Gene Feldman: Good evening, everybody. Welcome to our latest episode of Neon Protocol, where we break down the new technology and really talk about what's going on today. we have with us our Neon Protocol members. We have Ron, we have Damon, Dan, Mike, and Lucky, and myself, Gene. And we're being joined today with actually a close friend to the Neon Protocol committee. Actually, he's actually related to one of our committee members. And before I really get into it, kind of say that what as a committee, we've always tried to be very impartial, try to be a very open group to dialogue. So we never really advertise our own use cases or our own personal interests. And so, but what Lucky and his brother Ash Gobindram have been really doing with their company, Kenemetric, Ken American. I always throw the T in Ken American I just was corrected on that. What they're doing over there is some really cool stuff. And and Lucky's been a part of a lot of our conversations, but he's I always tell that he's kind of careful on keeping that unbiased approach. But this is really a chance for us, Ash and Lucky, really just to pick your brain and see what you guys are doing over there because you're really doing something neat with with how you're making emotional connections within. computer training and within these immersive environments. So Ash, rather than steal your thunder, I'm gonna actually let you kind of go ahead and introduce yourself and kind of what you guys are doing over there.
Ash Gobindram: Sure. Thanks for having me, Gene, and everybody else. so yeah, I'm I'm Ashko Bindrum. I've been building technology for, you know, the better part of the last twenty five years since, you know, I was a teenager. and about two years ago Lucky and I started Kinemeric. we really saw an opportunity, you know, with the maturity of L LMs at that point to kind of serve as an underlying engine for believable synthetic human interactions, especially in a spatial application. so we started building Kin American at that point. And today we really, you know, see ourselves living at the intersection of AI and spatial computing and how we can use those technologies to positively affect the way corporate trading and learning is done you know, today.
Gene Feldman: So when you get into like how do you positively affect it, what are you seeing that AI is able to bring to the table that is a little different than I guess the standard training model? Because I think that's the question a lot of people are gonna have that usually as a trainer, that's what I always get. How is this going to be better than instructor learning?
Ash Gobindram: Well, I think it's really about kind of harnessing what the the good things about instructor learning are, but giving it an opportunity to scale, right? I think that a lot of corporate training and learning departments try to do a good amount of role playing and a good amount of one-to-one instruction where possible. But really that's often hard to scale, in, you know, your typical corporate environment. So if we can teach our synthetic humans to behave like real trainers and provide that one to one level of, you know, care and interaction for their trainees, then we find that there's really a a positive result and, you know, a good net effect for the organization as well.
Gene Feldman: Nice. And I like you're using synthetic human beings. Sorry, I'm catching I caught that like twice now because everybody usually uses avatar. It's avatar. You know, I I we all fell under, you know, James Cameron's spell or something. so so what is what is the synthetic human? I mean, I guess how are you looking at to explain it like that? Because I ru I'm really curious.
Ash Gobindram: Yeah, I think for me, like the dichotomy is that, you know, growing up playing a lot of video games and, you know, thinking about what a a an avatar has, you know, come to mean, you know, through video games and, you know, even through social media over the years, you really have a an operator behind them or you have a very limited amount of interactivity, with the, you know, the the NPCs, if you will, or you know In a social media context, an avatar is usually kind of just a a representation of an actual human. So for us, we're, you know, creating characters and embodiments of, you know, values or lessons within a a a a digital human, but you know, it's it's kind of autonomous in a lot of ways, right? There's no human that's really driving it on a day-to-day basis behind it. It's able to answer your questions, it's able to interact with you. you know, all on its own based on, you know, its training and, you know, our kinemeric orchestration layer. So that's
Gene Feldman: No, I like
Ash Gobindram: yeah. That's kind of how I see the dichotomy in my mind, Gene.
Dan Meeks: I I got a question about that.
Gene Feldman: No absolutely. Yeah, go ahead, Dan.
Dan Meeks: so one of the tragedies of being a human is that we learn so many things and then we die.
Gene Feldman: Way to sum up the life experience
Damon: Wow, Dan.
Gene Feldman: right there, man.
Dan Meeks: I mean, but but hey, so my question to you, Ash, is and and I wish Mark would hop on, because there there's a difference between having consistent training. but when you train people, you want to have the best instructors possible. So not only like when I used to teach, not only did my students get better, but I got better at my craft because I had to figure out new ways of explaining the material over and over again. So you have these synthetic humans, you you don't use the term avatar. Is that the case where they improve on each cycle, to where, you know, they they get better at their craft and hopefully don't die.
Ash Gobindram: Sure. So I mean, that's definitely, you know, part of the vision. I wouldn't say our synthetic humans are doing that just yet, Dan. but that's definitely part of the vision. What we are really focused on right now is the ability to really know your core material. obviously whether the synthetic human is taking the role of an instructor or like a colleague for a believable like role play kind of interaction. where there's a lot more variability and you're not really trying to achieve this this apex level of information. you know, is a little bit different in use cases. So really it's about, you know, creating a believable enough persona where, you know, they can explain the same subject matter that matters, you know, to the user in N amount of ways and really meet that user where they are while still maintaining a believable persona personality or persona. but they're not They're not self improving just yet. And, you know, that's definitely something we're working on and thinking about.
Mike Vann: So I yeah, I had a follow on to that one. So Ash, are you able to like ingest a company's methodology, their proprietary way of thinking about right? Like I mean, they've been training in a lot of cases for a long period of time. You know, these companies have been doing this, and now you're able to bring intelligence to that and bring it into an immersive, you know, high touch virtual experience. So are you able to pull in methodology, even like use cases that are, you know, more recent, right? the ability to update. Can you do all of those things?
Ash Gobindram: Absolutely. So that's exactly what we're doing, Mike. So w what we do typically during an implementation is we do like a deep download and like fact finding, you know, kind of phase upfront and really learn like what's unique about that organization, how they're approaching the problems that they have, and how they solve those problems. And then we work hard to, you know, kind of transcend that into a curriculum that's easily ingestable, you know, by our agents and you know. Basically, it leans a lot on our kinemeric orchestration layer, which lives on top of the LLM. but yeah, that's exactly what we're doing. And as we progress, we're starting to create tools where, you know, the the core curriculum is really kind of broken down into something that's accessible via a web panel. So, you know, if a procedure or a policy is changing you know, on the fly, you don't need, you know, an engineer or kinemeric to necessarily update for you. you know, you can basically affect your agents through, you know, a web application that's able to, you know, kind of ingest those updates.
Mike Vann: I mean, I could see how that could be super powerful, right? I mean, if something happens in a company that is really critical, that everybody out that is in active training, you know, needs exposure to, the ability to update that one month and and have it out in front of people quickly is very different from the old way of of training a workforce, right? Yeah.
Ash Gobindram: Absolutely. And like with the underlying LLM and our orchestration layer, you know, it takes that core information and, you know, like I was saying before meeting the trainee where they're at, you know, it's able to present that information in N amounts of ways, right? So really, you know, if there's a particular allegory or, you know, some s abstraction of that that makes it easier for that trainee, you know, they can have a one-on-one freeform conversation with the agent and be like, you know, can you explain that to me a little bit differently? Or, you know, how how would you say this happens in this case? And, you know, really they're able to answer on their toes pretty effectively.
Gene Feldman: No, and I think you hit a key point, at least, you know, when you get into training, everybody talks about the assessment piece of it. You know, being able to track that progress throughout it. So as you're getting into this, you're also kind of leading into an assessment piece. And I think one of the ways your software and your solution really is great. It's removing multiple choice questions from the assessment piece of the training. You know, I by you saying the open dialogue, one of the things that I've experienced as as being in training and development majority of my career is multiple choice questions. A lot of times people feel there's setups, you know, because you know, especially when you're doing scenarios, what I would choose is not one of those four options. And I think having that open dialogue, and I guess wh my my question is, are you seeing the assessment piece of it? People are people responding to this better than not only the instruction, but also the assess the assessment piece of it.
Ash Gobindram: Certainly. I think because, you know, on every single session that we have we're we're ingesting all of the audio and running full analysis on all of the audio. and you know, we're we're Providing deep insights based upon how the the actual genesis of the conversation has gone and you know, your mastery of the information. So typically where you're, you know, we're used to assessments of like, okay, I got an eighty-five percent on that
Gene Feldman: Mm-hmm.
Ash Gobindram: or an eighty-nine percent on that, you know, you're really missing that dimension of like granularity on your mastery of the material. And, you know, through the gift of that LLMs and AI, you know, is, you know, we're able to actually provide, you know, very involved, deep, you know, analyses of how they how they've mastered their material, which I think really resonates with the trainees because they see what they said. they see suggestions of how they could have presented it better or where they fell short. And, you know, it's directly what came out of their mouths. And I think that, you know, that really hits them close. So yeah, we definitely see a positive, you know, a positive effect on the trainees with our analytics tools. And, you know, besides like the fact that multiple choice questions are kind of like, you know, they're tricking you, they they guide you as well, right? You know, if you have
Gene Feldman: Mm-hmm. absolutely.
Ash Gobindram: four answers in front of you, it's pretty easy to kind of, you know, pull the right answer out of the bunch. But, you know, if you're, you know, presented with a a case or you know, a scenario and you really need to answer that effectively and you don't have a a multiple choice, you know, cheat sheet, if you will, in front of you, you know, it definitely makes you strive a little bit more. And we think that matters. But we do do multiple choice also. But, you know, like
Gene Feldman: absolutely. Well, yeah, but but I I think people don't realize like in when you're taught how to write multiple choice tests, you're told to write two questions, two answers are obviously wrong, and two are cleverly disguised, you know, of it could be one or the other. And people love using the word not or not
Mike Vann: Yeah.
Gene Feldman: using the word not. So you start getting really mixed, it can really confuse a learner. So I'm always really curious on that approach to it. And I know Ron, I cut you off, so I apologize. I will so please
Ron: No total no no problem.
Gene Feldman: go ahead.
Ron: Sure. so Ash, what kind of metrics do you have about how much faster people learn with your approach versus instructor-led approaches and other technology enabled products?
Ash Gobindram: Sure. So I mean, you know, the the one the one deployment that, you know, is really public right now and we have a good amount of data on, you know, we've been running we've been running this deployment for upwards of a year now, Ron. And, you know, it's basically an application of the technology to distributed field sales teams. And what we've seen there is that typically, you know, it used to be, I think, six weeks before a sales rep actually closed their first deal. And, you know, on top of that, they were burning, you know, a ton of actual leads in, you know, getting out there and finding that experience in addition to, you know, the instructor led guidance that they had. What we see now is that these new trainees actually can close their first deals in week two. So we we've reduced their their time to actually closing their first deal by close to 200% at this point.
Ron: Interesting. And what's the is there any difference in terms of how well a person understands the subject matter with your approach versus others?
Ash Gobindram: Absolutely, because because they can, you know, spend as much time with the the agent or the synthetic human as they'd like, you know, they really are able to ask questions and you know slow down the instructor, if you will, so that they can understand the material. thoroughly where you know in a typical kind of tri corporate training learning environment there's a lot of you know social factors that hold you back right people you know don't want to be the guy who's asking every question or slowing down the class. Really with this kind of a solution we remove you know all of all of those stressors on the situation. So we do see a significantly greater level of mastery in the actual subject matter. And you know that goes all the way from the trainees to You know, even actual leadership who's now partaking in the in the training, you know, will hear anecdotally like, well, I'd never thought about it like that before, or I'd never presented it like that before. so even they are finding value in the solution right now, right?
Ron: So so do you have any metrics around the ROI of your approach versus self training, instructor led training, and other technology enabled training?
Ash Gobindram: Sure. I mean, I could say, you know, I could say at least like, you know, per trainee, we're seeing, you know, in the deployment I just spoke about, for example, you know, we're seeing at least ten to twelve thousand dollars annually in savings per trainee right now. And that basically goes through, you know, amortization of instructor time that's no longer applied to them, as well as savings in leads generated and burned that they were previously going out there and, you know, practicing on, if you will. So that that is quickly scaled to, you know, hundreds of thousands of dollars in savings annually at their organization. but they're they're not the biggest company, right? They're they're a mid-sized construction company out of the Midwest. So, you know, if you take the principle and you extrapolate it to a larger sales organization, this, you know, this could quickly grow to be millions of dollars in savings annually for for an organization.
Ron: So then what would the ROI be when they invest in your stuff and your methodology with these savings they're achieving?
Ash Gobindram: Yeah, so I mean I think that, you know, the return in investment and like, you know, the math the math is kind of, you know, right there. You know, so like basically if you're looking at like, you know, two hundred thousand dollars annually in savings, that's just like your real like, you know, your real your real like fiscal number. But then the actual strength and, you know, ability of your sales team and their mastery of the material and their ability to, you know, actually sell that much more. when they're out there, you know, you would tack that on as well. So I could
Ron: Right.
Ash Gobindram: say this this could, you know, the return on investment could be, you know, 10X annually.
Ron: So it could be like within a month. within a month or ahead of the game.
Ash Gobindram: yeah, for sure. I mean it it definitely varies from organization to organization, but you know getting back your your investment money within a month is definitely plausible in this scenario.
Mike Vann: I mean you're you're impacting speed to delivery of training as well, right, Ash? I mean, once you get there, it's not like sending trainers out around the country. I it's you have some efficiencies right there and the ability I mean, sales is a great place to be operating because you're you're dealing directly with the revenue. So if you can make an impact there, it seems like a good spot to be.
Ash Gobindram: Absolutely. And I mean we're seeing yeah, go ahead, Ron, sorry.
Ron: So yeah, so what are the what are the main challenges to success?
Ash Gobindram: I mean, I would say, you know, there's still as much as I'd like there not to be, you know, we're really, really committed to spatial computing. So I mean, I think there's still inherent aversion to spatial computing at a lot of organizations and really getting them to commit to, you know, hardware and understanding the value, you know, that that a spatial computing device really has. that That's often a challenge till today, Ron. you know, and I'd I'd like to see that change a little bit quicker. but that's definitely still a significant challenge. Lucky and I still haven't committed to doing like a mobile or a tablet deployment and we're really resistant to doing so, even though we get asked that question all the time. just because we believe that, you know, when you're really immersed in, you know, in the solution and you have a full blown, you know, 3D synthetic human in front of you. Either in mixed reality or full blown virtual reality, that's where you're getting maximal value. but a lot of people are like, you know, we don't want to listen to that. You know, how how can we get this on an iPhone? so we haven't we haven't kind of acquiesced those requests up to this point right now, and we we very well may never, but it's definitely a major deterrent in a lot of conversations till today.
Ron: So then you need to have a bit of a different reference. If you say spatial computing, it does have that you know pause with people. But when I say immersive learning, I would think that would trigger some curiosity about what you mean by that and how do you you know deliver on that? And so you have to have the headsets and things like that. But as these tech companies bring up these newer devices with like you know, projection capabilities and other forms of hardware, then there's more ways to experience immersive learning. So I wonder if I should be a way
Ash Gobindram: For sure. Like, you know, like holographic
Ron: of approaching it.
Ash Gobindram: holographic displays are super cool. I think that, you know, there's still a lot of mac lack of maturity on that front. I mean, the looking glass guys are doing really nice stuff out of Brooklyn, but you know, anything bigger than their eight or ten inch model is a pretty hefty price tag in its own. so we definitely use like Different kinds of, you know, terms like immersive learning. but really once you start to get down to the nuts and bolts, you know, people quickly realize you're talking about a virtual reality headset or, you know, an AR-based headset. so we've gotten we've gotten some pretty impressive organizations to, you know, get into it, you know, and and start to buy headsets and start to adopt. But even then internally, you know, there's always resistance. You know, even if they see the vision in one particular unit and they can they can kind of present the facts and the benefits, you know, getting by in beyond that that pod is, you know, it's often difficult. So
Gene Feldman: As well as well as I can speak from personal experience of leadership changes and the vision of that leader, you know, I mean, I was kind of a victim of that. So it's it really comes into that that piece as well, that, you know, trying to get that use case. Cause like one of the things that I found by doing the spatial doing the full VR headsets was the emotional connection that the learners were having. The uncanny valley was gone. Everything was gone and they were coming out just angry, upset, or you know, they because one one of the things that we tr that I found is that that truly creates that true to life experience. You know, I've always said that if you really want to see VR's true to life experience, go watch a video of somebody doing Richie's walk the plank. You know, you'll see emotional impact. And I think that's where, you know, the strength is. Unfortunately, we're at a kind of a rebuilding year with this whole. VR. but I still I but I think one of the things, because I also want to go back to your AI piece of this, because I like the blend of your AI. So in getting back into the AI and the synthetic humans, one of the things you said it can learn from itself. And I assume that it could have retention. Because one of the great things about learn learning avatar is that or synthetic humans that you keep coming back to it and they'll remember where you left off. It can grow with you. But and Syntheticum is a great way to to lower people's heckles, you know, and to calm people down. But how do you overcome that? It can learn from its, you know, it it can grow. It can, as you were saying, it's kind of it, it's just it you can have an open dialogue with it. I think people are gonna be worried about the guardrails of it. And I guess is is there any type of controls or is it true, is is your plan to truly have it kind of an open AI? How do you see that playing out?
Ash Gobindram: No, there's definitely guardrails, Jean. And so it's not, it's not actually self-improving just yet. That's that's definitely something we're working on, but we haven't commercialized that just yet. But in its incarnation today, there are definitely guardrails. Now the guardrails are definitely very wide. you know, we we try to give a lot of, you know, lateral ability to the agent to be able to respond on its feet to the user. but there are definitely guardrails. Like we don't want You know, we don't want the trainee and the agent having, you know, too much of a conversation about, you know, football or, you know, whatever it may be. So like depending on the use case, you know, like for example, in a sales use case, building rapport is typically part of any sort of sales ritual or the phases of it of a deal, right? So, you know, to the extent of building rapport, it it definitely does its job and it's able to play the role. And if you want to discuss you know, football or cars or kids or whatever it may be, it definitely delivers a highly believable exchange and, you know, a highly believable, you know, reality, you know, with whatever personality or persona or character that, you know, that synthetic human is at that point in time. But it's careful, you know, to try to pull the focus back to the objective at hand within, you know, the the right kind of, you know, timeframe, right? So, you know, if it's
Dan Meeks: yeah.
Ash Gobindram: basically a a sale, you know, like say, you know, you're a salesman and now you're in the house of somebody you're trying to sell windows to, for example, it will have that, you know, that building rapport phase with you. But, you know, before you realize it, like a real homeowner would, it'd be like, that's great, but can we talk about the windows now? You know, and it's careful to, you know, intelligently, you know, segue the conversation. so there are definitely Rails. but you know, it's definitely a a bit of an art as to, you know, how wide you set those rails and, you know, how you kind of orchestrate the synthetic human to be able to, you know, evolve the conversation back to the subject.
Gene Feldman: Nice. Now I I love seeing this.
Ron: Okay, so do you have anything you can show us of what you do?
Ash Gobindram: I can show you what I do. I don't I don't have I don't have a demo ready for you right now on the fly, but I can definitely get you a demo around.
Gene Feldman: And and for those of those that are listening since we're only audio, we will have links for all the websites that you can go to. for can me canmeric.
Ash Gobindram: In America.
Gene Feldman: Thank you for canmeric. I've known the name for years and I still have trouble. But for Kimmeric, which the website has a lot of the great a lot of the great examples that they're talking about.
Ash Gobindram: And I'll we'll try to get you some videos of some some stuff that's not published just yet, some more recent stuff. So we've really been going deep on, you know, a lot of like instructor-led, like we're gonna train you on entire basics of roofing or the entire basics of insulation. And actually, we're starting an engagement right now where we're actually gonna apply the technology to an academic institution. So it's gonna basically work in concert with a teacher. for seventh grade, you know, anatomy classes where, you know, basically they'll have their lesson in class, and then they'll be able to take a headset home from the from the school and then actually like kind of like a a TA, if you will. the synthetic human will be able to, you know, hit those lessons home further, be able to have conversations with you, explain stuff about you know the the human anatomy, pull up corollary, you know, materials and diagrams. so We don't don't have any videos that we could show on that front just yet, but I can definitely get you some stuff on the former stuff with, you know, these synthetic humans teaching roofing or teaching insulation. you know, that would be cool.
Gene Feldman: That's absolutely awesome. So are you so as you're getting into roofing, but have you no have you identified like there's there's these key like skills that you've kind of found that to be universal that are are like hits for everybody? Or is it or are you finding like like if I were to ask like what are the top five sales skills? Cause I would assume negotiation and some of the other things. And you know, so I guess what what are you hearing
Ash Gobindram: Absolutely. Like for sales there's definitely
Gene Feldman: that there are universal skills across the landscape?
Ash Gobindram: I mean, so I think like you you like you kind of said there, Gene, I think that depending
Gene Feldman: Ha.
Ash Gobindram: on the arena you're playing in, like there's some things that just transcend between organizations really well. Like, you know, if you're in a sales kind of cycle, like, you know, understanding how to build rapport, how to surface objections, you know, how to start to early early on in, you know, the sale, acclimate the acclimate the buyer with the idea of the price, right? those things kind of transcend across sales org to sales org. But I think that depending on the subject matter you're kind of applying the synthetic humans to, you know, there's definitely some specifics within each discipline.
Gene Feldman: Yes.
Mike Vann: Hey hey Ash, quest quick question. I know things have really evolved over the last couple of years, but you know, when you're doing these kind of training experiences, especially in, you know, fully immersive, how how are you handling, you know, body language and sounds and I mean I know vo you know voices are getting better, but a lot of this, right, to get it to be kind of real life, you need some of those reactions and some of those human things, especially when you're talking about sales, you know, if someone's gonna be difficult and really press and kinda, you know, get ornery about an issue, like you wanna see that come across. So are you are you seeing that improve in in the synthetic humans and the tech that you're working with?
Ash Gobindram: Absolutely. So I mean, I think voices are really, really good. I mean, tone is tone is pretty good at this point as well. I think that, you know, a lot of that, you know, you can harness some pretty great like foundational models out there. you know, and basically integrate them into your your orchestration and get a really nice result. I think that, you know, animation continues to be something that we're working hard to refine on our end. There's not just a an easy solution for that. you know, and what's nice is that we find like, you know, Gene talk spoke about the uncanny valley a little while ago. We find that if you have a believable enough conversation and the voice is good enough and tone is really good enough, then some of the things that typically used to throw us into the uncanny valley start to rescind a little bit and you're not really in that spot anymore. And people kind of bite into the conversation and the exchange. But You know, I think that animation is definitely something that continues to be, you know, probably one of the most challenging areas we work on because meaningfully correlating the output of the synthetic human and what they're saying with, you know, the right, you know, sequence of animations or body language, that's definitely an ongoing challenge. So we're on like I think version three of our synthetic humans today, like from a a look and feel standpoint, and we're gonna continue to, you know, chalk out time for the team to continue to improve that. That's almost like, you know, an ongoing effort no matter what we do.
Mike Vann: And and it's right, it's it's it's exp it's an expensive prospect to try and get like there. So I imagine that, you know, especially learners, they may be a little more comfortable if they know this is not a a direct human, you know, a replication of a human, but rather a a synthetic a synthetic human, but if the voice and the sounds are really high quality, I think you're it feels like you're in a good spot.
Ash Gobindram: Absolutely. And like, you know, beyond the actual interaction with the synthetic human and their voice and their sound, you know, we try to, you know, lean on like our history of building VR and spatial based applications and do, you know, a really good job of like ambient sound design and environment design. so that, you know, you're closing just as many of those open loops in the user's mind as possible. but yeah, I mean like voice is definitely in a good place, tones in a good place, body language is certainly continuous work on it. Work you know, work work in progress, Mike.
Gene Feldman: Is
Damon: So business wise then considering the business planning side of this and market growth, aren't you limited then by the hardware that's available on the market and whatever happens to it sort of determines your destiny? If a whole segment
Ash Gobindram: I mean up to a point.
Damon: of headsets go away or the OS goes away but the headsets are just, you know, door stops, aren't you kind of sunk?
Ash Gobindram: Yeah, in some ways that's definitely, you know, like like I said, Damon, like, you know, up to this point we haven't acquiesced to the ability to deploy our solutions, although they're easily and readily deployable on your more traditional kinds of devices, like, you know, an iPhone, an iPad. you know, we we're big believers in spatial. So we're gonna continue to try to, you know, pull it as far and make it as big as we can, leveraging only spatial computing, but you know. I'd be lying if I said that it hasn't crossed our mind about, you know, doing deployments on on the iPhone or the iPad. so,
Damon: Yeah.
Ash Gobindram: you know, definitely years like this one. Like I think Gene said that it's a bit of a recalibration year for devices in the in the industry. And we think that that's definitely very real. And, you know, it's definitely easy to get into your own personal trove disillusionment, if you will.
Damon: Yeah.
Ash Gobindram: But I mean, you know, you get a story like, you know, the I think today Road to VR upload VR did an in-depth an in-depth feature on the new meta phoenix headset, which seems to be, you know, very real and you know, probably gonna roll out in Metaconnect. We'll see. so we're talking about a super lightweight headset with external battery and extreme external compute in in its puck, which is, you know, a little bit different than what we've seen Pico or Apple do with their devices. so we're talking about something that's gonna be super lightweight, potentially sub thousand dollars. And you know, that that maybe breathes more life back into, you know, where we're at with the headsets. I think there's definitely
Dan Meeks: It's
Ash Gobindram: been some Some sad news out of Apple's pocket over the last ten days. I think, you know, Mark German was reporting that, you know, they've laid off some members of the Vision OS gaming team, but I'm not really sure what the gaming team was doing. It hasn't been exactly a hotbed of gaming activity. you know. So but I I I think, you
Mike Vann: Yeah.
Damon: Yeah, yeah.
Ash Gobindram: know, as long as they're still committed to, you know, the platform, even if it's on a, you know, a three year device roadmap. you know, I'm still I'm still hopeful. I go back to the The fundas of the device, right? And like kind of what made me fall in love with spatial computing devices 10 years ago. And, you know, basically the core value props are you could bring anything in the world to you, or you could teleport yourself to, you know, anywhere, you know, either real or imaginary. And I think those value props are just still too valuable. you know, when I do spatial FaceTime calls, you know, I always am reminded by, you know, that very real power. Obviously, you know, the Vision Pro is heavy, it's very cost prohibitive. But if some of those variables can kind of be, you know, rejigged and I think there's some enough activity in the space that they will get there inevitably. you know, I think that doing a FaceTime call or doing a spatial FaceTime call, they're worlds apart, right? So like Lucky and I we grew up with you know, we were basically the the only ones in our family that grew up stateside, basically everybody else was in Asia. And, you know, we used to do weekly phone calls of our grandparents on Saturday mornings. And like I just think about like the sense of presence that, you know, a spatial FaceTime solution could have had in that scenario. Right. And it's just hard for me to believe that, you know, as long as there's enough work and we're able to get the devices to the economics and like the ergonomics that are necessary, that, you know, those value props suddenly you know, disappear or vanish. I think that they continue to endure and, you know, I'm I've got faith that the the industry will get there. So
Dan Meeks: Well, we we have a paradox
Gene Feldman: Yeah.
Dan Meeks: with XR hardware. In order to make a good XR headset, you need to get into gear of a giant institution that is very hungry. And once you produce this nice piece of hardware, you can't simply turn back to that institution and say, Well, my business has a privacy policy, my business has a data sovereignty policy. They don't like it when you do that. Or when you do that, they do like the Vario and charge thirty grand a headset. And I don't think you want to pay thirty grand a headset. So we have this horrible paradox dilemma, whatever you want to call it, when it comes to enterprise XR hardware. And you know, you mentioned Meta coming out with something. And yes, Meta's full of the the most talented and congenial people I've ever met. But when it comes to enterprise, they keep fumbling it. And they keep fumbling it because They can't really listen to what you're trying to do as a business and securing your data and keeping those conversations private and not giving any telemetry. And they simply cannot do it because of the institution that was necessary in order to bring that hardware into being. So yeah.
Gene Feldman: Yeah. But I also but I also
Ash Gobindram: I think that well, I was just
Gene Feldman: th I was gonna
Ash Gobindram: gonna say I I think that's part of it. And then I also think that the other part of it is really, you know, the the workforce like, you know, really getting charged up enough that they're demanding these things, right? You know, I remember fifteen years ago, you know, most most corporates had almost zero Mac Or, you know, zero Macintosh presence because there's there were no tools to manage the devices. There were security nightmares for the IT team because they just didn't understand the MacBook. And I think that there was enough demand from the workforce that these things have changed significantly over the last 15 years. You know, any major corporate today has PCs and Macs, you know, deployed like side by side. So I think that that's definitely part of it, Dan. I think the other part of it is that, you know, the the people at the organizations really demanding and saying, We need these tools. We see the value in them and they they change us for the better. I think that, you know, we need devices that instigate that kind of a reaction, you know, from the workers.
Gene Feldman: Yeah. But we also have to I'm gonna throw a third prong in there, is that this the admin software, because you said the enterprise tools, I will tell you, trying to integrate it for years without work Oculus for Workplace or Quest for Workplace, whatever they were calling it at whatever time, it it would never have taken off in the Enterprise because IT does not wanna own it without something to manage the software. You know, and to manage the headsets because I think for some of us that have had the pleasure of sideloading multiple headsets, you know, we're he we're done. We that's the last thing we want to do. You know. and so I think also too, I think one of the things that's hurt Meta and that I think also hurts a lot of companies, is that there isn't everybody's got these separate tools, but there isn't a at least till Samsung, or it's not Samsung, but Galaxy or not. Galaxy Android XR comes out. I've gone so many different devices. Android XR. But the thing is, is that until there's a management software that such as like what IT can use for Windows and Mac devices and iPhone and phones, that's really also going to be a major crux to it because nobody's going to want to own this.
Dan Meeks: Yeah, you y
Ash Gobindram: Right.
Dan Meeks: you have people that are trying to get in that well not get in but have been in the space like Arbor XR and I I there's a handful of others that I can't quite remember off the top of my head. But
Lucky Gobindram: Yeah, manage, you have them, you're there's a there's four or five of them that are activity.
Gene Feldman: Yeah.
Dan Meeks: Yeah, but but they're they're like Gene said, they're after the fact. They're not from the manufacturer themselves saying here here's how you flash the firmware on the on the device. I think you probably can though, but you y you get what I'm saying. It's it's not it's not software
Mike Vann: Yeah,
Dan Meeks: deployed by the company saying this is used with our hardware. you just simply don't get that.
Gene Feldman: Yeah, because I yeah, because I know even yeah, because Striver I know for a while had great success with their Walmart use case when they had at one point Walmart had like a million headsets and we all thought, yes, this is it. You know, and Striver developed a great ecosystem for them, but the cost to develop it and maintain it eventually I think really killed the project because it it just there was no way to manage at that level.
Damon: And it became a cost value proposition, which Walmart
Gene Feldman: So Yeah.
Damon: always manages downward. Because they have to. That's that's what Walmart is. Not a slam
Gene Feldman: absolutely.
Damon: against Walmart, it's just the way the finances work out.
Gene Feldman: Absolutely. I mean and C P G companies right now I think are all taking kind of a hit as people are this gonna guess a different topic, but as people are shopping elsewhere. So but that's neither here nor there.
Damon: Yeah. So it sounds like you guys, Ash, lucky sounds like you guys started out in like construction and sales training and and things were the the sole proprietorship type areas where the the people had much more control over their destiny. Is that right? Did I did I get catch that right?
Ash Gobindram: Absolutely, Damon. We're definitely targeting, you know, mid-sized businesses. So a lot of times where we're interacting with, you know, the the actual decision maker directly and they don't they don't
Damon: Okay.
Ash Gobindram: have three levels of approvals. And you know, it it's definitely significantly easier to get things like this deployed in that level of organization. But we we've done deployments for, you know, larger companies as well. You know, it's definitely more entailed, it's definitely more clunky. but you know, for example, Richmond is a longstanding customer of ours. We've built a couple of spatial solutions for them. but you know, it's definitely a lot a lot more involved of a process, you know, with some of our mid-sized customers, you know, we can get things moving, get bills, you know, pushed out in a matter of, you know, twenty-four hours. That's, you know, significantly nicer than having to deal with, you know, that multi-tiered structure without a doubt. I mean and I mean just to add back to what Gene was saying, I think that, you know, Meta kind of having a multitude of strategies all at the same time and like, you know, maybe not being fully dedicated to some of them, like, you know, with their own device management tools, which they they've basically said they're gonna end of life by twenty thirty right now and there'll be no more active development on it. I think that, you know, if they work closer with an Arbor XR, perhaps you start to end up with tools that, you know are actually doing the job that they need to do. so that's a hope of mine. You know, I know that they are working more closely with Arbor XR at this point. So hopefully we're starting to see, you know, better tools for these kinds of fleet management.
Lucky Gobindram: I the other thing to point out is like you have VMware that's leaning into Workspace One on the enterprise side. You have Intune that's leaning in on the enterprise side. They've now started releasing tools for spatial device management. So you have some of the bigger big dogs that are actually in enterprises that are doing device management, paying attention, right? It may not be at the the depth that any of us want, but they're they're certainly paying attention to enterprise,
Damon: But they're still there. Yeah.
Lucky Gobindram: right? To make it make it more more delightful for the people that are already managing IT there, right? And tools that they're familiar with. So while Arbor XR is there trying to be like, we'll sell you the device, we'll brand them for you, we'll ship them, we'll manage and do all of them. And they're getting traction, they are, right? But they're definitely
Damon: Right.
Lucky Gobindram: like Pico, right? And they're betting on the the the Swan or whatever they're calling it, right? But
Gene Feldman: Mm-hmm.
Lucky Gobindram: like if you're looking at the other side where these guys are deploying A VPs, well they're not not scale but i some some level within the enterprise or they're they're using other headsets, meta or or similar, they're they're they're getting away with it and they're doing it with these these enterprise tools.
Damon: So if anybody from Arbor is listening out there, hit us up. We'd love to have you on the show.
Lucky Gobindram: Yeah.
Damon: Shameless plug.
Mike Vann: What do we what do we think
Gene Feldman: Absolutely.
Mike Vann: about I mean I'm I'm gonna say it. We talk about it every once in a while, but some of the glasses that are coming. So, you know, X Real and what they're doing. I mean it's not a headset. It's not the same experience, but is this gonna
Damon: Good point.
Mike Vann: be a place to maybe start to cross over a little bit into some kind of hybrid in between where some of these experiences at some level can come in on glasses and that becomes more approachable for some of the corporate clients. I mean, I don't for certain industries you need the you need the headset and for certain job, you know, training you need to be in the environment. But in other cases, especially some of the softer skill stuff like sales and other things, glasses might be the answer.
Ash Gobindram: Yeah. I mean, I think that if they're able to package, you know, true six stuff tracking in you know, that that's when the it starts to like kind of tip across, right? I think. So as much as it's like basically a heads up display on your face, you know, it definitely has some value. whether it can kind of do the same things that a mixed reality headset can do today or an AR headset, I think you really need like, you know, miniaturized six stuff tracking to be magical, you know.
Mike Vann: It's gonna take some time.
Ash Gobindram: We've thought Yeah, we've thought about dabbling
Damon: Yeah, not there yet.
Ash Gobindram: like CRM type stuff on like meta display glasses and you know, that could be cool, but it's not really like, you know, a game changer per se in our minds.
Mike Vann: think for certain things, right? So if you talk about scenario based training or personas and things like that, I mean, you know, if you don't really need this heavy environment, then there might be some opportunity there. But like you said, it it's hard. Once you cross that line, then you're going in different directions. So but I think I think you guys are doing the right thing. You watch what you know what's happening with the performance of the technology and if there are opportunities to evolve what you're doing But still kinda in the same DNA of where you started, then you have to pay attention to those.
Ash Gobindram: For sure. I mean, we've we've been paying attention to the snap specs for years, you know, and you know, it's cool, but it's definitely it's definitely not as smooth of experience as you would like, right? You know, it is
Mike Vann: Yeah, yeah.
Ash Gobindram: our true AR glasses, like it does do six DOF tracking, if you will, but it's clunky, it's a little bit laggy, and you know, it's not it's not a saucy experience just yet. But maybe, you know, two or three models down the line, they'll kind of be in that place.
Gene Feldman: All right. So so far, great conversation, Ash. Thank you so much for joining. really was excited to really get a chance to talk with you. I know I've had a friendship with you in Lucky for years, and I've gotten to pick your brain. And I think it was actually fantastic to be able to share this with our audiences. But one of the questions we always like to kind of leave with is a final protocol. So a piece of advice or a trend that you're seeing that maybe somebody that's new to the field could really benefit from hearing.
Ash Gobindram: Sure. I mean, you know, less so on the actual the actual what's affecting our customers directly, but more so behind the scenes and like how the sausage is made. I think that, you know, a year ago there was a lot of talk of like agentic programming and agentic development and you know, it was mixed results. But I
Gene Feldman: Mm-hmm.
Ash Gobindram: think over the last, you know, six to eight months we've seen, you know, some of these tools really become valuable in our workflows. And, you know, it's not like you could just vibe code yourself to something meaningful. I mean, you might get a nice prototype, but, you know, in the right structure, you know, kind of leveraging those tools, I think that that's a real game changer for, you know, any engineering org out there today. And it's very real. And the sooner you're kind of experimenting and using those agentic programming tools and learning, you know, what workflows work for you and, you know, how to keep your quality up whilst using those tools, I think that's super meaningful, Gene.
Gene Feldman: Awesome. Thank you so much. Well, guys, it is that time. So we're gonna go ahead and end our episode. Thank you all for listening. please feel free to like, share, and follow our pages. It will help. as well as we will have links to can Americ for Ash and Lucky. so please seriously check out their website. Even their website's a whole lot of fun. It adds some old interactive elements to the old to when internet sites were first born. So I'm not gonna let I'm not gonna destroy the fun of discovery, but seriously check it out. I'm a lifelong training and development professional. And so I've really been following what you guys have been doing. It has always kind of been in the back pocket of could I ever use this? Right now it's kind of. Iffy, but you know what I mean. Anyways, so guys,
Ash Gobindram: Yeah.
Gene Feldman: thank you guys for joining. and we will talk to everybody soon.
Ash Gobindram: Thanks guys. It's been fun being here.
Damon: Thanks, Gene.
Ash Gobindram: Sure. Thanks for having me, Gene, and everybody else. so yeah, I'm I'm Ashko Bindrum. I've been building technology for, you know, the better part of the last twenty five years since, you know, I was a teenager. and about two years ago Lucky and I started Kinemeric. we really saw an opportunity, you know, with the maturity of L LMs at that point to kind of serve as an underlying engine for believable synthetic human interactions, especially in a spatial application. so we started building Kin American at that point. And today we really, you know, see ourselves living at the intersection of AI and spatial computing and how we can use those technologies to positively affect the way corporate trading and learning is done you know, today.
Gene Feldman: So when you get into like how do you positively affect it, what are you seeing that AI is able to bring to the table that is a little different than I guess the standard training model? Because I think that's the question a lot of people are gonna have that usually as a trainer, that's what I always get. How is this going to be better than instructor learning?
Ash Gobindram: Well, I think it's really about kind of harnessing what the the good things about instructor learning are, but giving it an opportunity to scale, right? I think that a lot of corporate training and learning departments try to do a good amount of role playing and a good amount of one-to-one instruction where possible. But really that's often hard to scale, in, you know, your typical corporate environment. So if we can teach our synthetic humans to behave like real trainers and provide that one to one level of, you know, care and interaction for their trainees, then we find that there's really a a positive result and, you know, a good net effect for the organization as well.
Gene Feldman: Nice. And I like you're using synthetic human beings. Sorry, I'm catching I caught that like twice now because everybody usually uses avatar. It's avatar. You know, I I we all fell under, you know, James Cameron's spell or something. so so what is what is the synthetic human? I mean, I guess how are you looking at to explain it like that? Because I ru I'm really curious.
Ash Gobindram: Yeah, I think for me, like the dichotomy is that, you know, growing up playing a lot of video games and, you know, thinking about what a a an avatar has, you know, come to mean, you know, through video games and, you know, even through social media over the years, you really have a an operator behind them or you have a very limited amount of interactivity, with the, you know, the the NPCs, if you will, or you know In a social media context, an avatar is usually kind of just a a representation of an actual human. So for us, we're, you know, creating characters and embodiments of, you know, values or lessons within a a a a digital human, but you know, it's it's kind of autonomous in a lot of ways, right? There's no human that's really driving it on a day-to-day basis behind it. It's able to answer your questions, it's able to interact with you. you know, all on its own based on, you know, its training and, you know, our kinemeric orchestration layer. So that's
Gene Feldman: No, I like
Ash Gobindram: yeah. That's kind of how I see the dichotomy in my mind, Gene.
Dan Meeks: I I got a question about that.
Gene Feldman: No absolutely. Yeah, go ahead, Dan.
Dan Meeks: so one of the tragedies of being a human is that we learn so many things and then we die.
Gene Feldman: Way to sum up the life experience
Damon: Wow, Dan.
Gene Feldman: right there, man.
Dan Meeks: I mean, but but hey, so my question to you, Ash, is and and I wish Mark would hop on, because there there's a difference between having consistent training. but when you train people, you want to have the best instructors possible. So not only like when I used to teach, not only did my students get better, but I got better at my craft because I had to figure out new ways of explaining the material over and over again. So you have these synthetic humans, you you don't use the term avatar. Is that the case where they improve on each cycle, to where, you know, they they get better at their craft and hopefully don't die.
Ash Gobindram: Sure. So I mean, that's definitely, you know, part of the vision. I wouldn't say our synthetic humans are doing that just yet, Dan. but that's definitely part of the vision. What we are really focused on right now is the ability to really know your core material. obviously whether the synthetic human is taking the role of an instructor or like a colleague for a believable like role play kind of interaction. where there's a lot more variability and you're not really trying to achieve this this apex level of information. you know, is a little bit different in use cases. So really it's about, you know, creating a believable enough persona where, you know, they can explain the same subject matter that matters, you know, to the user in N amount of ways and really meet that user where they are while still maintaining a believable persona personality or persona. but they're not They're not self improving just yet. And, you know, that's definitely something we're working on and thinking about.
Mike Vann: So I yeah, I had a follow on to that one. So Ash, are you able to like ingest a company's methodology, their proprietary way of thinking about right? Like I mean, they've been training in a lot of cases for a long period of time. You know, these companies have been doing this, and now you're able to bring intelligence to that and bring it into an immersive, you know, high touch virtual experience. So are you able to pull in methodology, even like use cases that are, you know, more recent, right? the ability to update. Can you do all of those things?
Ash Gobindram: Absolutely. So that's exactly what we're doing, Mike. So w what we do typically during an implementation is we do like a deep download and like fact finding, you know, kind of phase upfront and really learn like what's unique about that organization, how they're approaching the problems that they have, and how they solve those problems. And then we work hard to, you know, kind of transcend that into a curriculum that's easily ingestable, you know, by our agents and you know. Basically, it leans a lot on our kinemeric orchestration layer, which lives on top of the LLM. but yeah, that's exactly what we're doing. And as we progress, we're starting to create tools where, you know, the the core curriculum is really kind of broken down into something that's accessible via a web panel. So, you know, if a procedure or a policy is changing you know, on the fly, you don't need, you know, an engineer or kinemeric to necessarily update for you. you know, you can basically affect your agents through, you know, a web application that's able to, you know, kind of ingest those updates.
Mike Vann: I mean, I could see how that could be super powerful, right? I mean, if something happens in a company that is really critical, that everybody out that is in active training, you know, needs exposure to, the ability to update that one month and and have it out in front of people quickly is very different from the old way of of training a workforce, right? Yeah.
Ash Gobindram: Absolutely. And like with the underlying LLM and our orchestration layer, you know, it takes that core information and, you know, like I was saying before meeting the trainee where they're at, you know, it's able to present that information in N amounts of ways, right? So really, you know, if there's a particular allegory or, you know, some s abstraction of that that makes it easier for that trainee, you know, they can have a one-on-one freeform conversation with the agent and be like, you know, can you explain that to me a little bit differently? Or, you know, how how would you say this happens in this case? And, you know, really they're able to answer on their toes pretty effectively.
Gene Feldman: No, and I think you hit a key point, at least, you know, when you get into training, everybody talks about the assessment piece of it. You know, being able to track that progress throughout it. So as you're getting into this, you're also kind of leading into an assessment piece. And I think one of the ways your software and your solution really is great. It's removing multiple choice questions from the assessment piece of the training. You know, I by you saying the open dialogue, one of the things that I've experienced as as being in training and development majority of my career is multiple choice questions. A lot of times people feel there's setups, you know, because you know, especially when you're doing scenarios, what I would choose is not one of those four options. And I think having that open dialogue, and I guess wh my my question is, are you seeing the assessment piece of it? People are people responding to this better than not only the instruction, but also the assess the assessment piece of it.
Ash Gobindram: Certainly. I think because, you know, on every single session that we have we're we're ingesting all of the audio and running full analysis on all of the audio. and you know, we're we're Providing deep insights based upon how the the actual genesis of the conversation has gone and you know, your mastery of the information. So typically where you're, you know, we're used to assessments of like, okay, I got an eighty-five percent on that
Gene Feldman: Mm-hmm.
Ash Gobindram: or an eighty-nine percent on that, you know, you're really missing that dimension of like granularity on your mastery of the material. And, you know, through the gift of that LLMs and AI, you know, is, you know, we're able to actually provide, you know, very involved, deep, you know, analyses of how they how they've mastered their material, which I think really resonates with the trainees because they see what they said. they see suggestions of how they could have presented it better or where they fell short. And, you know, it's directly what came out of their mouths. And I think that, you know, that really hits them close. So yeah, we definitely see a positive, you know, a positive effect on the trainees with our analytics tools. And, you know, besides like the fact that multiple choice questions are kind of like, you know, they're tricking you, they they guide you as well, right? You know, if you have
Gene Feldman: Mm-hmm. absolutely.
Ash Gobindram: four answers in front of you, it's pretty easy to kind of, you know, pull the right answer out of the bunch. But, you know, if you're, you know, presented with a a case or you know, a scenario and you really need to answer that effectively and you don't have a a multiple choice, you know, cheat sheet, if you will, in front of you, you know, it definitely makes you strive a little bit more. And we think that matters. But we do do multiple choice also. But, you know, like
Gene Feldman: absolutely. Well, yeah, but but I I think people don't realize like in when you're taught how to write multiple choice tests, you're told to write two questions, two answers are obviously wrong, and two are cleverly disguised, you know, of it could be one or the other. And people love using the word not or not
Mike Vann: Yeah.
Gene Feldman: using the word not. So you start getting really mixed, it can really confuse a learner. So I'm always really curious on that approach to it. And I know Ron, I cut you off, so I apologize. I will so please
Ron: No total no no problem.
Gene Feldman: go ahead.
Ron: Sure. so Ash, what kind of metrics do you have about how much faster people learn with your approach versus instructor-led approaches and other technology enabled products?
Ash Gobindram: Sure. So I mean, you know, the the one the one deployment that, you know, is really public right now and we have a good amount of data on, you know, we've been running we've been running this deployment for upwards of a year now, Ron. And, you know, it's basically an application of the technology to distributed field sales teams. And what we've seen there is that typically, you know, it used to be, I think, six weeks before a sales rep actually closed their first deal. And, you know, on top of that, they were burning, you know, a ton of actual leads in, you know, getting out there and finding that experience in addition to, you know, the instructor led guidance that they had. What we see now is that these new trainees actually can close their first deals in week two. So we we've reduced their their time to actually closing their first deal by close to 200% at this point.
Ron: Interesting. And what's the is there any difference in terms of how well a person understands the subject matter with your approach versus others?
Ash Gobindram: Absolutely, because because they can, you know, spend as much time with the the agent or the synthetic human as they'd like, you know, they really are able to ask questions and you know slow down the instructor, if you will, so that they can understand the material. thoroughly where you know in a typical kind of tri corporate training learning environment there's a lot of you know social factors that hold you back right people you know don't want to be the guy who's asking every question or slowing down the class. Really with this kind of a solution we remove you know all of all of those stressors on the situation. So we do see a significantly greater level of mastery in the actual subject matter. And you know that goes all the way from the trainees to You know, even actual leadership who's now partaking in the in the training, you know, will hear anecdotally like, well, I'd never thought about it like that before, or I'd never presented it like that before. so even they are finding value in the solution right now, right?
Ron: So so do you have any metrics around the ROI of your approach versus self training, instructor led training, and other technology enabled training?
Ash Gobindram: Sure. I mean, I could say, you know, I could say at least like, you know, per trainee, we're seeing, you know, in the deployment I just spoke about, for example, you know, we're seeing at least ten to twelve thousand dollars annually in savings per trainee right now. And that basically goes through, you know, amortization of instructor time that's no longer applied to them, as well as savings in leads generated and burned that they were previously going out there and, you know, practicing on, if you will. So that that is quickly scaled to, you know, hundreds of thousands of dollars in savings annually at their organization. but they're they're not the biggest company, right? They're they're a mid-sized construction company out of the Midwest. So, you know, if you take the principle and you extrapolate it to a larger sales organization, this, you know, this could quickly grow to be millions of dollars in savings annually for for an organization.
Ron: So then what would the ROI be when they invest in your stuff and your methodology with these savings they're achieving?
Ash Gobindram: Yeah, so I mean I think that, you know, the return in investment and like, you know, the math the math is kind of, you know, right there. You know, so like basically if you're looking at like, you know, two hundred thousand dollars annually in savings, that's just like your real like, you know, your real your real like fiscal number. But then the actual strength and, you know, ability of your sales team and their mastery of the material and their ability to, you know, actually sell that much more. when they're out there, you know, you would tack that on as well. So I could
Ron: Right.
Ash Gobindram: say this this could, you know, the return on investment could be, you know, 10X annually.
Ron: So it could be like within a month. within a month or ahead of the game.
Ash Gobindram: yeah, for sure. I mean it it definitely varies from organization to organization, but you know getting back your your investment money within a month is definitely plausible in this scenario.
Mike Vann: I mean you're you're impacting speed to delivery of training as well, right, Ash? I mean, once you get there, it's not like sending trainers out around the country. I it's you have some efficiencies right there and the ability I mean, sales is a great place to be operating because you're you're dealing directly with the revenue. So if you can make an impact there, it seems like a good spot to be.
Ash Gobindram: Absolutely. And I mean we're seeing yeah, go ahead, Ron, sorry.
Ron: So yeah, so what are the what are the main challenges to success?
Ash Gobindram: I mean, I would say, you know, there's still as much as I'd like there not to be, you know, we're really, really committed to spatial computing. So I mean, I think there's still inherent aversion to spatial computing at a lot of organizations and really getting them to commit to, you know, hardware and understanding the value, you know, that that a spatial computing device really has. that That's often a challenge till today, Ron. you know, and I'd I'd like to see that change a little bit quicker. but that's definitely still a significant challenge. Lucky and I still haven't committed to doing like a mobile or a tablet deployment and we're really resistant to doing so, even though we get asked that question all the time. just because we believe that, you know, when you're really immersed in, you know, in the solution and you have a full blown, you know, 3D synthetic human in front of you. Either in mixed reality or full blown virtual reality, that's where you're getting maximal value. but a lot of people are like, you know, we don't want to listen to that. You know, how how can we get this on an iPhone? so we haven't we haven't kind of acquiesced those requests up to this point right now, and we we very well may never, but it's definitely a major deterrent in a lot of conversations till today.
Ron: So then you need to have a bit of a different reference. If you say spatial computing, it does have that you know pause with people. But when I say immersive learning, I would think that would trigger some curiosity about what you mean by that and how do you you know deliver on that? And so you have to have the headsets and things like that. But as these tech companies bring up these newer devices with like you know, projection capabilities and other forms of hardware, then there's more ways to experience immersive learning. So I wonder if I should be a way
Ash Gobindram: For sure. Like, you know, like holographic
Ron: of approaching it.
Ash Gobindram: holographic displays are super cool. I think that, you know, there's still a lot of mac lack of maturity on that front. I mean, the looking glass guys are doing really nice stuff out of Brooklyn, but you know, anything bigger than their eight or ten inch model is a pretty hefty price tag in its own. so we definitely use like Different kinds of, you know, terms like immersive learning. but really once you start to get down to the nuts and bolts, you know, people quickly realize you're talking about a virtual reality headset or, you know, an AR-based headset. so we've gotten we've gotten some pretty impressive organizations to, you know, get into it, you know, and and start to buy headsets and start to adopt. But even then internally, you know, there's always resistance. You know, even if they see the vision in one particular unit and they can they can kind of present the facts and the benefits, you know, getting by in beyond that that pod is, you know, it's often difficult. So
Gene Feldman: As well as well as I can speak from personal experience of leadership changes and the vision of that leader, you know, I mean, I was kind of a victim of that. So it's it really comes into that that piece as well, that, you know, trying to get that use case. Cause like one of the things that I found by doing the spatial doing the full VR headsets was the emotional connection that the learners were having. The uncanny valley was gone. Everything was gone and they were coming out just angry, upset, or you know, they because one one of the things that we tr that I found is that that truly creates that true to life experience. You know, I've always said that if you really want to see VR's true to life experience, go watch a video of somebody doing Richie's walk the plank. You know, you'll see emotional impact. And I think that's where, you know, the strength is. Unfortunately, we're at a kind of a rebuilding year with this whole. VR. but I still I but I think one of the things, because I also want to go back to your AI piece of this, because I like the blend of your AI. So in getting back into the AI and the synthetic humans, one of the things you said it can learn from itself. And I assume that it could have retention. Because one of the great things about learn learning avatar is that or synthetic humans that you keep coming back to it and they'll remember where you left off. It can grow with you. But and Syntheticum is a great way to to lower people's heckles, you know, and to calm people down. But how do you overcome that? It can learn from its, you know, it it can grow. It can, as you were saying, it's kind of it, it's just it you can have an open dialogue with it. I think people are gonna be worried about the guardrails of it. And I guess is is there any type of controls or is it true, is is your plan to truly have it kind of an open AI? How do you see that playing out?
Ash Gobindram: No, there's definitely guardrails, Jean. And so it's not, it's not actually self-improving just yet. That's that's definitely something we're working on, but we haven't commercialized that just yet. But in its incarnation today, there are definitely guardrails. Now the guardrails are definitely very wide. you know, we we try to give a lot of, you know, lateral ability to the agent to be able to respond on its feet to the user. but there are definitely guardrails. Like we don't want You know, we don't want the trainee and the agent having, you know, too much of a conversation about, you know, football or, you know, whatever it may be. So like depending on the use case, you know, like for example, in a sales use case, building rapport is typically part of any sort of sales ritual or the phases of it of a deal, right? So, you know, to the extent of building rapport, it it definitely does its job and it's able to play the role. And if you want to discuss you know, football or cars or kids or whatever it may be, it definitely delivers a highly believable exchange and, you know, a highly believable, you know, reality, you know, with whatever personality or persona or character that, you know, that synthetic human is at that point in time. But it's careful, you know, to try to pull the focus back to the objective at hand within, you know, the the right kind of, you know, timeframe, right? So, you know, if it's
Dan Meeks: yeah.
Ash Gobindram: basically a a sale, you know, like say, you know, you're a salesman and now you're in the house of somebody you're trying to sell windows to, for example, it will have that, you know, that building rapport phase with you. But, you know, before you realize it, like a real homeowner would, it'd be like, that's great, but can we talk about the windows now? You know, and it's careful to, you know, intelligently, you know, segue the conversation. so there are definitely Rails. but you know, it's definitely a a bit of an art as to, you know, how wide you set those rails and, you know, how you kind of orchestrate the synthetic human to be able to, you know, evolve the conversation back to the subject.
Gene Feldman: Nice. Now I I love seeing this.
Ron: Okay, so do you have anything you can show us of what you do?
Ash Gobindram: I can show you what I do. I don't I don't have I don't have a demo ready for you right now on the fly, but I can definitely get you a demo around.
Gene Feldman: And and for those of those that are listening since we're only audio, we will have links for all the websites that you can go to. for can me canmeric.
Ash Gobindram: In America.
Gene Feldman: Thank you for canmeric. I've known the name for years and I still have trouble. But for Kimmeric, which the website has a lot of the great a lot of the great examples that they're talking about.
Ash Gobindram: And I'll we'll try to get you some videos of some some stuff that's not published just yet, some more recent stuff. So we've really been going deep on, you know, a lot of like instructor-led, like we're gonna train you on entire basics of roofing or the entire basics of insulation. And actually, we're starting an engagement right now where we're actually gonna apply the technology to an academic institution. So it's gonna basically work in concert with a teacher. for seventh grade, you know, anatomy classes where, you know, basically they'll have their lesson in class, and then they'll be able to take a headset home from the from the school and then actually like kind of like a a TA, if you will. the synthetic human will be able to, you know, hit those lessons home further, be able to have conversations with you, explain stuff about you know the the human anatomy, pull up corollary, you know, materials and diagrams. so We don't don't have any videos that we could show on that front just yet, but I can definitely get you some stuff on the former stuff with, you know, these synthetic humans teaching roofing or teaching insulation. you know, that would be cool.
Gene Feldman: That's absolutely awesome. So are you so as you're getting into roofing, but have you no have you identified like there's there's these key like skills that you've kind of found that to be universal that are are like hits for everybody? Or is it or are you finding like like if I were to ask like what are the top five sales skills? Cause I would assume negotiation and some of the other things. And you know, so I guess what what are you hearing
Ash Gobindram: Absolutely. Like for sales there's definitely
Gene Feldman: that there are universal skills across the landscape?
Ash Gobindram: I mean, so I think like you you like you kind of said there, Gene, I think that depending
Gene Feldman: Ha.
Ash Gobindram: on the arena you're playing in, like there's some things that just transcend between organizations really well. Like, you know, if you're in a sales kind of cycle, like, you know, understanding how to build rapport, how to surface objections, you know, how to start to early early on in, you know, the sale, acclimate the acclimate the buyer with the idea of the price, right? those things kind of transcend across sales org to sales org. But I think that depending on the subject matter you're kind of applying the synthetic humans to, you know, there's definitely some specifics within each discipline.
Gene Feldman: Yes.
Mike Vann: Hey hey Ash, quest quick question. I know things have really evolved over the last couple of years, but you know, when you're doing these kind of training experiences, especially in, you know, fully immersive, how how are you handling, you know, body language and sounds and I mean I know vo you know voices are getting better, but a lot of this, right, to get it to be kind of real life, you need some of those reactions and some of those human things, especially when you're talking about sales, you know, if someone's gonna be difficult and really press and kinda, you know, get ornery about an issue, like you wanna see that come across. So are you are you seeing that improve in in the synthetic humans and the tech that you're working with?
Ash Gobindram: Absolutely. So I mean, I think voices are really, really good. I mean, tone is tone is pretty good at this point as well. I think that, you know, a lot of that, you know, you can harness some pretty great like foundational models out there. you know, and basically integrate them into your your orchestration and get a really nice result. I think that, you know, animation continues to be something that we're working hard to refine on our end. There's not just a an easy solution for that. you know, and what's nice is that we find like, you know, Gene talk spoke about the uncanny valley a little while ago. We find that if you have a believable enough conversation and the voice is good enough and tone is really good enough, then some of the things that typically used to throw us into the uncanny valley start to rescind a little bit and you're not really in that spot anymore. And people kind of bite into the conversation and the exchange. But You know, I think that animation is definitely something that continues to be, you know, probably one of the most challenging areas we work on because meaningfully correlating the output of the synthetic human and what they're saying with, you know, the right, you know, sequence of animations or body language, that's definitely an ongoing challenge. So we're on like I think version three of our synthetic humans today, like from a a look and feel standpoint, and we're gonna continue to, you know, chalk out time for the team to continue to improve that. That's almost like, you know, an ongoing effort no matter what we do.
Mike Vann: And and it's right, it's it's it's exp it's an expensive prospect to try and get like there. So I imagine that, you know, especially learners, they may be a little more comfortable if they know this is not a a direct human, you know, a replication of a human, but rather a a synthetic a synthetic human, but if the voice and the sounds are really high quality, I think you're it feels like you're in a good spot.
Ash Gobindram: Absolutely. And like, you know, beyond the actual interaction with the synthetic human and their voice and their sound, you know, we try to, you know, lean on like our history of building VR and spatial based applications and do, you know, a really good job of like ambient sound design and environment design. so that, you know, you're closing just as many of those open loops in the user's mind as possible. but yeah, I mean like voice is definitely in a good place, tones in a good place, body language is certainly continuous work on it. Work you know, work work in progress, Mike.
Gene Feldman: Is
Damon: So business wise then considering the business planning side of this and market growth, aren't you limited then by the hardware that's available on the market and whatever happens to it sort of determines your destiny? If a whole segment
Ash Gobindram: I mean up to a point.
Damon: of headsets go away or the OS goes away but the headsets are just, you know, door stops, aren't you kind of sunk?
Ash Gobindram: Yeah, in some ways that's definitely, you know, like like I said, Damon, like, you know, up to this point we haven't acquiesced to the ability to deploy our solutions, although they're easily and readily deployable on your more traditional kinds of devices, like, you know, an iPhone, an iPad. you know, we we're big believers in spatial. So we're gonna continue to try to, you know, pull it as far and make it as big as we can, leveraging only spatial computing, but you know. I'd be lying if I said that it hasn't crossed our mind about, you know, doing deployments on on the iPhone or the iPad. so,
Damon: Yeah.
Ash Gobindram: you know, definitely years like this one. Like I think Gene said that it's a bit of a recalibration year for devices in the in the industry. And we think that that's definitely very real. And, you know, it's definitely easy to get into your own personal trove disillusionment, if you will.
Damon: Yeah.
Ash Gobindram: But I mean, you know, you get a story like, you know, the I think today Road to VR upload VR did an in-depth an in-depth feature on the new meta phoenix headset, which seems to be, you know, very real and you know, probably gonna roll out in Metaconnect. We'll see. so we're talking about a super lightweight headset with external battery and extreme external compute in in its puck, which is, you know, a little bit different than what we've seen Pico or Apple do with their devices. so we're talking about something that's gonna be super lightweight, potentially sub thousand dollars. And you know, that that maybe breathes more life back into, you know, where we're at with the headsets. I think there's definitely
Dan Meeks: It's
Ash Gobindram: been some Some sad news out of Apple's pocket over the last ten days. I think, you know, Mark German was reporting that, you know, they've laid off some members of the Vision OS gaming team, but I'm not really sure what the gaming team was doing. It hasn't been exactly a hotbed of gaming activity. you know. So but I I I think, you
Mike Vann: Yeah.
Damon: Yeah, yeah.
Ash Gobindram: know, as long as they're still committed to, you know, the platform, even if it's on a, you know, a three year device roadmap. you know, I'm still I'm still hopeful. I go back to the The fundas of the device, right? And like kind of what made me fall in love with spatial computing devices 10 years ago. And, you know, basically the core value props are you could bring anything in the world to you, or you could teleport yourself to, you know, anywhere, you know, either real or imaginary. And I think those value props are just still too valuable. you know, when I do spatial FaceTime calls, you know, I always am reminded by, you know, that very real power. Obviously, you know, the Vision Pro is heavy, it's very cost prohibitive. But if some of those variables can kind of be, you know, rejigged and I think there's some enough activity in the space that they will get there inevitably. you know, I think that doing a FaceTime call or doing a spatial FaceTime call, they're worlds apart, right? So like Lucky and I we grew up with you know, we were basically the the only ones in our family that grew up stateside, basically everybody else was in Asia. And, you know, we used to do weekly phone calls of our grandparents on Saturday mornings. And like I just think about like the sense of presence that, you know, a spatial FaceTime solution could have had in that scenario. Right. And it's just hard for me to believe that, you know, as long as there's enough work and we're able to get the devices to the economics and like the ergonomics that are necessary, that, you know, those value props suddenly you know, disappear or vanish. I think that they continue to endure and, you know, I'm I've got faith that the the industry will get there. So
Dan Meeks: Well, we we have a paradox
Gene Feldman: Yeah.
Dan Meeks: with XR hardware. In order to make a good XR headset, you need to get into gear of a giant institution that is very hungry. And once you produce this nice piece of hardware, you can't simply turn back to that institution and say, Well, my business has a privacy policy, my business has a data sovereignty policy. They don't like it when you do that. Or when you do that, they do like the Vario and charge thirty grand a headset. And I don't think you want to pay thirty grand a headset. So we have this horrible paradox dilemma, whatever you want to call it, when it comes to enterprise XR hardware. And you know, you mentioned Meta coming out with something. And yes, Meta's full of the the most talented and congenial people I've ever met. But when it comes to enterprise, they keep fumbling it. And they keep fumbling it because They can't really listen to what you're trying to do as a business and securing your data and keeping those conversations private and not giving any telemetry. And they simply cannot do it because of the institution that was necessary in order to bring that hardware into being. So yeah.
Gene Feldman: Yeah. But I also but I also
Ash Gobindram: I think that well, I was just
Gene Feldman: th I was gonna
Ash Gobindram: gonna say I I think that's part of it. And then I also think that the other part of it is really, you know, the the workforce like, you know, really getting charged up enough that they're demanding these things, right? You know, I remember fifteen years ago, you know, most most corporates had almost zero Mac Or, you know, zero Macintosh presence because there's there were no tools to manage the devices. There were security nightmares for the IT team because they just didn't understand the MacBook. And I think that there was enough demand from the workforce that these things have changed significantly over the last 15 years. You know, any major corporate today has PCs and Macs, you know, deployed like side by side. So I think that that's definitely part of it, Dan. I think the other part of it is that, you know, the the people at the organizations really demanding and saying, We need these tools. We see the value in them and they they change us for the better. I think that, you know, we need devices that instigate that kind of a reaction, you know, from the workers.
Gene Feldman: Yeah. But we also have to I'm gonna throw a third prong in there, is that this the admin software, because you said the enterprise tools, I will tell you, trying to integrate it for years without work Oculus for Workplace or Quest for Workplace, whatever they were calling it at whatever time, it it would never have taken off in the Enterprise because IT does not wanna own it without something to manage the software. You know, and to manage the headsets because I think for some of us that have had the pleasure of sideloading multiple headsets, you know, we're he we're done. We that's the last thing we want to do. You know. and so I think also too, I think one of the things that's hurt Meta and that I think also hurts a lot of companies, is that there isn't everybody's got these separate tools, but there isn't a at least till Samsung, or it's not Samsung, but Galaxy or not. Galaxy Android XR comes out. I've gone so many different devices. Android XR. But the thing is, is that until there's a management software that such as like what IT can use for Windows and Mac devices and iPhone and phones, that's really also going to be a major crux to it because nobody's going to want to own this.
Dan Meeks: Yeah, you y
Ash Gobindram: Right.
Dan Meeks: you have people that are trying to get in that well not get in but have been in the space like Arbor XR and I I there's a handful of others that I can't quite remember off the top of my head. But
Lucky Gobindram: Yeah, manage, you have them, you're there's a there's four or five of them that are activity.
Gene Feldman: Yeah.
Dan Meeks: Yeah, but but they're they're like Gene said, they're after the fact. They're not from the manufacturer themselves saying here here's how you flash the firmware on the on the device. I think you probably can though, but you y you get what I'm saying. It's it's not it's not software
Mike Vann: Yeah,
Dan Meeks: deployed by the company saying this is used with our hardware. you just simply don't get that.
Gene Feldman: Yeah, because I yeah, because I know even yeah, because Striver I know for a while had great success with their Walmart use case when they had at one point Walmart had like a million headsets and we all thought, yes, this is it. You know, and Striver developed a great ecosystem for them, but the cost to develop it and maintain it eventually I think really killed the project because it it just there was no way to manage at that level.
Damon: And it became a cost value proposition, which Walmart
Gene Feldman: So Yeah.
Damon: always manages downward. Because they have to. That's that's what Walmart is. Not a slam
Gene Feldman: absolutely.
Damon: against Walmart, it's just the way the finances work out.
Gene Feldman: Absolutely. I mean and C P G companies right now I think are all taking kind of a hit as people are this gonna guess a different topic, but as people are shopping elsewhere. So but that's neither here nor there.
Damon: Yeah. So it sounds like you guys, Ash, lucky sounds like you guys started out in like construction and sales training and and things were the the sole proprietorship type areas where the the people had much more control over their destiny. Is that right? Did I did I get catch that right?
Ash Gobindram: Absolutely, Damon. We're definitely targeting, you know, mid-sized businesses. So a lot of times where we're interacting with, you know, the the actual decision maker directly and they don't they don't
Damon: Okay.
Ash Gobindram: have three levels of approvals. And you know, it it's definitely significantly easier to get things like this deployed in that level of organization. But we we've done deployments for, you know, larger companies as well. You know, it's definitely more entailed, it's definitely more clunky. but you know, for example, Richmond is a longstanding customer of ours. We've built a couple of spatial solutions for them. but you know, it's definitely a lot a lot more involved of a process, you know, with some of our mid-sized customers, you know, we can get things moving, get bills, you know, pushed out in a matter of, you know, twenty-four hours. That's, you know, significantly nicer than having to deal with, you know, that multi-tiered structure without a doubt. I mean and I mean just to add back to what Gene was saying, I think that, you know, Meta kind of having a multitude of strategies all at the same time and like, you know, maybe not being fully dedicated to some of them, like, you know, with their own device management tools, which they they've basically said they're gonna end of life by twenty thirty right now and there'll be no more active development on it. I think that, you know, if they work closer with an Arbor XR, perhaps you start to end up with tools that, you know are actually doing the job that they need to do. so that's a hope of mine. You know, I know that they are working more closely with Arbor XR at this point. So hopefully we're starting to see, you know, better tools for these kinds of fleet management.
Lucky Gobindram: I the other thing to point out is like you have VMware that's leaning into Workspace One on the enterprise side. You have Intune that's leaning in on the enterprise side. They've now started releasing tools for spatial device management. So you have some of the bigger big dogs that are actually in enterprises that are doing device management, paying attention, right? It may not be at the the depth that any of us want, but they're they're certainly paying attention to enterprise,
Damon: But they're still there. Yeah.
Lucky Gobindram: right? To make it make it more more delightful for the people that are already managing IT there, right? And tools that they're familiar with. So while Arbor XR is there trying to be like, we'll sell you the device, we'll brand them for you, we'll ship them, we'll manage and do all of them. And they're getting traction, they are, right? But they're definitely
Damon: Right.
Lucky Gobindram: like Pico, right? And they're betting on the the the Swan or whatever they're calling it, right? But
Gene Feldman: Mm-hmm.
Lucky Gobindram: like if you're looking at the other side where these guys are deploying A VPs, well they're not not scale but i some some level within the enterprise or they're they're using other headsets, meta or or similar, they're they're they're getting away with it and they're doing it with these these enterprise tools.
Damon: So if anybody from Arbor is listening out there, hit us up. We'd love to have you on the show.
Lucky Gobindram: Yeah.
Damon: Shameless plug.
Mike Vann: What do we what do we think
Gene Feldman: Absolutely.
Mike Vann: about I mean I'm I'm gonna say it. We talk about it every once in a while, but some of the glasses that are coming. So, you know, X Real and what they're doing. I mean it's not a headset. It's not the same experience, but is this gonna
Damon: Good point.
Mike Vann: be a place to maybe start to cross over a little bit into some kind of hybrid in between where some of these experiences at some level can come in on glasses and that becomes more approachable for some of the corporate clients. I mean, I don't for certain industries you need the you need the headset and for certain job, you know, training you need to be in the environment. But in other cases, especially some of the softer skill stuff like sales and other things, glasses might be the answer.
Ash Gobindram: Yeah. I mean, I think that if they're able to package, you know, true six stuff tracking in you know, that that's when the it starts to like kind of tip across, right? I think. So as much as it's like basically a heads up display on your face, you know, it definitely has some value. whether it can kind of do the same things that a mixed reality headset can do today or an AR headset, I think you really need like, you know, miniaturized six stuff tracking to be magical, you know.
Mike Vann: It's gonna take some time.
Ash Gobindram: We've thought Yeah, we've thought about dabbling
Damon: Yeah, not there yet.
Ash Gobindram: like CRM type stuff on like meta display glasses and you know, that could be cool, but it's not really like, you know, a game changer per se in our minds.
Mike Vann: think for certain things, right? So if you talk about scenario based training or personas and things like that, I mean, you know, if you don't really need this heavy environment, then there might be some opportunity there. But like you said, it it's hard. Once you cross that line, then you're going in different directions. So but I think I think you guys are doing the right thing. You watch what you know what's happening with the performance of the technology and if there are opportunities to evolve what you're doing But still kinda in the same DNA of where you started, then you have to pay attention to those.
Ash Gobindram: For sure. I mean, we've we've been paying attention to the snap specs for years, you know, and you know, it's cool, but it's definitely it's definitely not as smooth of experience as you would like, right? You know, it is
Mike Vann: Yeah, yeah.
Ash Gobindram: our true AR glasses, like it does do six DOF tracking, if you will, but it's clunky, it's a little bit laggy, and you know, it's not it's not a saucy experience just yet. But maybe, you know, two or three models down the line, they'll kind of be in that place.
Gene Feldman: All right. So so far, great conversation, Ash. Thank you so much for joining. really was excited to really get a chance to talk with you. I know I've had a friendship with you in Lucky for years, and I've gotten to pick your brain. And I think it was actually fantastic to be able to share this with our audiences. But one of the questions we always like to kind of leave with is a final protocol. So a piece of advice or a trend that you're seeing that maybe somebody that's new to the field could really benefit from hearing.
Ash Gobindram: Sure. I mean, you know, less so on the actual the actual what's affecting our customers directly, but more so behind the scenes and like how the sausage is made. I think that, you know, a year ago there was a lot of talk of like agentic programming and agentic development and you know, it was mixed results. But I
Gene Feldman: Mm-hmm.
Ash Gobindram: think over the last, you know, six to eight months we've seen, you know, some of these tools really become valuable in our workflows. And, you know, it's not like you could just vibe code yourself to something meaningful. I mean, you might get a nice prototype, but, you know, in the right structure, you know, kind of leveraging those tools, I think that that's a real game changer for, you know, any engineering org out there today. And it's very real. And the sooner you're kind of experimenting and using those agentic programming tools and learning, you know, what workflows work for you and, you know, how to keep your quality up whilst using those tools, I think that's super meaningful, Gene.
Gene Feldman: Awesome. Thank you so much. Well, guys, it is that time. So we're gonna go ahead and end our episode. Thank you all for listening. please feel free to like, share, and follow our pages. It will help. as well as we will have links to can Americ for Ash and Lucky. so please seriously check out their website. Even their website's a whole lot of fun. It adds some old interactive elements to the old to when internet sites were first born. So I'm not gonna let I'm not gonna destroy the fun of discovery, but seriously check it out. I'm a lifelong training and development professional. And so I've really been following what you guys have been doing. It has always kind of been in the back pocket of could I ever use this? Right now it's kind of. Iffy, but you know what I mean. Anyways, so guys,
Ash Gobindram: Yeah.
Gene Feldman: thank you guys for joining. and we will talk to everybody soon.
Ash Gobindram: Thanks guys. It's been fun being here.
Damon: Thanks, Gene.
