 Hi, my name is Chad and I'm the founder and CEO of Scantar. We in 2017 started with generating AR avatars and we're building the biggest library of AR avatars in the world, 110 of our IPs. And the problem in that case was that it takes a lot of time to animate 3D characters, you know, to get every emotion right. Because if you want to create a library, you want to capture each and every possibility that a 3D character needs to resemble. So that's the problem that we found in generating, you know, when we want to generate a lot of content from reality, there needs to be a smarter way. There needs to be a way where we're able to combine technologies like machine learning so that our production pipelines could be significantly reduced. And that's how we see in one space, one micro aspect of this is animation. When we're able to automate the entire animation process and reduce those production timelines, I think that would be a really interesting solution for the market. So what we did was we took a 3D asset and we linked that 3D asset to the multiple different animations that we have. Now, the 3D asset is able to be linked to those animations based on voice command. So the user says, hey, I'm really happy today. It chooses the relevant animation through our network or our model. And through that process, it's able to identify the right animation, right blend shapes, which are expressions and a 3D model in that case and also link it to the relevant environment. And give an output in that case, which is completely in sync with what the user is trying to say. And that's how we see a very interesting mix of how machine learning is integrated on to the automated animation space. And that's how we are specifically leveraging it and we think that the use cases go way beyond AR. It has huge use cases for the animation industry and also content generation in VR as well. We see now that automated animation has already generated a lot of interest and it's really exciting of what could be the use cases for it. One of the use cases that we see right now is AR avatars. And every big ecosystem has their own AR avatars where you can customize and create your own stuff. And our objective is we can make all of those ecosystems and all of those avatars intelligent. Now these avatars are being leveraged as a medium of communication and augmented reality is a natural tool for it. Now let me give you an example of how this could work. You're at your home and you say, hey Alexa, tell John I'm gonna reach at 7.30pm. I'm sorry I'm late. Hey Alexa, tell John I am gonna reach at 7.30pm. I am sorry I am late. John receives this message. It could be either through a smartphone notification within an iMessage or a WhatsApp or whosoever we're able to integrate with or it could be through a smart device. Once John receives this message, avatar pops out and says, hey I'm sorry I'm gonna reach at 7.30pm. I'm sorry I'm late. I am gonna reach at 7.30pm. I am sorry I am late. Now this AR avatars depicts exactly what the user is supposed to say and depict the right emotion. Now this entire process allows the avatar to animate itself based on the voicing course and that gives us liberty to integrate across ecosystems. So we're able to integrate with smart speakers, messenger applications, smartphone manufacturers and also smart glasses manufacturers because we've seen that as also a prospective medium of communication. So there are immense possibilities of how we could leverage this. I've been involved with augmented and virtual reality for the past few years now. I even started Tesla's ARVR group. I'm excited to join SCANTA because of our vision and our direction. At SCANTA we're using artificial intelligence to automate the animation of our 3D characters called picamojis. Picamojis are 3D spatial characters that allow people to add new, fun and interesting things to their conversations with their friends around the world using augmented and virtual reality. The technology behind animating these 3D characters has massive potential. It has the potential of saving filmmakers and animators literally billions of dollars through our platform. There's a few challenges that we're going to be facing over the coming years as we build this platform. One is going to be selecting and building out the right deep learning models. Next is going to be creating and optimizing our pipeline. And finally the biggest one of all is going to be data. Finding the right type of data and enough of it to create compelling animations. I'm looking forward to the coming years as we build out our world-class team to create this incredible product.