vegas with Amazon re Mars I'm John ER, host of the cube. Our first guest is Howard Hughes program manager, necess Ryan program. Howard is involved with all the action and space and the moon project, which we'll get into Howard. Thanks for coming on the cube. >>Well, Hey, thanks for having me here this morning. Appreciate you guys inviting me here. >>So this show is not obvious to the normal tech observer, the insiders in, in the industry. It's the confluence of a lot of things coming together. It's gonna be obvious very soon because the stuff they're showing here is pretty impressive. It's motivating, it's positive and it's a force for change in good. All of it coming together, space, machine learning, robotics, industrial, you have one of the coolest areas, the space what's going on with your Orion program. You guys got the big moon project statement to >>Explain. Well, let me tell you, I'll start with Orion. Orion is our next human space craft. That's gonna take humans beyond low earth orbit and we're part of the broader Artis campaign. So Artis is our plan, our NASA plan to return the first person of color, first woman, back to the moon. And we're very excited to do that. We have several missions that I could talk to you about starting with in a very few months, Artis one. So Artis one is going to fly on the space launch system, which is gonna be the biggest rocket we call the mega rocket has been built since the Saturn five on top of the SLS is the Ryan spacecraft and that Ryan spacecraft houses four crew members for up to 21 days in deep space. And we'll have an unru test in a few months launch on the S SLS. And Orion's gonna go around the moon for up to 40 days on Aus two, we will have the first test of the humans on board Orion. So four people will fly on Aus two. We will also circle the moon for about 10 to 12 days. And then our third mission will be our landing. >>So the moon is back in play, obviously it's close to the earth. So it's a short flight, relatively speaking the Mars a little bit further out. I'll see everyone as know what's going on in Mars. A lot of people are interested in Mars. Moon's closer. Yes, but there's also new things going on around discovery. Can you share the big story around why the moon what's? Why is the moon so important and why is everyone so excited about it? >>Yeah. You, you know, you know, coming to this conference and talking about sustainability, you know, I mean it is exploration is I think ingrained in our DNA, but it's more than just exploration is about, you know, projecting human presence beyond our earth. And these are the stepping stones. You know, we talk about Amazon talked about day one, and I think about, we are on those very early days where we're building the infrastructure Ryans of transportation infrastructure, and we're gonna build infrastructure on the moon to learn how to live on a surface and how to utilize the assets. And then that's very important because you know, it's very expensive to carry fuel, to carry water and all the necessities that you need to survive as a human being and outer space. If you can generate that on the surface or on the planet you go to, and this is a perfect way to do it because it's very in your backyard, as I told you earlier. So for future mission, when you want to go to Mars, you're nine months out, you really wanna make sure you have the technologies and you're able to utilize those technologies robustly and in a sustainable way. >>Yeah, we were talking before you came on, came camera camping in your backyard is a good practice round. Before you go out into the, to the wilderness, this is kind of what's going on here, but there's also the discovery angle. I mean, I just see so much science going on there. So if you can get to the moon, get a base camp there, get set up, then things could come out of that. What are some of the things that you guys are talking about that you see as possible exploration upside? >>Yeah. Well, several things. One is power generation recently. We just released some contracts that from vision power, so long, sustainable power capability is very, very important. You know, the other technologies that you need utilize is regenerative, you know, air, water, things that are, you need for that, but then there's a science aspect of it, which is, you know, we're going to the south pole where we think there's a lot of water potentially, or, or available water that we can extract and utilize that to generate fuel. So liquid hydrogen liquid oxygen is one of the areas that are very interesting. And of course, lunar minerals are very exciting, very interesting to bring and, and, and be able to mine potentially in the future, depending on what is there. >>Well, a lot of cool stuff happening. What's your take on this show here, obviously NASA's reputation as innovators and deep technologists, you know, big moonshot missions, pun intended here. You got a lot of other explorations. What's this show bring together, share your perspective because I think the story here to me is you got walkout retail, like the Amazon technology, you got Watson dynamics, the dog, everyone loves that's walking on. Then you got supply chain, robotics, machine learning, and space. It all points to one thing, innovation around industrial. I think what, what, what's your, what's your, what's your take? >>You know, I think one of the things is, is, you know, normally we are innovating in a, in our aerospace industry. You know, I think there's so much to learn from innovation across all these areas you described and trying to pull some of that into the spacecraft. You know, when, when you're a human being sitting in spacecraft is more than just flying the spacecraft. You know, you have interaction with displays, you have a lot of technologies that you normally would want to interact with on the ground that you could apply in space to help you and make your tasks easier. And I think those are things that are really important as we look across, you know, the whole entire innovative infrastructure that I see here in this show, how can we extract some that and apply it in the space program? I think there is a very significant leveraging that you could do off of that. >>What are some of the look at what's going on in donors? What are some of the cool people who aren't following the day to day? Anything? >>Well, well, certainly, you know, the Artman's mission Artis campaign is one of the, the, the coolest things I could think of. That's why I came into, you know, I think wrapping around that where we are not only just going to a destination, but we're exploring, and we're trying to establish a very clear, long term presence that will allow us to engage. What I think is the next step, which is science, you know, and science and the, and the things that can, can come out of that in terms of scientific discoveries. And I think the cool, coolest thing would be, Hey, could we take the things that we are in the labs and the innovation relative to power generation, relative to energy development of energy technologies, robotics, to utilize, to help explore the surface. And of course the science that comes out of just naturally, when you go somewhere, you don't know what to expect. And I think that's what the exciting thing. And for NASA, we're putting a program, an infrastructure around that. I think that's really exciting. Of course, the other parts of NASA is science. Yeah. And so the partnering those two pieces together to accomplish a very important mission for everybody on planet earth is, is really important. >>And also it's a curiosity. People are being curious about what's going on now in space, cuz the costs are down and you got universities here and you got the, of robotics and industrial. This is gonna provide a, a new ground for education, younger, younger generation coming up. What would you share to teachers and potential students, people who wanna learn what's different about now than the old generation and what's the same, what what's the same and what's new. What's how does someone get their arms around this, their mind around it? Where can they jump in? This is gonna open up the aperture for, for, for talent. I mean with all the technology, it's not one dimensional. >>Yeah. I think what is still true is core sciences, math, you know, engineering, the hard science, chemistry, biology. I mean, I think those are really also very important, but what we're we're getting today is the amount of collaboration we're able to do against organically. And I think the innovation that's driven by a lot of this collaboration where you have these tools and your ability to engage and then you're able to, to get, I would say the best out of people in lots of different areas. And that's what I think one of the things we're learning at NASA is, you know, we have a broad spectrum of people that come to work for us and we're pulling that. And now we're coming to these kinds of things where we're kind getting even more innovation ideas and partnerships so that we are not just off on our own thinking about the problem we're branching out and allowing a lot of other people to help us solve the problems that >>We need. You know, I've noticed with space force too. I had the same kind of conversations around those with those guys as well. Collaboration and public private partnerships are huge. You've seen a lot more kind of cross pollination of funding, col technology software. I mean, how do you do break, fix and space at software, right? So you gotta have, I mean, it's gotta work. So you got security challenges. Yeah. This is a new frontier. It is the cybersecurity, the usability, the operationalizing for humans, not just, you know, put atypical, you know, scientists and, and, and astronauts who are, you know, in peak shape, we're talking about humans. Yeah. What's the big problem to solve? Is it security? Is it, what, what would you say the big challenges >>Are? Yeah. You know, I think information and access to information and how we interact with information is probably our biggest challenge because we have very limited space in terms of not only mass, but just volume. Yeah. You know, you want to reserve the space for the people and they, they need to, you know, you want maximize your space that you're having in spacecraft. And so I think having access to information, being able to, to utilize information and quickly access systems so you can solve problems cuz you don't know when you're in deep space, you're several months out to Mars, what problems you might encounter and what kind of systems and access to information you need to help you solve the problems. You know, both, both, both from a just unplanned kind of contingencies or even planned contingencies where you wanna make sure you have that information to do it. So information is gonna be very vital as we go out into deep >>Space and the infrastructure's changed. How has the infrastructure changed in terms of support services? I mean see, in the United States, just the growth of a aerospace you mentioned earlier is, is just phenomenal. You've got smaller, faster, cheaper equipment density, it solved the technology. Where's there gonna be the, the big game changing move movement. Where do you see it go? Is it AIST three? It kind of kicks in AIST ones, obviously the first one unmanned one. But where do in your mind, do you see key milestones that are gonna be super important to >>Watch? I think, I think, I think, you know, we've already, you know, pushed the boundaries of what we, we are, you know, in terms of applying our aerospace technologies for AIST one and certainly two, we've got those in, in work already. And so we've got that those vehicles already in work and built yeah. One already at the, at the Kennedy space center ready for launch, but starting with three because you have a lot more interaction, you gotta take the crew down with a Lander, a human landing system. You gotta build rovers. You've gotta build a, a capability which they could explore. So starting with three and then four we're building the gateway gateways orbiting platform around the moon. So for all future missions after Rist three, we're gonna take Aion to the gateway. The crew gets into the orbiting platform. They get on a human landing system and they go down. >>So all that interaction, all that infrastructure and all the support equipment you need, not only in the orbit of the moon, but also down the ground is gonna drive a lot of innovation. You're gonna have to realize, oh, Hey, I needed this. Now I need to figure out how to get something there. You know? And, and how much of the robotics and how much AI you need will be very interesting because you'll need these assistance to help you do your daily routine or lessen your daily routine. So you can focus on the science and you can focus on doing the advancing those technologies that you're gonna >>Need. And you gotta have the infrastructure. It's like a road. Yeah. You know, you wanna go pop down to the moon, you just pop down, it's already built. It's ready for you. Yep. Come back up. So just ease of use from a deployment standpoint is, >>And, and the infrastructure, the things that you're gonna need, you know, what is a have gonna look like? What are you gonna need in a habitat? You know, are, are you gonna be able to have the power that you're gonna have? How many station power stations are you gonna need? Right. So all these things are gonna be really, things are gonna be driven by what you need to do the mission. And that drives, I think a lot of innovation, you know, it's very much like the end goal. What are you trying to solve? And then you go, okay, here's what I need to solve to build things, to solve that >>Problem. There's so many things involved in the mission. I can imagine. Safety's huge. Number one, gotta be up safe. Yep. Space is dangerous game. Yes. Yeah. It's not pleasant there. Not for the faint of heart. As you say, >>It's not for the faint >>Heart. That's correct. What's the big safety concerns obviously besides blowing up and oxygen and water and the basic needs. >>I think, I think, you know, I think you, you said it very well, you know, it is not for the faint of heart. We try to minimize risk. You know, asset is one of the big, you're sitting under 8.8 million pounds of thrust on the launch vehicle. So it is going very fast and you're flying and you, and, and it's it's light cuz we got solid rocket motors too as well. Once they're lit. They're lit. Yeah. So we have a escape system on Orion that allows a crew to be safe. And of course we build in redundancy. That's the other thing I think that will drive innovation. You know, you build redundancy in the system, but you also think about the kind of issues that you would run into potentially from a safety perspective, you know, how you gonna get outta situation if you get hit by a meteor, right? Right. You, you, you are going through the band, Ellen belt, you have radiation. So you know, some of these things that are harsh on your vehicle and on, on the human side of this shop too. And so when you have to do these things, you have to think about what are you gonna protect for and how do you go protect for that? And we have to find innovations for >>That. Yeah. And it's also gonna be a really exciting air for engineering work. And you mentioned the data, data's huge simulations, running scenarios. This is where the AI comes in. And that seems to me where the dots connect from me when you start thinking about how to have, how to run those simulations, to identify what's possible. >>I think that's a great point, you know, because we have all this computing capability and because we can run simulations and because we can collect data, we have terabytes of data, but it's very challenging for humans to analyze at that level. So AI is one of the things we're looking at, which is trying to systematically have a process by which data is called through so that the engineering mind is only looking at the things and focus on things that are problematic. So we repeat tests, every flight, you don't have to look at all the terabytes of data of each test. You have a computer AI do that. And you allow yourself to look at just the pieces that don't look right, have anomalies in the data. Then you're going to do that digging, right. That's where the power of those kinds of technologies can really help us because we have that capability to do a lot of computing. >>And I think that's why this show to me is important because it, it, it shows for the first time, at least from my coverage of the industry where technology's not the bottleneck anymore, it's human mind. And we wanna live in a peaceful world with climate. We wanna have the earth around for a while. So climate change was a huge topic yesterday and how the force for good, what could come outta the moon shots is to, is to help for earth. >>Yeah. >>Yeah. Better understanding there all good. What's your take on the show. If you had to summarize this show, re Mars from the NASA perspective. So you, the essence space, what's the what's going on here? What's the big, big story. >>Yeah. For, for me, I think it's eyeopening in terms of how much innovation is happening across a spectrum of areas. And I look at various things like bossy, scientific robots that the dog that's walking around. I mean to think, you know, people are applying it in different ways and then those applications in a lot of ways are very similar to what we need for exploration going forward. And how do you apply some of these technologies to the space program and how do we leverage that? How do we leverage that innovation and how we take the innovations already happening organically for other reasons and how would those help us solve those problems that we're gonna encounter going forward as we try to live on another planet? >>Well, congratulations on a great assignment. You got a great job. I do super fun. I love being an observer and I love space. Love how at the innovations there. And plus space space is cool. I mean, how many millions of live views do you see? Everyone's stopping work to watch SpaceX land and NASA do their work. It's just, it's bringing back the tech vibe. You know what I'm saying? It's just, it's just, things are going you a good tailwind. Yeah. >>Congratulations. Thank you very much. >>Appreciate it on the, okay. This cube coverage. I'm John fur. You're here for the cube here. Live in Las Vegas back at reinvent reinforce re Mars, the reser coverage here at re Mars. We'll be back with more coverage after this short break.