Behind The Tech: Carv 2 Podcast

If you're a skier, you've most likely heard of Carv, and if not, in today's episode of the Big Picture Skiing Podcast, you're going to find out more. What used to be an insole inside your ski boot is now this, almost the size of a car key, and it's much smaller. And there's some great innovations that Carv have done to make this device tell you all about your skiing. Now, in this episode, you're going to hear from the lead data scientist, Charlie. He's going to give you some great insights into how they achieved measuring skiing on all types of terrain, which is a big breakthrough. It was previously really only accurate if you skied on the groomers, but now it measures your bump skiing very accurately, powder skiing, and it can detect it. It knows all what's going on without you even having to tell it. So I wanted to chat with the team, hear some more details about how they got there, what some of the problems they had to overcome, and what's coming in the future. Now, with this change from a pressure-sensing insole to a device that sits on the outside of your boot like this, there's a lot of skeptics that say, how can you get accurate, uh, data measurement of what's going on? And I'm there too, because the first time I tried Carv in New Zealand many years ago, I was blown away by the fact there was a pressure sensor under my foot telling if I was pressing on the, the inside or the outside of my foot, if I was forward or back. It gave me insight into wanting to change the ramp angle inside my boot to balance better. So I'm very curious how Carv have managed to stick with still measuring things really accurately but without the pressure sensor. And you're going to find way more about that inside this episode today. So if you're already one of the thousands of dedicated Carv users, this episode is going to give you insight into how they've managed to make some major upgrades and changes to this coming season's offering. And if you're new to Carv, you're going to find a lot more about their philosophy on skiing and how this device could help you to become a better skier. And as you'll hear Alex say, better skiers have more fun on the whole entire mountain. All right, without further ado, let's get into this chat with Carv on today's Big Picture Skiing podcast. Coming into this new season, what did you really want to improve?

I mean, it's good to go back to why Carv even exists and sort of go from there. So Carv's been around a while now, I think 7 years on the market. Its original— the original ethos of why Carv exists is, is definitely still the governing thing in our whole business, which is most of us get lessons when we start learning, then we basically stop getting any input. Now, some people, the enlightened people in the world, will follow you, Tom, and will also keep getting inputs from other instructors, and they're seeking out all these amazing sources to make their skiing better. But most people don't, and most people have moments of learning where they would sort of go and focus on something, and then 95%, 99% of the time they have moments of skiing where they're just skiing.. And I think what's interesting is people mentally have, I'm learning or I'm skiing. And I think what the best instructors do, in fact, most instructors will do this, is they put the two together. And so the best days you could have on snow are when you go and ski with an instructor, because they'll take you to some cool places. They'll give you some teaching along the way and you'll get better and have a more fun experience on snow. Now, unfortunately, most of us can't ski with instructors most of the time. And generally speaking, people sort of forget that there's still things to improve, and they also forget the idea that better skiers have more fun, right? I think that's why everyone subscribes to Big Picture and why people are looking for this input. So KAR was originally built to solve that problem, which is how do I get inputs into my skiing all the time so I can increase that slope of learning so it's not like flat periods of plateau, and then maybe I'll get a new tip and I'll suddenly have a little spurt of improvement. How can we make that gradient steeper and more constant for everybody? So that's the ethos of Carv. Now, Carv One, which is our original product, did that with a pressure sensor, uh, which went in, into the boot under the liner, and it's an insole, as you guys know, uh, and it had pressure and motion sensing. Um, but it really, it was sort of getting in the way of skiing for some people. So it had some issues, like actually installing something in your boot was an issue. Um, it also had a few issues technically around how it was able to capture data, which we optimized around, but basically we felt there was a way to do that better. And, and it was really largely optimized for groomers. And so this year, the two main things we wanted to do was to, to take the ethos of Carv, which is to put learning into everyday skiing, and to do that everywhere. And, and actually, when looking at that problem, we, we had to be fairly brave and go back and totally rebuild our whole system to really achieve it. So it's been an enormous year. I mean, everyone in the team has done an incredible job to get to where we are. I think it's safe to say we're also pretty tired at this point, and the season's only just starting. But solving for every boot and reducing their complexity and the faff, basically, and solving it everywhere. So we've truly got a tiny device that is pretty much invisible, which means you can learn wherever you go skiing this year. And that was, that was our goal.

So, okay, perfect. So we've got this goal of everywhere. So was there difficulty, I guess, you were trying to overcome with, you know, when it wasn't a groomed day? Because if Carv users are using, uh, listening, they'll recognize that some of the best scores always were when it was the morning and it was perfect snow. Yeah, big goal is, was to change that. So Yeah. Did you— is that why this sort of mashup part was part of, part of it?

Yeah. So, so one of the interesting challenges at Carv is we always have to build based on accurate data and build a system that responds accurately to you. Now, if we want to make Carv's coaching work in other terrain, we have to have a really good system that quantifies and scores skiing of every level. Everywhere. And actually to do that at scale required this actually kind of fun and interesting system where you can basically get scored by instructors against other skiers. And I think what's always amazing about Carv is to make these changes, we can't just guess and sort of write in some tips and just hope it works. We have to build on a basis of data and what's actually happening. And then we can train our models based on real things that they're looking for, you know. So we're not using our own assessment of what we think good skiing should be in bumps or in powder. We basically get instructors to say this person was better in powder than this person, and our system can learn which skier to model on. And so I think for Carv, every time we do one of these big changes in the product, what you experience as a skier is, oh, it's cool, it just recognized powder and it coached me in it. But the work to do that is very, very challenging in Carv. Yeah, terrain, which I'm sure Charlie can talk about, and then know what to prioritize and what to coach. And those are two very difficult problems that we've had to solve, and the mechanism of the Ski Mash system that Charlie spoke about is a really great tool to do.

What is Ski Mashup, and why did you do it to advance Carv this year?

Yeah, so Ski Mashup is a platform where we basically show two videos of 2 different skiers, and we ask our ambassadors to decide who's the better skier, but also to tag relevant, uh, conditions and, uh, ability labels in the turn type. Uh, and it's basically a way for us to attach labels to Carv data, which is the entire foundation of how we build Carv going forwards. So Yeah, they watch the videos, they tag them, and we've done that for 11,500 videos of, of Carv users. And the, the output of that is then this really clean dataset that we can use to assess correlations with ability, but then also to, uh, evaluate how well we can pick up different conditions like moguls and powder, uh, and various, uh, off-piste conditions.

Yeah, and where did this idea come from? I remember you, you sort of messaged me and told me to look up something to do with chess.

Is that right? Yeah, so historically with a smaller data set, we had just labeled by ability level. So we asked, we gave definitions for beginners, intermediates, advanced, world-class athletes, etc., and then we got our ambassadors to tag those specific ability levels, but that requires every single ambassador to have the exact same definition of each ability level. And we actually go into 9 different buckets. So we found that there was quite a lot of, um, disagreement— not large disagreements, but, you know, an ability label here and there. So we were trying to find a, a clean way to do this, and this is where the mashup idea came from. And in chess, with online chess, you basically have this thing called an Elo ranking where you have— you start off with a baseline score and then you play people, and dependent on how high their rating is and if you win or lose, your rating then increases, uh, dependent on that. So we thought, let's do something similar for skiing where we can battle two skiers against each other and then we can adjust their, their ranking based off of you know, who's winning in the eyes of, of the instructors that we get to watch the videos. And yeah, the idea here is that we'll get a cleaner way of understanding the ranking of skiers in our dataset.

And so AI being, you know, all the buzz at the moment, everything's got AI in it, sort of the timing of Carv and even this year makes a lot of these things possible. Am I, am I correct? Because you're feeding this data in to get this machine learning patterns and recognizing things, and I'm going to guess throughout this season it's going to continue to learn as more skiers give it input. Is that right?

Yeah, yeah, exactly. So this, this idea of moving to all-mountain conditions has actually been multiple years in the making, and it's only now at this moment when we've collected enough data and the advances in AI have come far enough that we've actually been able to execute this well enough. So there's actually been two phases to getting this over the line. And as Alex said, it's been a lot of hard work. But to start with, we started collecting these videos 3 or 4 years ago, and we've been ramping that up year on year. And then this year, we've been able to get super high-quality labels from our ambassadors with SkiMash at scale. But we've also been collecting from the entire user base this, this whole time. We've got over half a billion turns now, and over the last two seasons, we've been asking our, uh, carvers to annotate their own segments of skiing with the type of snow surface that they were skiing on. And we actually use both of these inputs into our AI model to detect what type of skiing, uh, you're doing and, and what surface you're, you're skiing on. So We, we basically have these, all these different metrics that are, um, characterizing the movement of the ski in all these different conditions. And then we feed, uh, these examples with the labels into the model. The model then starts to learn, uh, and then, uh, yeah, we can then output what, what terrain you were skiing in. And yeah, exactly. Over the, over this, uh, year, over this season, as we get more and more data, this is going to get more and more accurate. So yeah, we're really excited to continue to improve this and get it more and more accurate over time.

Yeah, and on the UX side of the product, I'm thinking about the listeners here saying, oh, my head is going to explode with how complicated this is getting, right? But one of the big downfalls of the previous version of Carvid has this very simple model. You take your edge angle and you multiply it by a factor and you take your early edging or you take your parallel skis and you multiply them by a factor and you add them up. Very simple. There's just a weight to each one. But what it meant was it only worked for carving skiing on moderate slope in groomed terrain because as soon as you went to something else and you skied in powder, now all of a sudden the weight for your edge angle was really high and it shouldn't be for powder. So that's where it broke. And what Charlie's saying is now the system is a lot smarter depending on the, the snow surface that you're skiing in, the turn type that you're doing, the pitch of the terrain. It adjusts all those weights. And the beautiful thing is now it scores mogul skiing or skiing in lumpy, bumpy snow or skiing and steep pitch more appropriately. But going back to my point, well, doesn't this make people's heads explode with like, well, what, you know, what means, what means what and what should I do? And so what we're doing in the product is each of our metrics has what are called target zones, and then we just adjust the target zones based on those factors. So you can see based on the conditions that you're skiing in, what should you be striving for?, and we'll be providing illustrative examples of different people at different ability levels in different conditions and what kind of targets you should be aiming for. So then it takes what, what could otherwise become so complex, it requires machine learning and, and adjustment and training and all this stuff that may sound complex. We do, we reduce it into something really simple. These are the metrics that matter most in these kind of conditions. And these are the kind of ranges you should shoot for. And in fact, we show you what's one level above you, so it's not something out of your reach, it's just one little step ahead. How can you inch your way forward? And that's how we try to make this all accessible in the product, right?

Yeah, good jump in there, John, to help, uh, give some context. And actually, on, on that, for people listening where they've maybe heard of the, heard of this CARV product, I'm just trying to think of, of a person who they're into their skiing, maybe what Alex mentioned before, that, oh, you know, yeah, I usually just ski and sometimes I take a lesson. But this idea of combining the two, being able to sort of improve all the time and that bring on more fun. This new ver— like the new updated Carv 2, a new user using it for the first time, like, who wants to like run them through what it'd be like? You you put it on, what happens?

Yeah, I'm, I'm probably the best person to do that because I'm more the Carv noob here. I joined the team back in April and, uh, I am not as strong a skier as Alex and Charlie and the rest of the team members. Uh, I'm learning quickly. Uh, but I actually was a Carv customer for 2 years before I joined the team, and that was because I had snowboarded for 30 years and then started teaching my son to ski. And got hooked on it. And I said, well, I better learn fast because otherwise he's gonna be embarrassed to ski with me soon. So I got on Carv and, and loved it, got hooked on it, but then had all these ideas about, you know, what we can do. So that brings us to now, what's the experience going to be like if you've never used Carv, you hop on here, you, you take these sensors, put them on your boot, go in the app, We've got it down to one button press now to pair the sensors to your app. It used to be a whole bunch of different things and calibration and this and that. Now you hit a button, it says they're connected and you're ready to go. No extra calibration, just, just magic. And that one blows my mind. The team members, what they've been able to do with where you put it on your boot, but you just go ski and Carv says, hey, John, How's it going today? Go get 'em, tiger. And, and then once you start skiing, it learns some, it learns and starts to tell you, all right, every time you stop, here's a Ski IQ. And then you take a couple, you take a run, and by the time you're at the end, it tells you what focus metric to focus on and why. So it, it's giving you some information about what you're, what kind of terrain you're skiing. What you should focus on, and some tips on what to adjust and why. And then each time you stop, it will give you your SkiIQ, which is this overarching number of the, the quality of your skiing that's basically taking all of those instructors that have evaluated videos and building this massive brain for you that assimilates all that and gives you this feedback. And it'll tell you how you did on that particular focus metric. Whether you're trying to get more parallel skis, trying to get your edge angles up, trying to, um, maintain your balance more effectively. And then it gets into that cycle. Each time you stop, gives you some feedback. Each time you get on the lift, gives you some tips. And the first time I tried it, I thought it was magical. And where we are now is head and shoulders above where we were the past couple seasons.

Okay, so I mean, very much like when I go and teach people, they come for a lesson, I have to watch them first. And the SkiIQ is a bit like in my head, I watched them come down and I've kind of ranked them against all the other hundreds, thousands of people I've skied and watched and kind of going, okay, well, they fit here and they're missing these things. Today I'm going to suggest we, uh, we improve, you know, turn shape, something like that, which Carv can also do. Yep, now, uh, now as well. So yeah, so that person trying it out, it's looking at everything and then it's going to start like focusing on an area. Now I'm interested, have you changed where Carv focuses on in your skiing? Because I mean, there's so much to work on. I mean, I'm still working on trying to become a better skier. I think all of us here are. How do you— how's it been done to get what, you know, what it thinks, what Carv thinks you should work on.

I'll give both sides of this. One, I think we've made a ton of advances. On the other side, we have a lot to do. So I'll tell you what, where we've made the advances and then what's, what's next on our plates. So a big limitation that we had before is we gave metrics like turn shape or parallel skis or edge angle, and that was great. It took you from having No measurement of your skiing to having these, these, uh, quantitative findings that you could try to drive up and drive down. But then the immediate question that people ask is, well, parallel skis, are my skis in snowplow? Are my tips diverging? Is it my right turn? Is it my left turn? Is it the beginning of the turn, the middle of the turn, the end of the turn? Right? So it, the, the data then read more curiosity and more need for more granularity so you could give great coaching. So that's a big transformation that we've done this year. Now, instead of just giving you a turn shape score, we also draw your turn, your actual turn shape segment to segment. You see it stretch out or it makes sharp angles or nice curves. And now you can see that throughout the phases of the turn. So the turn shape measurement actually becomes something more actionable and coachable. Now we also paint on that every millisecond throughout the turn where your skis are, are, uh, diverging your tips versus your tips coming together and snowplowing. Um, and I'm not talking about just like dramatic snowplow or dramatic diverging. I'm talking about small changes throughout there. So you can see, and we can move from saying something like, keep your skis more parallel to, oh, when you're carving in steep terrain, your tips are diverging at the end of your right turns, and this is what you can do for that. So this is the real transformation that we've done this season, is giving a lot more granularity. Where we still have a lot to do is making those tips more diverse, smarter, doing more skill-based coaching. A lot of this is like one metric at a time. But putting the other layer of, I want to get better at moguls, or I want to work on carving in steep terrain, I want to— getting more of the essence of what the user wants to achieve and then tuning that all to that, there's work to do there. And we're excited to hear from everyone this season, collaborate with them, and throughout the season, start closing that gap.

Yeah, I must say that's a big advantage I see from my side is the way you collaborate with users, instructors, everybody that, that is involved in, in using this product. I mean, over this Australian Aussie season, that's the summer northern hemisphere, I got to be involved with the, the Carve mashup thing and, and also John yourself as you're sort of showing us some of the new user experience when we, when we look at the app now, the software inside. And it's been, uh, yeah, really, like, I, I standing here watching, I, I think it's very admirable that you are so involved with the community and making sure you're, you're hearing everything they're saying. There were a lot of requests from people, users. We want this, we want that. And, you know, some people are shooting for the moon. So what can you say? What do you think? I, I would say the ToneShape one and being able to pick out that if someone is, is in snowplow or they're diverging their tips at the start of the turn or the end— being specific, that's massive. That would have been a big, big one. What would you say is another area you've really improved based on what people were asking for last year?

Yeah, I think the biggest one is one that Charlie got into with snow surfaces. People want to just be able to ski across the mountain and not feel deflated, right? We used to hop off to some moguls on the side of the trail and you'd get a a really low score, but you were skiing them well, or maybe you weren't skiing them well, but we were comparing apples to oranges and it just, it made it so people would turn off Carv for certain parts of their skiing and turn it on for other parts. So those advances that, that Charlie and the team have worked on have been a huge unlock. And what we also did was we changed the whole ski recording experience.. It used to be a whole mess of modes that you had to choose between, and it was quite complex. And it actually, based on what you chose, it splintered the experience. It splintered the kind of data that you could get. So if you were in free ski mode or you were in active coaching mode, or you were in a particular monitor mode, you would get different data in the end. And so it became very complex and splintered and that's led to this behavior of, oh, I'll turn Carv off sometimes. And now we collect all the data all the time, and you just choose what kind of audio feedback you want. Do I want, do I want it more verbose and, and giving me dings and dongs for every turn that I make? Or do I want it to just talk to me on the lift or only at the end of my segments? So now people can get a SkiIQ that's really tuned based on they're doing short turns or longer turns, whether they're in moguls or on groomers, whether in steep terrain or moderate pitch, and they can get the audio that they want without all this complexity. And that, that's a really transformative piece that, you know, Charlie and the data science team were able to unlock by doing all this magic of finding that stuff out without requiring a lot of work out of, out of the user.

Hey, I wanted to talk about the change in hardware. And if you're watching, this is the, the Carv unit now is way smaller. Someone compared it to a car key. It's literally like a car key, and you've got one on each boot. There's no insole, so you don't have to change the fit of your boot, which I know was a big problem for a lot of people, even myself, in a tighter fitting boot. When this came out, I was skiing, I was testing it this season, Thredbo, and my son Archie was up going to do some really junior races And of course, me being the coaching dad, I'm like, come on, Archie, let's, you know, work on this. And, and he would listen for about half a second and just ski off, frustrate me to no end. Anyway, this new Carv sensor, I took it off my boots and I said, Archie, can I put it on you? And he's like, what is this thing? And it's like, oh, it's kind of like a game. Look, it'll measure everything that you're doing. Why don't you go do, do your turns and then we'll have a look on my phone. So he goes down and he makes some turns, and then we stop and we open the Carv app and have a look. And I show him, and there's a score there, so the Ski IQ. And he goes, is that good? Like, you know, 120 or something like that. I said, that's pretty good. I don't know, I've never seen a kid use Carv before, so I'm not sure. And we clicked into some of the metrics and looked at your edging. And I said, so, so see here, it's, it's saying that your, your, your inside edge angle and your outside edge angle are kind of not moving at the same time. Do you want to try and beat that? And he goes, yeah, yeah. So I just gave him to just try and keep them moving together. So he goes off with way more focus this time and tries to beat his old score because we're all competitive. And, and in my mind, I was just like, this is crazy that one, this device that was just on my boots, just put it on his boots and he's now straight away using it. And then two, there was buy-in because there was some gamification and competition against himself with, with his skiing. So anyway, that's, that's my first experience of how, like, straight away I was like, this is such a good move. There's people that will have, you know, seen Carv in the past and seen the pressure sensor and gone— and I was one of those people thinking the pressure sensor is so important, gotta have it there because you can tell what, what's going on under the feet. Why the move? Maybe why the move away from the pressure sensor? And then how have you got the new device, this thing that goes on the side of your boot, to do almost as good a job as the pressure sensor?

Yeah, I, I can get started, but I, I've been chatting a lot and, and Charlie's definitely the, the guru here, so he'll follow up with some more details. But the motion metrics have always been our strongest metrics. Um, they correlate better with ability and they also are more consistent across users.. But the pressure metrics in the past were also a really important piece of that whole puzzle. But we had this huge unlock this year with something called sensor fusion, which is how we combine the accelerometer data and the gyroscope data to create a motion model of your boots. And, and I won't get into that in detail. Charlie, Charlie knows more about that. But what it did is unlock this much more accurate model of the movement of each of the boots.. So suddenly that gap between the motion metrics being a bit more consistent and a bit more correlated with high ability level with the pressure metrics that it, it jumped and the gap got quite wide.

Can you help the, help the listener if someone's not familiar, like give an example of a motion metric versus a pressure metric?

Yeah. So, a motion metric would be something like the rotary of your skis.. And whether you're in a snowplow or you're in a diverging tip situation, so we can measure the roll, pitch, and yaw of your boots, which is side to side, front to back, every direction of your boots moving around. So the, the snowplowing or diverging is one example. Your edge angles as you go through the turn and you start with your boots straight up and down to tipping over and tipping back. And how smooth you do that and how it, how similar it is between the two boots. All of that is just motion. And then pressure would be how your feet interact with the bottom of the boot. And are you pressing with the, the balls of your feet or your heels? And, and how is that balanced? The thing about the pressure metrics is everybody's boots are a bit different. And when you install those pressure sensors in there, even though the sensors themselves are accurate, the way they're positioned and the way you interact with the boot. If you use the cuff of your boot a bit to apply forces on it, it will have your foot interact with those pressure sensors differently. So that's what creates some of the inconsistency. While motion is motion, you, you put this on your boot and your boot moves, it's pretty consistent for everyone. And with this new unlock, it became even more accurate so that that gap in consistency became wider.. And what we found is we were able to outperform last year's SkiIQ and metric accuracy with just motion compared to last year's model that used motion and pressure. The motion metrics just got so good that they could do that to the point that to make Carv 1 as good as Carv 2, because we're going to continue to support the, the existing hardware for everyone. And we're going to continue to give them all the latest features. But to make it as good, we had to just stop using the pressure metrics. They were essentially, you know, pulling things down while the, while the motion metrics were getting better and better.

Yeah, I think I remember you mentioning it was kind of a frustrating, like, the pressure sensor one, because people would, they would try and change the, you know, hey, you're not forward at the start of the turn. So people would go, right, I'm going to get more forward. And they'd try and they'd be really far forward, but the pressure sensors, because of the way that the leg interacts with also the cuff of the boot and everything like that, they, they didn't get the, um, they didn't get the same feedback. Like, they were doing the right thing, so it was kind of confusing, whereas now it's very different.

Yeah. And in the past, don't get me wrong, the pressure played a huge value in the past. Each year that you go back in time, pressure had more and more of a role. Because back then the motion model wasn't as good, right? And it's just that that motion model has gotten better and better and better that has unlocked this. But I'll hand it over to Charlie because he can get into some of the other huge unlocks about some of the individual metrics, how motion has made them better.

In particular, one of the data sources we've looked at and explored is the acceleration of the, of the ski. And, um, yeah, basically what we've been able to do through analyzing all the raw data from our elite skiers like yourself, Tom, and Ted Ligety, Marcus Caston, etc., we, we spotted this very clear pattern in the acceleration data where the skis just before transition, so at the end of the previous turn, they would decelerate and then during transition, uh, they would then catch, uh, they would then accelerate afterwards. So you got this moment of, of deceleration, weightlessness, and then acceleration at the start of the next turn. And, uh, by isolating a certain axis along the, the length of the ski, we've been able to, um, yeah, really quantify how your ski is then accelerating at the start of the turn to basically catch back up with an early forward movement. So This insight has basically allowed us to understand and measure your, your shift in balance without relying on the pressure sensors, which were, were flawed, um, in the way that you mentioned where if you really hammer the boot cuff, that would lift up the, the back of the boot into the sensors causing Carv to think that you are actually backwards and you're forwards. And then people were trying to get so far forwards that their tails are washing out and it's, you know, really confusing for, for, for people who have that bad experience. You know, other people had a great boot fit and, and weren't overusing the, the shins and it was working very well, but Um, with this new approach, acceleration data is accurate and it works for everyone. And for this particular metric of early forward movement, you know, it really makes sense from a biomechanics point of view. When the skier becomes weightless in transition and moves diagonally over, over their skis, so you've got the combination of forward movement and topple, the, the skis then accelerate back round to catch the skier. So you know, the, the pattern that we spotted aligned with our expectation for, for what should be happening. And, uh, yeah, this, this enabled us to basically understand that we could measure early forward movement from the acceleration data itself.

Yeah, what we're hearing from all the people that we've been working with testing this prior to launch is that the simple thing is now they can adjust how much they move their center of mass forward at the beginning of the turn versus not, and they get a responsive measurement. Um, the— with the old measurement, sometimes it would respond, sometimes it wouldn't. It made it very hard for teaching. But now you can adjust this balance at the beginning of the turn and how much you lean forward and how much you lean back, get a different result out of this, and then find that optimum point in between. And that That's the kind of thing that we're striving for with each of these metrics, is that ability to be accurate and correlate with ability level, but also to be responsive so you can try things. And a big unlock with these two is some that previously you couldn't have in the monitor mode, which is when you can hear the value with each turn that you make.

Now we've unlocked the ability to hear those values with each turn that you make. So for example, if John, you saw your early forward movement wasn't where you want it to be and your target was, you know, like further up, you could switch on this monitor mode and actively try and do things to change that. And after you do one turn in your earbuds or whatever, it'll go— we'll make a noise.

Will it on that one? Do you know? On that one, it will give you the actual number each turn, but you can also do, uh, another audio setting, which is Active Coach, which will set a target with you, and then you'll get a, a, a bing or a buzz with each turn on trying to hit that number. And it, it starts to mentally ingrain this, and it's like this unconscious thing that you're skiing and hearing and skiing and, and hearing it, and you just subtly learn how to change your body movements and adjust to be able to optimize it.

It's, it's Yeah, it's, uh, it becomes quite cool. Back to, you know, my story about Archie, my, you know, nearly 7-year-old. That mode would work really well. Whenever you hear it's going ding ding, you're doing— keep doing that. And when it's going, or the buzz, it's very simple. Yeah, because there's a lot going on in skiing in, in the moment. So, so that's cool. Alex, what's your take on you know, some of these changes and the move to the, the small car key sized sensor now on the side of the boot?

Honestly, it's, it's an amazing change for Carv because our whole thing is around something you can just clip on and go and then get that feedback anywhere. Now, the more we put in the way of skiers— installation or boot fit or, you know, complicated app— the less that vision is able to be achieved. So You know, when you said the car key thing, I'm a dad now, so I'm allowed to make really naff jokes. But essentially, a car key unlocks your car, but car unlocks your skiing. And the more you have it with you, the more it can do that. So I think Carv 2, the big thing, honestly, is it's just simplicity. It's awesome we can make it more accurate. Our whole business is based on being accurate. I think a few companies have tried at this concept. Most of them failed because they're just not able to be accurate. Uh, and I think Carve, we're incredibly lucky to have Charlie and his team who do amazing things. But with Carve 2, it's sort of the challenge. Obviously we thought about doing this for a while. The challenge was how do we make this thing, but not sacrifice all of that amazing accuracy that we've been building up over 6 years. Um, and I think John explained it really well. It's sort of difficult for people to understand because pressure is very conceptually simple. I understand pressure in skiing like balance. That's really important, right? I think carve too, it's harder to understand because no one quite knows about how these measurement things work. And, you know, I can explain a bit in a second. But essentially, if you're— all of the things you do with your body, even your pressure, you're essentially reacting to and managing the forces that go through the ski. All those forces create motion and acceleration in your skis. So everything we do higher up, that's all trying to affect what's happening in your ski. Now, Carv 2 is just a more precise way of measuring that end output, which is great because it means we can actually see very, very specific, small, detailed things like Charlie mentioned with balance. Previously, we'd look at balance using the distribution of pressure on your foot. That obviously has some issues., we actually had to adapt our metrics to sort of manage those issues. But with motion, you can see, like, in a great, in a world of great balance for someone, we see this, like, beautiful pattern of acceleration that emerges, which we can see every time, no matter what boots or what skis you're, you're using. So I think it, I mean, what do I think? Honestly, it's a, it's a really amazing upgrade for our whole system because we can simplify it and make it more accurate. And I think for us, that's, that's always what we're gunning for.

Like going back to the tight boot fit thing, it was a hindrance to me. I would often not put it in because it was a warmer day and my feet would hurt with the insole. This season wasn't even— it's just, it's just on the side of my boots and the batteries last forever. I have to say, I was down in the snow and over a whole week, and I think at the end of it I had to charge, charge the, um, the sensors. So Yeah, pretty incredible, incredible feat there. Hey Charlie, you're deep in the, the data science, you know, you're seeing, you know, not as much— it must be kind of weird, all these skiers are feeding you these kind of numbers and that you put into graphs. Can you tell me— we had a very brief discussion, I asked you after doing some moguls, I said, what patterns do you see in mogul skiing that are different to all the graphs and patterns you see in, in carve skiing?

Yeah, so mogul skiing is, uh, is pretty different. Obviously, we, we see, you know, quite a distinct pattern, uh, for all levels of skier, which is why we're able to detect it with our, with our new classification, uh, model. Typically, you know, the pitch of the ski is moving around a lot more, um, and the acceleration data is, is actually really interesting. It's, it's, it's interesting in carving skiing, but when you're then adapting to the the undulations of snow as well. And for elite skiers, it becomes, yeah, incredibly interesting. So what we see is we see this early forward movement, like, like we discussed already, that, that metric is, is very clear in, uh, in mogul skiing. Uh, we also see large g-forces. So especially, you know, when you can imagine an elite skier doing like a zipline of moguls, those, those impacts of, of each bump, you can really see them going up to like 3 or 4 Gs. Um, but what we see always for, uh, advanced skiers, or elite skiers rather, is, um, that they completely release their acceleration data by the transition. So after hitting the mogul, there's that moment of weightlessness after you've absorbed it and you've moved back over to, to hit the next one. Uh, and, and we can see that in, in the acceleration data, uh, as well. But yeah, typically we see some, some early edging still, but the edge angles are then not as high. And that links back to what John was talking about with these terrain adaptive targets that we have, because, you know, you don't want 70 degrees of edge angle in, in moguls. So we're now able to see that actually elite skiers, they're, they're only getting to 30, 40 degrees, and we can then, um, you know, communicate that that's the right thing to do. But, but yeah, in general, it's fascinating to see such clean rhythmic patterns in, in such extreme environments from these elite skiers.

Like, if you contrast a not-so-good mogul skier's graph in the moguls to an elite skier, what are they doing in that moment where you see that, that accelerometer— is that the right word? Yeah, yep, yep.

Show that, show that, that pattern. So they are not moving as predictably or as rhythmically, particularly in acceleration data, but, but also in the way the ski is rotating. So typically you'll see a lot of rotation all in one movement and then periods of a lack of rotation. And when you think about what that is in real life, that's someone traversing over a few bumps and then deciding to turn and then doing the same, whereas an elite skier is able to, you know, pick their paths, uh, tactically, and, and they have a very consistent turn shape despite the, the difficult terrain that they're skiing in.

And, uh, yeah, we can now see that with the, the new visualization feature of actually showing you your turn shape. You mentioned on a, another call that I was privy to, there's some pretty high scores still even though it's in the moguls.

What did you say was a SkiIQ of? Yeah, so SkiIQ is, uh, ranges from, from 60 to 170, just over 170. And previously, mogul skiing, even, you know, elite mogul skiing, would be 130, maybe, maybe one high 130s. And, and for this year, with the new adaptive SkiIQ that takes into account the different inputs of how steep the run is, what the snow surface is, we now get SkiIQs of into the 160s for mogul skiing, which when I I saw that after training the model, I was like, oh wow, what have we done? This is incredible. I'm a passionate freeride skier. I'm not that good in moguls, and it's something that I really want to improve at. And knowing that I can aim to try and get into the 140s, 150s, and know that that's actually reflective of good technique, I can't wait to get out there this season and And yeah, I only heard that this morning, and that was, that was the coolest thing that I'd heard.

Like, knowing, wow, it's really recognizing that you can push up there. Because I love mogul skiing, and I think it just speaks to— at a day, especially in Australia, the conditions change a lot, and you can't just spend a whole day working on carving. It's just not possible, and it's not that fun. But you can go when the snow's good carving into some short turns, do some mogul skiing, vary it up. And then now the fact that Carv registers you're doing these different things and it actually gives you a more apples-to-apples score for that is, uh, is very exciting. I kind of, uh, yeah, I can't wait to see, yeah, where, where, where some scores go and what people do with, you know, coaching, uh, of within that, that mogul skiing area.

At the end of the day, I mean, Carv is there to make you a better skier, and that's because better skiers have more fun. But we have— we had to look at like, what is a better skier? A better skier isn't someone who can just rip it on a green run on a groomer and then fumbles around in the moguls and gets stuck in powder. We would all look at that as humans and go, oh, that's, uh, that's not a better skier. And better skier is about versatility. We speak with so many of the most amazing skiers in the world, and actually, usually when we say, well, what is your goal? It's to flow effortlessly through terrain, to be versatile, to ski this terrain and go into this terrain and look equally as good on both. And I think Carv was never very good at that. It was really good at one kind, but our goal is, as like Charlie said, our goals are to look awesome basically wherever we ski. Nothing would give me greater joy than if someone looked at me from a chairlift and said, that guy looks good on whatever I skied. Now, I'm not there, unfortunately, but I think Carv is now actually aligned with what our goals are as skiers. So it's obviously we're excited as a team because a lot of us like, yeah, we really do like skiing groomers, but a lot of us love skiing like off-piste or different kinds of snow. And that's the fun of skiing and adapting.

And so it's awesome to have a system that does that. While you're there, Alex, I know you did some research with skiers this, over this break. Give us some insight into you know, something interesting you found, like a bit of a pattern with people, skiers not like myself that, you know, obsessed and into improving.

It's interesting because I, I don't think the audience who listen to this, maybe they will resonate and we'll resonate at some level with this, but we interviewed probably 100, 200 skiers over summer, um, trying to understand the new proposition, how to build Carv 2, as well as actually just how to describe it and make our make our goals speak better to the world of skiing. And I think the interesting thing we found is, okay, a lot of people want to improve. That's good. We all know that. And a lot of people understand this idea that if you're better, it's more fun. But the role of technique in that is so interesting. A lot of people don't believe that they should go and work on their technique. I think there's a very funny thing that's, that's true in skiing. That, you know, you guys won't see this because, well, you know it, but your world is all around technique. But most people can say things like, yeah, I obviously, I want to be better. And I'll say, well, are you gonna— what techniques are you working on? And they'll say, well, I'm not really like into technique, I don't really want to work on my technique. Or, you know, and I'll be like, I'll prod it a bit and interview, and I'll be like, oh, well, why is that? And they'll say, well, look, I think like, look, I'm not into racing, I'm not a racer, I'm not like an instructor either, but, but I do want to ski better off-piste. And there's this like very funny thing where technique is sort of a bad, bad rap in skiing. I think everyone wants to look like these amazing people in videos like Candide or someone, or, you know, do this amazing off-piste stuff. And everyone's sort of comfortable with the idea that their technique might be bad, but they could still be good at the sport. Which you wouldn't really see. I think we were talking the other day, Tom, you wouldn't see this in tennis, you wouldn't see this in golf. Like, oh yeah, I could play like 4 over par, but my swing is horrible and I can barely putt. Don't, but don't, don't look at me swing, but I can get around at scratch. You know, it's a very strange concept. Yeah. But I think in skiing we don't really have any benchmarks, right? So, so why does this emerge? Well, our only benchmark in skiing is really what terrain we can ski. So from very young, we're like, okay, I can do the green one, I can do the blue one, I can do the black one, I can do the diamonds. And now I'm an off-piste person, and that is it. And so once you go through the terrain, you don't really have a benchmark. Some people just go faster and they're like, oh, I'm really fast now. And I think technique, it sort of loses its place in the story a bit. Yeah, that's— that was a really interesting learning for us because I think with Carv, a lot of people see improvement as happening when they ski, where they ski, and a lot of people see it as relating to terrain. And that meant we had a huge problem. Because Carl was not very good at other terrain, right? So it didn't fit in with how people perceive improvement, and so it didn't have a role in helping them to improve. And I think changing that has been the biggest thing for us, because I think even in our team, you know, skiers ourselves, we actually want to improve on the terrain where we feel less good. That's sort of what triggers improvement, is when you come up to something that makes you feel a bit uncomfortable you know, a bit in your— out of your comfort zone. Um, you know, there's this funny phrase in skiing, oh, you know, I can— I'm comfortable getting down anything, I can get down anything. And I think once people get comfortable on something, they feel that they've achieved it. And so there's this funny thing where the moment you're made to feel uncomfortable again, you're willing to learn. And then I think some people who, who get really good are willing to get better on stuff they're even comfortable on. And I think those people tend to listen to your podcast, Tom, and those people do get better. And I think that the secret hack is if you try, you will get better at skiing, and then you're going to have more fun.

And I think, yeah, Carver's now got a much wider place than that, which is awesome. Yeah, I agree. I think there's just— there's just, at least where I ski in the world, especially the southern hemisphere, there's just not enough great awesome days where you're going to be entertained ripping around. You skid Aspen all the time, I can understand why people just put on their skis and just go up and down and look at the beautiful scenery and ride the perfect corridor. But the short runs, the, the different snow on the East Coast of Canada and America, if you want to spend a day skiing and really enjoy it and get into it, I think that there is a place for technique and, and skill development. And, and that is a fun thing in itself. And I think once people discover that and that it's not a boring thing or laborious task, but actually it can be novel and interesting trying to do different drills and trying to challenge and change something. That's where, um, yeah, I, I agree with you right there. And I think it's very cool that the Carv now can read all terrain and doesn't handicap you if you are on, on the side of the world where the snow is not perfect all, all the time and you don't have the longest runs to link you know, these 10 perfect carve turns, and, and you don't feel very good about your skiing because it doesn't show up like the other people. Um, yeah, I think that, that direction where it's going is, is cool.

I think the only other thing I'd add, Tom, is improvement doesn't just happen. Like, I think some people— there's a, there's a perception, if I just ski stuff, I'll get better. If I just ski with better people, I'll get better. Even if I buy new skis, I'll get better. It doesn't really happen by chance. Like, you know this, I think everyone listening will know this. To improve at something, you do have to try something that's new. You generally need some inputs, some feedback, or something different, and then you can make change. But you can't just get better just by skiing. Like, to an extent you can, but your curve of growth is very, very flat until you get inputs, until you try. And I think getting more people to try something to shake up how they were skiing, I think would be an amazing thing. If we start to see more people just shaking up the way they were skiing and trying something new, we're going to unblock a whole load of those plateaus everyone's sitting on right now.

Absolutely.

Hey, uh, John, you're new to the team this year and very much involved in, like, when someone opens the Carv app after a day of skiing, what they see, what, what the experience is like interacting with that app. What are you, what are you really proud of other than the granular, you know, being able to see the turn shape, that sort of stuff? Are there any other areas that maybe a familiar Carv user would notice is improved, or a new user when they're opening it, they'll be able to look at it and then, like Alex is talking about, go, oh great, I'm gonna fix this.

Yeah, I'll work on this. Yeah, one of the, one of the biggest things I'm excited about, and I touched on it, is the skiing recording and audio experience now. For me, it was just so difficult to have countless and countless modes that I had to choose from, and I had to weigh the consequences of that. Oh, if I choose this one, I get that. But if I choose this, it was a false choice. We never had to do that. And it was, it was just because over the years we came up with all these great ideas and we put it in a new mode and we put the next one in a new mode. And what we realized pretty quickly is, well, they all are complementary to each other. And you can just have one skiing experience that is totally customizable. But on a day-to-day basis, there's only one button to push, just start, and you just get out there and have fun and learn. And, and it, it creates the opportunity for what's coming because now instead of 15 different brains of all these different modes, We've consolidated it all into one brain so that now we can get to the, the next frontier, which is based on what skill you want to develop and what you care about. It can just adjust all that for you. It can say, oh, well, you ought to try monitoring this for a little bit, and then, then we'll go back and then see how that impact it had on this. You ought to try working on this., right? That's the next step. And this unlocks that because now there's one mode for skiing. All of the brain is pulled together and all of the audio is customizable and you don't have to stop skiing, adjust something, restart something else. It can all just fluidly change along the way. So that's kind of the centerpiece of it all. But it also says we've got a lot more to do, which is fun. Like it, it's fun for our users because there'll always be something new that we can keep adding. It's fun for us because there's new challenges to solve.

So it's, it's both this huge advantage but also this huge opportunity of what's next. I've seen some of the changes that have come through with this new update, and I must say, it just is— even looking at a day of skiing, say, from a month ago, is much easier to just take in. It's not as much like data because, I mean, that's— it's recording everything, but then that's That's a tricky thing you guys have had to, you know, work out. How much is too much information? How much we don't want to— I remember Jamie, one of the, the co-founders, him saying like that was the thing, you just didn't want to get in the way of someone skiing and enjoying their day. And I feel like when you open the app now, it's, it's a lot more pleasant to look at and easier to navigate. So I think that's, that's what I really—

I, I really noticed that. Well, I appreciate that. And that the team involved in that will appreciate that as well. I think that's one of the advantages of having a, you know, new team member and fresh perspective is the rest of the team members have built this amazing foundation. The what it, what Carve can measure and what, you know, what it can do is, is really, like I said before, magical. But the next step is how do you really make that accessible to people? And and simple. And that doesn't matter if you're a novice skier or an advanced skier, right? We, we want to get out there and, and take in the nature and enjoy the skiing experience. So for everyone, what we want to do with Carv is really distill down the most important, most actionable things without you going and digging through every little bit, right? We need to do that detail. So then the brain of it can find those nuggets and pull them out for you. And that's, that's where I think this foundation now is cleaned up, tightened up. It has all the, it has all the details in there. And then the next step is really to pull out all those nuggets so that you don't have to go spelunking for them, right? Which is, which was the old experience. And that's quite delightful too, that the spelunking is still fun. It will still be there and in even more detail than it ever was before. But there will also be this facade that is your guide, your coach along the process. And your story with your son Archie is a prime example about how we want this to be, right? That you gave a little bit of guidance on top of what Karv does, and together they were this beautiful marriage where you could say, hey, Archie, try this. He did it. He got the feedback. And you were this another brain on top of it. I think we can do more of that in the app to bring more of that. But in the end, there's still gonna be, always be this beautiful partnership with expert instructors as well, where Carve can reinforce and, and help them to measure the things that they care about, and they can provide this extra level of empathy and insight and, and, and knowledge on top of that and create this feedback loop. So Uh, we'll, we'll continue to try to, try to learn all of that and bring more and more of it into CAR, but there's always this opportunity for them to work together as well.

And that's a big part of our philosophy is that they, they feed and support each other. Yeah, I'm listening to a book that is sort of addressing, we're in an age where technology, artificial intelligence is getting better and better, and it's called The Skill Code. And he points to there are still things that are necessary to improve skill, and one of them is like sort of like a mentor and this interaction alongside having, you know, these other things like technology going along. And it's just how humans have developed. You know, if I was a blacksmith and then my son Archie decided to become a blacksmith, you know, it was through him having a go and me leaning over his shoulder and pointing him a few you know, tips here and there and helping him, but he needed to, you know, have someone along the way to, to help him there. And it's just, yeah, that human interaction part important. And it's really cool you recognize, I guess, the role. You're not trying to push the instructors out, you're trying to build something that works within and brings even more people, like, enjoying more of the mountain.

I'd say we have more camps and instructor-calf crossover than ever each year. And that's nice to see that growing. I think there's a lot of the people who are Carv users, there's actually now a decent amount of options and they're growing every year of where you can go to get, hey, like I've got this score, I want to work on this. And then you can go and work with some of the world's best people who know all about the system and also, you know, can help unblock you. And it's been lovely watching that ecosystem grow because I think our role in the world of skiing is we can get people— I mean, the first thing is most people don't get any input at all. In fact, we think it's around 8 to 12% of people in a given season will get a lesson on the mountain, roughly. Those are the stats we have from industry and from some of our partners in ski school, um, which means like, let's say, 80%, 85%, 90% of people aren't getting any inputs. And so the cool thing Carv does is it makes people stoked about improving, and they get it, and they realize there's maybe more work to do, and they're not quite as good as they thought they were. There's always a little bit of a painful realization. I think it's quite an honest tool, and so That's kind of interesting. And then we survey people to say, well, what changed about your skiing? And most people, 96% of people, say they improve. But the cool thing is, I think it's 96, but I'll check it, 95 or 96% of people say Carv made them more interested in technique and improving. And that then drives them to want to do other things. Now, other things look like signing up for Big Picture, it looks like getting a lesson, it looks like going to camps. It's actually really like synergistic with the current industry. And so I see Karl's role as activating people that there's more to do, that there are things to go and learn. And there's nothing more awesome to the right person than getting better. Like, for people who care about improvement, getting better is like the most empowering, awesome feeling. You did it, you know, you got better at the thing you love., and that feeling is incredibly exciting. So I think that's Carv's role. I think it's amazing seeing some of our partners yourself, um, you know, we've got Thomas Renaud and Morgan and all these amazing instructors, Bartek, and all around the world there's people now teaching on top of Carv.

And I think honestly, the more of that, the better. It's a wonderful ecosystem. Hey, I want to touch on— you mentioned the honesty part. The SkiIQ has changed it's measuring things different. When the, the new software rolls out soon, are people going to see a difference? Are their scores going to change? If this is asking for the Carv users of past, are they going to go, well, I had this great score and now there's a recalculation done?

Is that—

maybe Charlie, you can talk to that.

Is there going to be changes to people's scores? Yeah, in short, yes, there will be. So every year we update SkiIQ, uh, for greater accuracy as we're constantly learning from, you know, chats ambassadors and our increased data set, all the Ski-Mash coming in, you know, we don't want to just fix SkiIQ as this one thing. We want to always, always make it more, uh, more accurate and improve it. And then this year, the main focus has obviously been across all conditions. So yeah, people can expect their off-piste skiing in moguls and crud and powder— they can expect those scores to go up. You know, we're also getting more accurate on-piste as well, so people may drop down, you know, there's swings and roundabouts. And, um, the main thing to know is that we're now— every year we're more accurate, so you can go into the season and try and improve on whatever score that you have with our new reprocessed, uh, SkiAQ Nevada. But yeah, I expect particularly advanced skiers who are— and expert skiers who are skiing in these off-piste terrains, those scores will go up, but the, the highest possible score is still on a carving turn in, in groomed conditions. So those scores should stay fairly similar, but, um, yeah, they, they can go up and down. But because we're now accounting much more for how steep the run is, that's another thing at the elite level, uh, skiers on carving on steeper terrain, those scores are going to go up. And that actually touches back to what John was saying about our sensor fusion upgrade. This has had knock-on impacts across all metrics. So all of the metrics are now more accurate. But one particularly interesting use case for our adventure into all-terrain is how steep the run is. And we're now actually able to detect the slope pitch for every turn that you do, no matter where you are. So previously we actually cross-referenced with a database of known runs to work out how steep the run was, but that obviously doesn't work in the backcountry, doesn't work in smaller resorts where no one's done this, uh, this mapping. So this year we're now able to understand how steep your skiing is from every turn that you do, which then feeds back into SkiIQ. So that's a really big step forward, um, and we can expect those steeper runs, to be scored more highly. And yeah, in general, the philosophy behind SkiOQ is to reward higher skill skiing with higher scores. So yeah, we're really excited that we're now able to do that across different terrains. But for, for, yeah, every skier, like for me, I, I went down.

I've already had a look at my— yeah, I've seen, I've seen some, some of my runs go down. And as probably I was thinking, I wanted to share that too. At first I was like, like, oh, you're kidding me, it's like you've been robbed, is the first probably I would say people experience that. But really, I think you have to like check in with yourself and go, well, this is accurate. And when I thought about that one, I knew that this kind of slope was, you know, a bit of like a, a ski hack kind of run. Oh, I knew it was not that steep, but I could go fast enough to get some higher edge angles and move my feet really quick and maybe it wasn't what I would classify as like my best skiing, but I knew that the algorithm liked it, and I could see that I got dinged back on that one. So the honesty of the new SkiIQ is, is definitely there. And I would just say, listeners, if you've got some scores there and you, you feel like, oh, I just got over 150, but now I've been pushed back down into the mid-140s, that's a good thing. It's like, now it's, now it's a reality, you know, rather than dancing around and thinking you're looking great, saying, hang on, still some things to work on here. And which is awesome, there's, there's improvements to come.

And, and that's the best feeling, is when you, when you get better. Yeah. Well, the other thing to add, I think, is the thing that makes it palatable, and maybe not only palatable but maybe delightful, is that with any of those changes, you've got all this extra detail. That you didn't have before. So it helps to illuminate when you go digging. There's this treasure trove of digging to be done before the snow hits. I've been working with a bunch of people and testing. We have this what's called a First Tracks program now where— and you're a part of it, Tom— where people can get an early preview, and they give us feedback, and they test things. They're digging in, and they're finding things. Oh, that's why this has changed. Now I can see the turn graph. Now I can see these details. Now I can see the snow surface. All of these variables that were hidden before now are illuminated, and you can start to make these connections. So I think it's going to be fun for a lot of our users pumping up for the ski season to be able to see all their data and all this new treasure of these details in there. Yeah, that's right.

It might be a little bit of pain here and there where it's like, oh, just remember this conversation here, and that's You know, the only way is forward from there. I want to be respectful of time. I really have enjoyed this conversation. I love hearing about how problems are solved like that. The forward movement thing, I mean, that's, yeah, crazy that, you know, everyone would think you'd have to have pressure. Like, if that's what people feel, you know, I feel when I'm moving forward, but you're able to get around that. It's amazing. Love hearing those stories. Love hearing what's changed, what's coming up, that, that all-terrain is there.

You guys, do you have anything, any final words, any maybe common questions that you've seen coming up? Just to thank you. Thanks for having us and chatting for all this, and thanks to everyone who's contributed to this. As, as Charlie and Alex said, none of this would have been possible without all of our users. They've been feeding us data. We ask them, well, what is this terrain like? What do you feel about this? And, and this includes everybody who uses the app. And then also a lot of folks that we work with closely on SkiMash and other tools. It's just amazing how passionate the community is and how that's been able to help us make the experience better for everyone. And, and we're only gonna do more and more of that. There's gonna be opportunities, um, in the Northern Hemisphere to be part of the First Tracks program and and get early previews of things and provide early feedback.

So folks are interested in that, just get in contact with us. Yeah, I, I just have one thing on the end. It's, it's something we haven't really covered much, but I think this year we really wanted to make it easy for people to try CARV, especially the new CARV that we're really stoked in. And we actually, we basically halved the price this year. So if you are listening and you're like, oh, this seems kind of interesting, I've been watching it for a few years. This year the device is free with the membership, it's included. So the price is essentially halved to try Carv. So I would say, I mean, we did that deliberately. Obviously it still costs us to make these things. They're incredibly technologically capable and, and they're very, very delicate and, and amazing pieces of equipment that we've built. But we just want to make it easy for people to try it because once you try it, we're pretty confident that you're going to love it.

So.

I'd say if this is the year that you were sort of looking at it, head over and try it. Yeah, hopefully we'll have enough stock for the season, but it is going kind of fast at the moment. So I would say hopefully your listeners will get in with this podcast. But yeah, we really tried to make that accessible. So yeah, try it and let us know. We're always listening. We always love to get feedback. Some stuff you love, some stuff you don't love.

You'll probably find we'll change it and improve it next year as a result.

Charlie, you got any final words? Yeah, just echoing the others. Thanks to all the users. And super excited for the upcoming season. Taking Carv off-piste is incredible, and we'll keep improving the surface detection. You know, there might even be some new metrics that we're working on that we release in the middle of the season.

So yeah, stay tuned. And yeah, as Alex says, give it a go. Highly recommend it. I think that the new Carv 2.0, big improvement, way easier for everyone to try it out. Thanks everyone for listening.

Thanks for tuning in, and we'll see you next time.