Snap Mafia: Rajan Vaish, founder of Easel, on building at the intersection of social and Gen AI a...

We're back with another exciting episode of Snap Mafia this week with Rajan Vash. He's done some incredible things on the AR&VR side at snap, which we'll get into, but he's now the co founder and CEO of Easel, which is an AI powered app that lets users create scenes with AI, build avatars, and talk with friends directly within imessage. Rajan, we're super excited to have you here today. We would love to just jump right in and get into your background. You've done a ton of interesting stuff, starting from your bachelor's in computer science. You did a master's, a Ph.D. and then you've done a few cool things since then. So let's talk about that and just hear about your journey to where you are now with easl.

Thank you so much for inviting me, Daniel and James. It's been a pleasure. I've been following your podcast for a while now and really wanted to chat at some point. Yeah, so my, my journey has been quite interesting in the sense of like I I did my undergrad in India about 15 years ago and I joined Accenture Technology Labs to work on really like exciting researchy stuff. Like I was fascinated by the research side of computer science while working as an undergrad. However, with just like an undergrad degree, I felt very constrained by all the possibilities that I could engage in. So when I saw my colleagues writing patents, getting patents and publishing papers, I really got fascinated by that side of world and I got interested in a field called accessibility. Like in particular for me it was visually impaired folks. How can we enable them to use technology in any way they want? And so I started working on accessibility research and applied for PhD programs. This was like 2010 and then got into my PhD program in 2011. So I came to the U.S. i was very fascinated by this area and after working for a while in, in accessibility, I got into crowdsourcing. I almost felt that one way to solve the challenges of society is if we can allow people to mobilize in different ways and solve like hard problems. And my style of like crowdsourcing was not mechanical crowdsourcing, which is very common where you give like tasks to like folks and they do micro tasks like labeling images or kind of annotating data. What I was trying to work on was can we imagine a world where we can let people do complex tasks like academic level research, for example. And so I spent a lot of my time during my PhD working on mobilizing the citizen crowd to do very complex tasks. So I launched this project called Stanford Crowd Research Initiative where people around the world were allowed to do research. It was kind of like that era when MOOCs were very popular, Coursera, Udacity and like many of these platforms were prominent. Everybody was trying to teach different kind of courses. And I wondered like, okay, so we can scale education, we can scale teaching these courses. What about getting people to do actual research? And so this project was born. We basically we allowed anyone in the world to sign up for this. 1500 people signed up from all the continents except Antarctica with zero filters. Which means like they had, we never checked for like their research background. We never checked whether they are like computer science students or not. As long as they were interested in academic research, we let them in and we kind of created this experience for them where they could pick between three research projects. So there was a computer science within computer science. So there was data science, computer vision and human computer interaction projects led by professors at Stanford, Cornell and University of California. And these students were paired up with them and they started working on these, on different, different research projects. And the goal was how do we let them get this academic experience while a professor only spends the same amount of time as they would do with their single PhD student? So there was a lot of orchestration required to make that happen. And that was part of my research, like how do we organize these kind of like collaborative systems? And so a lot of students who worked on these projects, they wrote papers, they built the systems, they did research and they wrote. And a lot of these papers got published. In some scenarios we had 20 plus authors from these publications. Later when they were actually interested in grad school, we started writing them letter of recommendations to support them in their career mobility. The top student from one of the programs ended up going to MIT for his PhD program. Some students went to Stanford for master's, while some went to Berkeley, Cornell and other universities. So it was a very, it was a very interesting experience in terms of like getting, supporting career mobility while also answering the hard question of like can we get crowd or like can we get people around the world to do solve hard academic problems? And after that like as a follow up we launched like another project called Stanford Crowd Course where we wanted to get students to make videos because reading papers was quite boring for a lot of undergrads. And so can we make videos to educate them? And watch, watch, watch it in like a short format. Back then short format was 10 minutes, today the short format is 10 seconds. This was YouTube prime era. And so these students like created 10 minute long videos on different papers. So we, I was like very much in the mode of like academia and I was strongly considering becoming a faculty at a university after that. But interestingly one day I got an email from David Salson, who's the, who's like the head of research at snap. Because I had spoken to him in like at multiple occasions etc. And he was like, hey, like we just like set up this lab here, would you like to come or you know, interview us? And I was like, okay. So I came down to la, interviewed them and it was amazing for the first time. Met Bobby Murphy who was in the interview panel, had a lot of fun chatting with the team and a few days later I got an offer and I was like, okay, this is such a cool opportunity where the goal was to kind of think about the future, think about the future of communication. How will, how will people connect in the next, you know, in the next era when like technology is getting better. And so like I decided to move down to LA to join snap. So that's been like kind of like my quick journey until snap.

That's, that's awesome. That's an amazing journey I think for myself and for listeners, like going back a little bit. Like can you help distill down when you say, you know, you wanted to go into research and then you did research during your postdoctorate and then you came in and as part of the research group at snap, like what does that mean both in the academic setting and then like coming into a private, private revenue generating for profit company like snap. Like what does research mean in these different scenarios?

Yeah, on a very high level research is a process of like answering the unknowns or like there you don't know what the end output would be. So for example, let's say if you are building like an email system, right, like we know that like how emails are, how emails, how email systems are like built. We know the mechanics of it. There are no unknowns. The unknowns are, let's say once an email system has been built, how will people react? If there was a live component to emails, if you could see who's online, will that change the behavior of like how people respond to different people at different times? Now like from, from known we are, we switched to unknown, right? Like, and that's the, that's the research aspect there. The known was that for like, let's take the example of like standard crowd research initiative was the known was that yes, people will be interested in doing research, professors will be Interested in supporting students to do research. But how will we coordinate at scale where professors not gonna be spending more time than they would do with their single PhD student? All these unknowns is where research gets very exciting. Because now we're trying to uncover the unknowns and we don't know whether this will be successful or even not successful. It could be a complete failure. But the process of finding the answers to these questions requires research. And that's what I found very exciting. In the industry setup, the goals were different, but fundamentally also same. We knew that what matters is human connection. Friends want to stay in touch with each other. Friends are already enjoying expressing themselves with each other. On the smart glasses form factor, like using Snapchat, how will that translate on a new device that is unknown, Right? Like it is possible that people will not enjoy it. On smart, a different form factor, that's fine. But we need to study that. We need to build systems to understand that. And the whole process of discovery and query and inquiry is what research is all about. That got me excited.

Okay, thanks for walking through that. So anyway, so you were about to tell us about your experience at Snap before I interrupted you. So let's get back to that.

At Snap, I, for the first year I worked on several crowdsourcing projects, which was a very seamless transition into like my work thinking from like moderation stuff to content curation, to whether we can make new crowd based experiences on the main product. So they were like research projects. But right around that time, augmented reality was starting to become a bigger priority and it was just fascinating to see what was possible in terms of bringing people together using augmented reality. So I did one of my first project was called Blocks, which kind of was aimed at understanding the fundamentals of collaboration using ar. What I mean by that is when we are working in augmented reality, we often ask questions of what kind of multiplayer experience can we create with ar? Could it be co located? Are CO located experiences better or are remote experiences better? Are experiences that are tied to a geolocation better or independent better? Are synchronous experiences better or asynchronous experiences better? There are all these questions that are important when we are making design decisions when it comes to AR applications. I wanted to answer them once and for all, kind of. So we ran a very extensive study and we built a product around it called Blocks, where people could come and build Lego like structures together. And we learned a ton. And that influenced the rest of the kind of like my work on ar. A few years later, Snap launched a collaboration With Lego, with kind of, I believe like a lot of concepts that we learned through that project. And from that experience we started working on not just like phone as a form factor, but like glasses as a form factor. Like what could we do with like AR on smart glasses? Something that was very exciting to me with like smart glasses was that this form factor, the phone form factor is why we have Snapchats of today. Once we'll have smart glasses, what kind of new Snapchats will we see on that form factor? And like how will Snapchat evolve on that form factor? Especially when you have a camera that can see anytime, you have a screen that can project anytime, you have a computer that can sense anytime, and all of these things, all of these components are sitting right next to our most essential senses, like eyes, ears, mouth in a hands free format. I believe that it unlocks a whole lot of like, opportunities. Things that were not possible on phone will now be possible on glasses. So we ran, we built a lot of projects on spectacles and the smart glasses form factor.

And you know, I think from, you know, maybe I'm just kind of curious from maybe like the research community's point of view, you know, what is the perception of SNAP in terms of like, you know, how they push the boundaries and like sort of the innovation that took place there. Like when, when you told your friends at Stanford that you were going to snap, were they like, what are you doing moving down to la? Or they're like, no, I get it. Like, these guys are onto something.

People who are not familiar with Snapchat, they definitely were like, wait, why? Why are you doing that? I had to like actually show them like how Snapchat works and like how technology is embedded, you know, like what seems like fun, a fun experience. There's so much science going on behind, behind the scenes. Once they like acknowledged it and they like, they felt like there's a lot of tech there, it's not just like a picture sending messaging app. Like there's so much more to it. I think like for some it needed some education. For some who were already, let's say in like computer graphics field, right? Or computer vision field, I think they were more in tune with like what SNAP is doing because Snap, I think was publishing some papers. Like there were like researchers at snap, like we're publishing papers, so. Or had like collaboration with professors. But in general, like, I think Snap had a very, very positive perception that like, it's a very innovative company in the sense of, you know, the new formats that it had Shown to the world or introduced to the world. I think, like, people definitely appreciated that. Not everybody was aware because of the target demographic. Most of my friends, like, are professors. And, you know, so they. They were not like actual users of Snapchat, but at conferences I would go and, like, I would show them, and they were like, whoa, like, it can do this. One of the. One of the features that nobody talks about or, like, did not talk about, but created a lot of like, wow factor was snapmap. Actually. They were like, whoa, you can see this. Like, you can do that and you can see what's happening around the world. All of that experience created, created, like a lot of wow factor because everybody used to see lenses on ads and everything. They did not see the map. But, like, there's so much science and, like, research behind, like, the. The like, motivations behind, like, how people are gonna. Why people are gonna share content publicly on Snapchat. So there's. There's a lot of, like, positive perception. And we even wrote a paper in my second year, snap on, like, why people share publicly on Snapchat. Like, there was this feature called rstory, right? So why do people even share on our story? And what can motivate people to share more so that our SNAP map is more richer?

And I'm curious, like, that in particular the science and behavior behind why people are sharing on our story in snap. But does that research translate at all to other platforms? So obviously Facebook and reels, or Instagram and Reels, TikTok certainly, like, what can you. What are the cross learnings across those? And then where are there differences? Where, like, if you were at TikTok, your research might. Might differ.

Yeah, no, totally. Like, so we first, we. We drew inspiration from, like, other platforms first, like Reddit, Yelp. Why do people leave reviews on Yelp? What are they getting out of it? What is their motivation? Why are people writing. Spending time, like, writing articles on Wikipedia? What are they getting out of it? They don't have to. They're not like, you know, there's no monetary incentive, for example, when you write something on Wikipedia. But why are people even doing that? And it came down to a lot of, like, altruistic intrinsic and extrinsic motivations. Altruistic in the sense of, like, doing something good for the world. Intrinsic, just because it gives you a lot of joy to do that. And extrinsic was around some form of, like, benefit. For example, on Yelp, when people share their reviews, they get a specific, you know, they get invited to specific events and that was, that was exciting to them. And so a lot of these learnings we did share with like product design team at Snap and, you know, like, how we can incentivize people to do share more using altruistic, intrinsic and extrinsic motivations. And I think, like, fundamentally it translates to every platform. Like, there's a reason why people share on TikTok today. Because when you share on TikTok, like, there's definitely an intrinsic motivation because you enjoy posting on TikTok, but then there's extrinsic motivation that like, if you become famous there, then you can get brand deals, you can, you know, you can. Then you can like make more money. And so there's extrinsic motivation. But purely extrinsic motivation generally doesn't lead to like, sharing behavior because you cannot force someone to do something if they're not excited or interested in something. So there has to be an intrinsic desire. And that's why to a certain level, like gamification features fail on many platforms. Because that's why, like, for example, like Duolingo has. Why does gamification work on Duolingo so well? Because there's an intrinsic desire to learn a new language. And then extrinsic motivations of like, to allow you to track that helps you. So you're like, okay, I'm, you know, I've like finished like 50 days streak, etc. So that's like extrinsic motivation in play. But if somebody was not even intrinsically motivated, motivated to do that, no matter how many credits you'll give or like how many streaks kind of like you'll set, we cannot force someone to like, use Duolingo to learn a new language. So it's a combination of like, different motivations and how they play out. And I think, like, different platforms have different, different levels of. They, they kind of like pull these levers of like, different levels of motivation.

It's interesting, you know, I guess given that you were like in academia and then you went to Snap, you know, how did you end up deciding that you were gonna kind of jump ship and go fully on to now running easel? You know, that's like, definitely like, I feel like running a company is like just a whole different mind space than having kind of probably more of like a research mindset. So, yeah, I'd love to hear kind of how you got to that point and then obviously love for people to. If you can explain a little bit about easel and what you're building there.

Yeah, it is different, but also similar in many ways. So, so I've had like I, I have spent like 10 plus years in academia slash academic world so I'm very familiar with that world. I know the ins and outs of that in some ways and having worked at like industry research lab, I also know that world. So there was a motivation and interest in like trying something new that is going to challenge me and that's, that, that's something I don't have spent a lot of time working on. At the same time I think like Snap Research was a very special place. It was kind of like an incubator where we would build new products, we would ship something, we would test things, we would launch stuff. So it was kind of like we were working on different startup ideas pretty constantly. And so that brought a lot of joy. So I felt like if I continue doing this kind of work, it'll be a lot of fun. But at the same time, because I was so familiar with the academic world and I had experienced a larger company, I really wanted to try something that I have never tried before. But at the same time what interests me is discovering the unknown, solving like problems that you don't know the answers of and that you could do that in a startup environment. Like if you're working on hard problems where we don't know the, the answer. Like if it was, let's say, you know, if it was like let's, let's build like a, a books shopping platform, I don't think like it has that many unknowns because you know, they are like successful products in that space and you can learn and you can iterate but trying something apps like very different, very fresh requires that level of like inquiry that was like. So even when I was thinking of like doing a startup, I wanted to do a startup in a space that had similar level of like intellectual inquiry scope that, that will make me feel challenged and to solve the unknowns.

And so Rajan, what, what is EAZL?

Yeah, so EAZL is an AI first AI, first visual messaging experience that is built directly inside iMessage. What that means is instead of taking a picture, you are generating a picture of yourself with or off your friends and sending it on imessage. So since in the last decade there has been a successful product that has built a very complex social graph. And so we wanted to bypass that problem by building on imessage. But at the same time there were so many limitations with how people, you know, send pictures. They're, they're like not everybody. First of all, not everybody's comfortable sharing selfies. There's a big demographic of people who are shy or they're not comfortable. There's a barrier to entry when it comes to sharing selfies. How can we enable them to lower that barrier? The second aspect is when people are kind of like trying to express something, there's always like something that is in your mind like a mental image. How do you convey that? Not everything, again, can be conveyed with just a real picture. What I mean that is by that is, let's say you're like working late at night, you're tired and you know, you want to send the feeling of that you're, you know, you're burning midnight lamp and you're like, you know, everything is stressful. I don't think you can create a scenario in your room to send that. But with AI, you can finally unlock that kind of experience. That Rajin with messy hair, paper flying around, burning midnight lamp. And then you send that image of yours, that avatar of yours to your friends and you're like, okay, Rajen is really tired, he's working on a lot of things. So it really supercharges that form of expression. And then on top of that, when anybody sends these messages, even if they don't have easel installed, they can view it, but if they have easel installed, then they can tap to remix the same scene and they can see themselves in a similar scenario. It's not like a copy paste. The beauty of AI is that every generation is special, it's unique. So they can see themselves in a similar scenario, but like a different image. And then we have a multiplayer experience where friends can add each other and create scenes of themselves together or of just that particular person. And we are like very careful in terms of how do we create multiplayer experiences. Because the moment you give access to a friend to create a scene of yourself, they can do whatever, right? And having seen the history of how social experiences can be misused, we put a lot of thought into it. So number one, it's a key based approach. So the two parties first exchange keys to enable that like handshake moment. After that, any scene that a person creates, the other person has full visibility into what is being created. So you can keep seeing it on your easel. Like, okay, James is creating the scene of me. Okay, now he's doing that. Now he's doing that. So you have like full visibility over that. And finally we have a mutual deletion policy. So it's not that like a person can create a Scene of you or with you, screenshot and delete. Even after they delete, the other person has visibility into, like, what was deleted so that it cannot be misused. And of course, like, you know, folks can always revoke keys. So we kind of created this whole experience with user safety, user control in mind, because as AI is evolving, there are people who are bullish on AI, but there are people who are also skeptical about AI. So, like, the more comfort we can bring early on, I think it'll have a positive experience on users. So that's, in summary, that's easel. It's a visual form of expression that allows you to see yourself in any scenarios or experiences.

And for, you know, I think everyone's familiar with sort of AI, but not a lot of people have, like, developed their own models and, you know, have done kind of the level that you guys are doing. Like, how has that experience been? Like, where are we kind of, I guess in the, in sort of the cycle. I know that, like, kind of like the common refrain is like, it's the worst it's ever going to be, but, like, how has it evolved? Even in, like, the short amount of time you're working on easel and where do you see this going? Do you envision that at some point you're going to be pretty soon, a year from now? Are we making videos of me and Daniel? Where is this going to end up?

Yeah, I feel like technology is constantly improving. And as technology is improving, design decisions are changing constantly. Things that were not possible a year ago are finally possible in many sense. And I think things that we feel are harder, like we are not doing today, will be possible like a year later or maybe in six months. And the way we are building easel is we have a vision. We have a vision of how communication will be five to ten years from now. Let's say a world where people are able to express themselves in any way through capture or create meaning. Like you're on a walk and you know you're seeing. These are. These are like the North Star experiences that you like, kind of like see on in many demos. But the way I feel the world will function in terms of, like, communication is by bringing all of it together. You're on a walk, you see like a statue. You, like, capture that statue, send it to your friends in ar, or it's James's birthday, and so you kind of send Mickey Mouse shaped cake to James on his birthday because Mickey Mouse is his favorite cartoon character. How do we take that? Because the technology for that does not exist and neither does user behavior. User behavior around anything. AR is still very much phase based. How do we take what is possible today while latching onto an existing user behavior is how we are building this. And there is user behavior around this. 83% US teens are on imessage. It's America's largest social network. There's 250 million Bitmojis are sent every single day. There's a user behavior on that. And so how do we latch onto an existing user behavior to create this experience is what we are excited about. But more importantly how we are, how we're leveraging technology is by constantly improving our models. And you're right like you know, maybe in a year like when the right now video takes a lot of time. All this video stuff that we see are very kind of like either edited or very very hand picked. All the like demo videos or trailers that we see today. I'm hoping that like in six months or a year it won't be the case. Things will still improve like still will improve and they'll be fast enough that you know right now static scenes but like in the future it won't be surprising to see videos of like of friends together in different scenarios.

Where are you guys as far as traction? Like how much have you raised? How big is the team? Where are you in the cycle of bringing user on and starting to develop some of those habits that you just talked about?

Yeah, so we raised like 2.65 last year from Unusual Ventures, F7 Ventures and Korazen Capital. These are folks ex meta execs, ex CEO of Match Group and founder of nextdoor and some Stanford professors as angels. Since then we have been constantly building. We are a small team five folks, some backend engineering help design and AI engineering. And we are just getting started. So we just had our TechCrunch article which was a launching point for us. So we are very early in the process of user growth but we are just getting started in that direction.

And how has been the thesis around launching kind of solely for imessage so far? Is that starting to prove out? Do you feel like just like having to as you mentioned not have to build your own social graph is such a huge advantage.

Yeah, I mean I think one of the best advantages of one of the big unlocks has been to enable like remixing while you're like chatting with your friends. It's extremely powerful in a group chat setup when you're like when you have like multiple friends especially so you send like a message and we have seen like once you send, once one friend sends something, then others start remixing and then they with multiplayer, then they start adding others in the same scene. So let's say it's like I send you like hi from Hawaii. And then James remixes is hi from Hawaii. And then Daniel is like James and Daniel in the same scene saying hi from Hawaii. And so like everybody starts remixing. So one person's initiation almost like converts everybody else in the same group chat. That has been a good unlock for us whenever like we kind of like see this imessage experience and of course like it is, it enables almost like as you're like chatting, it kind of like allows for that seamless integration in the sense of if I want to say like hey, I'm like running late, I don't have to generate something somewhere else or like come to the imessage to just say like hey, running late. And like creating a scene of myself like running frantically. So while I'm chatting I can create that, send it to my friends and then they can think of like oh, thumbs up. Or like they do haha emoji, etc. So it kind of like blends pretty seamlessly there.

As a researcher, have you found anything even in this short period since launch that surprised you with how people are using it or adoption?

Yeah, I mean I, I thought like that a lot of like use cases will be around emojis, like how people want to say like normal things like you know, hi, bye, love you, etc. One of our users, she, she had like a really interesting insight. She said that EZL has made her more aware of her surroundings, her context as well as different events. So you know, things like MLK Day, she would really like not think too much about it but because you know, she got like a notification from easel that like, you know, reflecting on a pool in Washington D.C. et cetera. Like she was like, oh yeah, like you know, it's MLK Day. And so you know, gave her more presence in that, in that situation. Or she was like, oh, I'm eating pasta right now. And she's like like how will I show that to my friends? And so then she started like creating like different scenes of like her pasta eating experience. And she started like documenting her life in that, in that particular format. And so we are starting to see interesting use cases not just around expression, but expression or imagination, but also documentation and of like how your life is in AI kind of, kind of angle. And because of that like she's just more aware of her surroundings, the context she is in, and the different holidays and things like that. So that's been pretty interesting, I thought. Like, I was not thinking about it from that perspective, but it was a very interesting finding. On that note, a user behavior, like a user change that I've had, like, personally is I have become much more, like, I've been able to like, share more publicly, like, my images. I feel like the barrier is lower or if I'm watching a movie, I'm almost like always now trying to create a scene from a movie into like, what I'm trying to in AI. So if I'm watching Jurassic park, like, I'll create like a scene of me and my wife being chased by dinosaurs or like on. On 4th of May, you know, Star wars scene. And even like we were watching like this movie of like the, you know, shot in like, Australia, and I was like, oh, what would be like, you know, if we were in Australia? And so like, and just like, completely off topic, something that we have, like, observed is, this is totally anecdotal, but our son, who is 4 years old, like, he loves Easel. He's like, can I have like my mommy and daddy? Like, he keeps. He keeps giving me prompts of like, can you create a scene of mommy, daddy and like, surrounded by kangaroos? Or like, you're doing this, you're doing that. So it's just like a fun thing for him, like as a. As a playful experience. Something like it's not designed for, but just cool to see it playing these kind of roles.

Yeah, that's awesome. And I know it's hard to predict just given how fast all this technology is moving, but, like, where do you think Easel is, like two years from now? Or, like, where do you want it to be? Or are you just taking it one, one, you know, one sprint at a time?

Yeah, I mean, I feel like I want, as technology is evolving, I feel like the vision of Easel to be agnostic to the form factor formats and devices. Something that is not just like tied to, let's say, phones or in terms of format, maybe not just images or in terms of how people are interacting with it, maybe not just inside imessage. And so I see it evolving in all different kind of variations of how people interact and different formats and form factors people interact with while keeping everything tighter. So the vision should still stay same, but I see it evolving in different forms.

I believe this is awesome, Rajan. This is. This has been kind of a whole new realm, I think, for James and I kind of understanding the research side both from academia then kind of in SNAP and your journey to Easel. For folks listening, where can they learn more about Easel, where can they go download it and where can they follow some of the research you've done?

Yeah, they can go to easelapps AI to download it. It's E A S E L apps AI for my research they can go to my website rajan bash.com it's R A J A N V A I S h dot com. I have documented all of my research because it's all public. So we have papers and videos from different conferences. A lot of my work from SNAP is there as well that they can check out.

I think in doing research for this show I went through a lot of that. Didn't understand much of it but a lot of it's there. I can, I can test to that.

Yeah, we tried to make videos, like 30 second videos to kind of give a quick trailer into like what we were up to. Hopefully that was more helpful than reading like long papers.

Yeah, yeah. But Raja, thank you so much for joining us today. This has been a great conversation.

Thank you so much for inviting. I, I really enjoyed like answering these questions but like more importantly, I think conversations like these help me self reflect as well and allow me to actually think about these questions. Like a lot of questions are self reflective and makes me think about things that you don't think on a normal day basis because you're so lost in like the details. Like as part of my product designing process, I'm obsessed with product design these days so it's good to take a step back, see the big picture again and go back to work.

Well, thank you and everyone should go to eazl. What's the website again?

Easelapps AI.

We'll put that in the show notes, make sure people have that as well as access to your website and yeah, everyone should go download that.

All right, thank you so much.

All right, thanks.

Thanks man.

Appreciate it.