Hey, Marc. I just lost. There we are. I'm back. Hey. First of all, it's a pleasure to be here, and I look forward to spending the next 15-20 minutes with everybody here. Before I go into my presentation, I just want to dovetail off of some of Marc's opening comments because I think they're really worth repeating. One of his comments was about being, we're the first inning of AI. It is early, he's right, but it's very clear it's happening. I've been in this business for about 4. 5 years as the CEO of BrainChip, and the maturity of the conversations, the maturity of the customers, the use cases that are coming are radically different. It's an undeniable trend. It's happening, but it is early. There is a lot of room to grow in this market. The second point I want to reinforce is the power issue that he talked about. It won't go away, and there's some talk in here about data center, and you'll hear from at least a couple of edge companies why certain workloads make more sense and help that dissipate that power issue. There was some commentary about how important this was versus the internet, what's called revolution. I believe this is the biggest thing that's happened in the economy ever, more than agriculture, industrial, internet. This is the productivity tool that is going to change the world in so many ways. This is something that I don't think any investor or anybody, any business wants to sit on the sidelines about. My last thing I want to comment on before I go into my slides is you talked about some of the older chips. In the end, AI is requiring specialized silicon to make it run better. When you talked about NVIDIA or any other company, it's a matter of getting the right kind of silicon for the right workload. When it comes down to a company like us, we'll talk about how we really tune it up for the right workload. With that, could I go to the first slide, please? I always think it's important to start with an understanding of the market. We talk about the AI market, and I just commented about it, about the fast growth rate, but there's some really imperative things that are driving workloads out of the data center. I think everybody here is familiar with data center, thinking about ChatGPT or Claude. There's a whole bunch of AI that happens outside of the data center. It's called physical AI or edge AI. These are some of the markets that we serve right here. It's not everything. You can see these are very large markets growing very rapidly. Our symbol of our company, we're right in the middle of that and can address that. I've got some interesting use cases to bring to life a little bit later on in the presentation. It always starts with cool technology, but you got to make sure you have a big market to grow into. Reinforce some of the other comments. Every industry is going there. The kind of industries we serve is so many right now, oil and gas, medicals, defense, wearables, right down the line. Every industry is trying to AI-ify their products. And then, of course, one of the driving factors for edge or physical AI is the ability to do it to alleviate concerns about latency or data privacy, in which course you need a long battery life, back to the power issue. Next slide, please. So just a little bit about our company. I won't make this technical because our time is brief. What makes us unique is Marc said earlier, we are the first in the world to commercialize neuromorphic. Many people think of this as maybe a little more scientific, but no, we've mainstreamed it. It's fully digital. It's portable to any fab in the world. We've got an extensive tool chain, model zoo, et cetera. So we're the first to commercialize this in many form factors, and I'll talk about that in a moment. As investors, you always should be thinking about what you're investing in. We have an incredibly strong patent portfolio. This is a company of mostly scientists and engineers from the best universities in the world, that we're always advancing the science. We're tracking the model trends and staying ahead of that with the right kind of silicon designs. Our patent portfolio protects that from any kind of penetration from other competitors. We have incredible customer choice. We have a variety of chips, modules, IP packages for those companies that want to build their own. Marc made a comment about royalties. We have a licensing business as well as a chip business. So you can consume, depending on the maturity of the business, which way you consume our technology. Plug and play on the right-hand middle box. I think it's so critical when you're striving for breakthrough performance that you can make it easy to adopt. Great technology is great, but if it's hard, it won't be adopted. We put a lot of energy into making this plug and play and very easy to adopt. I talked a moment ago about power and latency, so I'll move quickly to the right on hybrid computing. A lot of the kind of things we talk about in edge computing tend to be discreet, but we've also got an exciting bunch of work going on around hybrid computing, where you take an NPU, which is neural processing unit by us called Akida, and you can work with CPUs and GPUs and distribute that workload to hybrid computing. Basically, what I like to say is the right tool for the right job. So that makes us unique as a provider of AI edge technology. Next slide, please. I'm not going to walk through these options here. I just want to be as brief as possible. But what I want to show here is what I mentioned earlier. We have a whole plethora of options for people to consume our technology. This is part of a multi-year strategy we've had as a company to ensure that we can expand the offering and make it easy to support. When I joined this company, we had a single level of IP. As we exit this calendar year, we will have four for people to choose the right IP for their job. There was no hardware. We have chips that are available. There was no modules. There was no reference designs. We sell all of those today. In addition, again, we're supported by the world's best tool chain to make it easy to support and put models onto the hardware, because if people are buying accelerating hardware, they want to put models on there in a very simple way. The message here simply is a lot of offerings, part of a comprehensive multi-year strategy that's coming together with a market at the right time right now. Next slide, please. I mentioned some of the things. I'm going to give you just three or four examples of how you can use this technology before I bring it to a close with some Q&A. If you notice, I'm not going to go into a lot of technical stuff, which we can, and back up our claims about lowest power in the industry and things like that, but I just want to bring it to life with some use cases. First is this is one what we call hybrid computing, and I mentioned it a moment ago. This is some breakthrough work we're doing with IBM, and many of you have read, if you follow us at all, with some work from a gentleman, Kevin Johnson, who has pioneered this work. It basically allows Akida, which is our piece of silicon, to work with GPUs and CPUs, depending on the work that gets put on via IBM Spectrum Symphony onto our accelerator, and other work that gets put onto other kinds of silicon. What that allows you to do is address more and complex use cases that we had previously done in the past. More use cases, more pieces of silicon, the more revenue. Next slide, please. Another very interesting use case, and I just picked a few, I could have picked a lot to illustrate the versatility of this technology, is in the defense industry. The defense industry has changed forever. It has gone from kind of fixed, heavy kind of defense tools to things about mobility, so drones, robots, command modules on soldiers' backs and things like that. You can only do that kind of stuff with edge AI technologies by companies like BrainChip. Here is one we do with ultra-low radar processing. If you think about radar, before it was dominated by fixed-position, heavy things, and it could only identify if something was coming, not necessarily what it was. We've done some breakthrough work with the U.S. Air Force Research Laboratory and Raytheon and developed a set of algorithms that say, yes, something is coming in a very portable form factor, and we can tell you whether it's something friendly or not friendly. So great value add, but a really good example of a use case and a really good example of working with some industry leaders, which we are having great traction with many defense companies right now. Next slide, please. Onsor Technologies. This is a company in the wearable space, and I'm showing these to show the versatility of our offering. This is a company out of the Middle East that's developing epileptic prediction glasses. It has a little sensor on the temple, and when somebody's about to have a seizure, within one hour, they put out an EEG signal. We have a chip on that sensor, and it says with 98% accuracy that they're going to have a seizure, which opens up somebody's life. They can now drive a car. Maybe they can get medical attention quicker. a very powerful, changing people's life. The next slide, please. Frontgrade Gaisler, one of our licensees. I chose this to illustrate one of our example of a license. They have taken a license from us. They will be taping out their silicon later this year for the harshest environment in the world, to put it into space. Space where they can go out. You cannot afford latency. You're going to send something up for a long time. You got to have ultra-low power. You got to have accuracy in your models. They've created a chip with our technology to service the space industry. That's just a wonderful example of the versatility of our technology. The next slide, please. To bring this to a close, where I really want to get into the questions part, because I think that tends to be even more interesting, is I'm going to start with the middle box. You heard Mark's comments, you heard mine. There is very strong industry trends about emerging not only AI markets, but the edge market. On the left side, BrainChip is the most mature leading edge AI company with the broadest offerings, IP, silicon, models, tool chains, commercial traction. When you go to the right side, we're having strategic traction with some very, very important customers in this world. You're seeing them in some of the examples, and there's others that we have as well, and we are expecting even more in the coming years and months. With that, I look forward to taking some questions with my few remaining minutes. Thanks, Sean. We do have a number of questions that have come through, so we'll jump straight into it. Where possible, I've sort of grouped questions together where it seems obvious that they're along the same line. Received a question around BrainChip's progress towards commercialization. What are the clearest milestones investors should watch over the next 12 months to assess whether customer engagement is converting into meaningful commercial adoption? Yeah, I think the most direct one, of course, is bookings. We are expecting really solid bookings for the foreseeable future, so I think I would look directly at our bookings. We are doing investor relations updates on a quarterly basis, and we are starting to disclose more and more information about our pipeline, that people can examine that. I would also encourage, because I know many investors only look at the ASX for information, I would encourage our investors to look at all the tools that BrainChip use, because we are very active on social media channels, X, LinkedIn, and others. Our website, our PR. We are putting stuff out every single week. So I think between bookings, if you look at our quarterly IR update, where you'll get visibility into our pipeline and all the news, I think you'll get the idea for the traction. A question here about customer journey. What does the process look like from a customer first evaluating Akida through to commercial deployment, and where are your most advanced customers currently sitting in that process? Sure. There's really two answers to that question. It's very comprehensive. Depending if they're going to go a silicon journey or an IP journey. In order to be an IP acquirer, you've got to be a relatively large company with a large budget because buying a license from us is several hundred thousand upwards in price and in royalties, but building a chip is several million dollars. Those companies, typically, their buyer journey is they will buy chips first, which we have. They will try some models to make sure they work. They might buy, let's say, 100 chips or 500 chips to make some modules and get some market testing, and if that all goes well, then they would go ahead and take a license and design their chip. So that's their journey. Smaller companies or ones without the budget, the wherewithal, will buy chips or modules, and they'll kind of plug them into their existing products. That second one is quicker in the journey, and one of the reasons why we have so many offerings is we want to address both those markets, bigger customers, smaller customers, and also the smaller customers can go quick. I think the second part of that question is where are they in the journey? On the IP journey, we've got several customers because I mentioned earlier, when I joined this company, we had a single level IP. We have four right now. A lot of them are in the early to later stages ones that we introduced lately, one of which is called Akida Pico, which is a very interesting offering for us. We've got customers that are evaluating it very carefully, going through their diligence, and once they decide, then they'll go through an acquisition cycle. On the chips, we have many chip companies, some of which we have announced, some of which we have not announced. They are taking products, trying the models, and trying them at the market. A question here, a very specific question, so hopefully it's not too specific. The Onsor Technologies product for predicting epilepsy or epileptic events, the user case you showed was glasses. Are you looking at other sort of wearables or other methods to use the same technology beyond glasses? Absolutely. The beauty of our technology, it was designed to be horizontal in nature, and one of the reasons I gave four examples of a variety of use cases within individual, let's call it verticals like wearables for those glasses, which would be under wearables. We can address many other kind of use cases, whether that's audio or EEG signals for the heart. Yes, we are talking to many companies about all those use cases and wearables. So it's very versatile, very horizontal enabling technology that could enable virtually any industry. There's several questions here about your business model. You offer IP, silicon development kits, and reference platforms. Which of these do you expect to make the largest contribution to revenue over time? It depends on the timeline because over time, we envision that the IP will go, but that takes years to build because we have licensees now, we have others that are looking as they tape out the royalties. The royalty business model is beautiful because the royalties are virtually 100% margin, so at some point, we anticipate that being a very large percent of the revenue. The other major part will be around chip/modules, right? The reference designs are more to sell for people to get ideas and modify off of. The two revenue streams are really IP, let's call it IP/royalties, which is one bucket, and then the chip modules together. We think they'll be roughly the same over a period of time. There's a question here, and because I don't know the background, I'm not going to try and get myself into trouble, but it's more around, I assume it's pipeline and revenue opportunity and not necessarily hitting those targets. Are you disappointed that in some cases, potential customers in that pipeline aren't commercializing quick enough? My job is never to be patient on anything, so I wouldn't use the word disappointed. You got to remember, when you're selling the kind of technology we are, we're enabling people's revenue stream or, in the defense industry, people's lives. It is not a quick decision. Whether you're going to be doing a set of wearables glasses, which for a company like Onsor Technologies is their revenue stream, they're going to take their time in making these decisions. This is just the nature when you have a very enabling business-to-business, B2B business. These evaluations take time, but when they get in, they stay there, they stick and they pay. They continue to pay and buy more volume, or they pay royalties. Question here in relation to the relationship with IBM. You touched on in your presentation, is that something you're working with them in a formal sense? We're not allowed to talk about things that we have signed NDAs with between companies, but the promise of that technology is very good or those use cases. I really can't comment specifically on what we're doing or not doing with them, but we're very excited about that use case. We're excited about the idea of just orchestration layers in general, but IBM is the one we think is very interesting right now, but we anticipate there'll be others as well. Last few. Another question relates to competition. Many semiconductor companies now describe their technology as a lower power edge AI solution. What can Akida do that conventional CPUs, GPUs, and all competing edge processors cannot do as efficiently? Yeah. I'll try to answer that in a very untechnical way, but I want listeners to listen to this carefully. Virtually the entire industry, since many of us were born, has done compute the same way with something called the von Neumann architecture or just matrix multiplication, a bunch of zeros and ones, whether that's AI or just general CPU or GPU stuff. Neuromorphic or event-based is different. We break that paradigm, and basically at its simplest level, when nothing is happening, let's call it a zero value in that zero one matrix, we don't compute. That alone allows you to knock off huge amounts of power. We do other things like putting the memory in, you'll hear from some companies later on, put a memory next to the compute. But doing it the way we do it, and doing it uniquely in the industry, is that it gives us pretty much an impenetrable kind of moat around that because the whole industry is locked on kind of a process and methodology that they did 40, 50, 60 years ago. We do it uniquely, and what I said earlier is very important. To break through that performance with kind of our event-based neuromorphic approach, but make it easy to adopt, that's what we've done here, and allow that to make it easy to adopt with our tool chain and offer many offering for people to consume. That's why we think we have absolutely a very strong and legitimate claim to be the lowest power in use cases. Final question. If we're speaking again in 12 months, which we hope to do, what progress would you want BrainChip to have demonstrated? Well, I think we've come a long way, right? I think what I expect the next 12 months is even more maturity on our offerings, one. I talk about our IP offering. Two, our module offerings. I would expect us to certainly have a much higher level of bookings than we have today. It's also not just the progress of the company, it's that market dynamic that Marc Kennis kicked us off with, which is the market is coming. We broaden our offerings and mature them even more. I think that's what we're expecting the bookings to happen between all that. I'm going to leave you with a statement from a shareholder, which sometimes when I do this, the CEOs get nervous, but bear with me. No questions, but just wanted to tell Sean personally, keep going with the good work. We appreciate you. Well, thank you. I really appreciate all of our shareholders. They have been incredibly loyal and we very appreciative of their support. Sean, thanks for joining us and taking us through BrainChip's progress. It's been a real honor. Thanks so much, David and Marc, and everybody who-