Episode 50
SPEAKER_04: 0:00
What we've seen is that for many countries, the idea that we simply use AI given to us by some Californian company or of course by a Chinese business may not be what the country wants.
SPEAKER_01: 0:14
We're legacy and we're old school. What it means is that they've built the technology in such a way, one, it's pre-assembled in Iraq. I mean, we've tried to assemble an NVIDIA Iraq and it's requires a Harvard MBA, let me put it this way, and an MIT degree with it to get that done.
SPEAKER_03: 0:30
Thinking more of the MIT degree. Because usually we just read about it and talk about it.
SPEAKER_00: 0:34
And to build a financial model, do we really build financial models? My job is to make these gentlemen successful. Okay, if I do a good job with that, they're gonna come back and buy more systems from me. It's not about me putting my brand front and center.
SPEAKER_03: 0:52
Welcome to the Spark of Ages podcast. In this episode, we're on the critical mission of how to build sovereign AI. That's right, sovereign AI. And we're speaking with the founders of Southern Cross AI, or STX.ai. We're gonna call it STX from now on, who are building their company in Australia to secure that nation's data future with help from a friend of our show. This conversation is about the foundational architecture that defines the AI-powered economy. So here's my guest. I got David Keene. David served as the founder and CEO of Southern Cross AI at Inference as a service platform dedicated to establishing sovereign, scalable, and cost-efficient AI infrastructure tailored for Australian requirements. Previously, David led Big Ten Can as CEO managing director for over 14 years. So a fellow founder who stuck with it, David is an alumnus of Macari Graduate School Macquarie? We'll get there.
SPEAKER_04: 1:52
We'll work on it. I'm gonna get you an Australian accent, Rajay, before we finish this.
SPEAKER_03: 1:56
Macquari? I thought I got it. Macquari.
SPEAKER_04: 1:58
Macquari.
SPEAKER_03: 2:00
Macquarie Data Graduate School of Management. I listened to it on YouTube and I guess I didn't do it, right? Okay. Akash Agraval. Akash serves as the chief strategy officer and co-founder of Southern Cross AI. He's been on the show before. He founded and led AI and various AI and security companies. He previously was SVP at SAP, where he led the IoT application security business. Akash holds an MBA from Harvard Business School. Then there's my great friend Abi Inglay, who I've known for over 20 years. Abi serves as the chief product and strategy officer at Samba Nova Systems. Before joining Samba Nova, he was a member of the executive team at Qualtrics. Prior to Qualtrics, Abi spent over 17 years at ATT serving as senior vice president and business leader of multiple multi-billion dollar businesses. Abi also holds an MBA from Harvard Business School. So, gentlemen, welcome to the Spark of Ages.
SPEAKER_00: 2:53
Thank you. Thank you for having us. Thank you.
SPEAKER_03: 2:56
Well, we're really excited to have you. We're going to talk a lot about this really interesting concept. Everybody knows AI is what you get with ChatGBT or Claude or they talk about various AI infrastructure vendors. But David Akash, could you explain what Southern Cross AI or SCX is about and how it fits into the AI ecosystem? Why'd you start this firm?
SPEAKER_04: 3:19
What a great way to start. So, yes, first of all, I'm the one with the strangest accent on this call. So you're going to have to bear with that. That's going to be a challenge for the viewers out there to see how they can understand this crazy Australian accent. But I think, Rajiv, it's such an interesting time in technology overall. You know, it doesn't take a rocket scientist to understand the impact that AI is going to have on our society and of course our economy, but on the lives of every human being. And in fact, many people would say that we're already halfway there. If you think about how people use AI today as everything from their tool they use to help them draft an email or a note to their boss looking for a pay rise, right through to many people, particularly young people, using an AI as almost their personal advisor to guide them down some of life's biggest decisions. You know, AI is already having a big impact on the lives of many of us. But when you think about that deeply, what you start to realize, of course, is that whilst the world is amazing and many of us have so many things in common, there are also differences in the world. Countries and cultures and environments can be different. And what we've seen is that for many countries, the idea that we simply use AI given to us by some Californian company or, of course, by a Chinese business may not be what the country wants. It might be if AI is going to have such an impact on the lives of everybody. And I'll just speak here about Australia for a minute, every Australian. You know, we want to have some control in that. We want to know what's happening. We want to know what happens to our information. Is it processed in a particular way? Is it used in a particular way? And we want to have some influence over that. So SCX was launched with the goal in mind to build Australia's first sovereign AI cloud. And that means that we're delivering the outputs from what people now term an AI factory. It was a phrase I've I've heard a lot now. But basically a business that builds the capacity to then create the AI that is used by every citizen for business, for government use. And of course, amazing next generation AI builders that are creating the future through their tools. But do it in a way where it fits the Australian context, the Australian culture, the Australian version of English, and does that in a way that works for all. So, you know, we have seen this trend impact a lot of organizations and countries, and we're just so pleased to be able to bring that to Australia with the launch of scx.ai. And Akash, what's, you know, you've we've talked a lot about this. Akash is someone who brings tremendous value to the team and I think brings that Silicon Valley native experience as well. And, you know, whilst it's easy sitting in Silicon Valley to think about and understand what AI does, but you know, when Akash was with me in Australia just recently, you realize that not everyone in the world has that depth of knowledge yet, right, Akash?
SPEAKER_01: 6:09
Yeah, that's correct. So I think there's, you know, as David pointed out, with SCX, there's obviously one of the biggest differentiators is that we're partnering with company like Samba Nova. So we've gone all in and we're using next generation technology to bring what we call inference as a service. So, you know, layering on top of the sovereign capabilities that David defined, you know, part of being sovereign is being in the country, making sure the data doesn't leave the country's perimeter. You know, we're also making sure that we're bringing kind of a disruptive technology. We believe that ASICs technology that Samba Nova is based on is fundamental to inferencing. And, you know, we are an inferencing cloud. We're inferencing as a service. So we don't stop in Australia. We are providing inferencing across the world. So, you know, if you have an application and want to use inferencing, you can leverage the SEX service to do that.
SPEAKER_03: 7:03
So, like David, you talked about the notion of a sovereign data cloud. Is it kind of like what happened with GDPR, right? The European standard, where you want to have your data in the country? Or is it, you know, because the way AI works so closely with data, you want it super close to the customer and therefore you want to put it in Australia? Or is it even as Akash talks about it, is this is one location that's doing lower cost inference as a service, offering it internationally? Just help me understand it.
SPEAKER_04: 7:33
Yeah, look, I think it's really insightful that question you ask. So of course, we saw this happen in the history of computing many times when things often started in one country, particularly here in North America, and then things get distributed around the world. Often it was for latency issues, it was for cost issues in terms of backhaul. There were a lot of reasons why technology got distributed. And I'm sure Arby can give us some really great examples of how ATT solved that. But, you know, like there were those traditional challenges that you weren't distributed for those reasons. I think what's happening here is something that's slightly different. Those things still apply. But we're talking here about intelligence, guys. Intelligence. Every time I kind of say that, I think, well, what am I talking about? Intelligence. It's not intelligence. But for many businesses and organizations, it will be. And the idea that you can just outsource your intelligence overseas is a challenge for some countries, right? First thing. Having said that, our goal at SCX is to apply what I like to call unit economics. I love the phrase tokenomics, and I'm sure Abby can talk to us about that. But the the concept of look, if you can make this stuff in a way that delivers outputs with the performance and price that really works, you can sell it anywhere. So I think the answer is nuance for a Jeep. It's like, yes, sovereign kind of means sure where it is and what it is, what is this intelligence? How is it being done? And we'll talk about it today. But we also launched, as part of our program, was a unique version of one of the models, which we call Project Magpie. And we can challenge those on the podcast to send you a comment on Twitter, Rajiv, if they know what a magpie is. That's going to be a test. That's a test. It's a test. I'm not going to say what it is.
SPEAKER_03: 9:14
We can even make that as part of our game. We can add it to it.
SPEAKER_04: 9:16
Oh, we could. We could. I'm not going to give it away.
SPEAKER_01: 9:18
And no, you're not allowed to use AI to answer that question.
SPEAKER_04: 9:21
Uh-huh. It's right.
SPEAKER_01: 9:22
You'll get the answer very quickly. Yeah.
SPEAKER_03: 9:25
So you talk about Project Magpie. And go ahead and give us a quick brief because I have a whole bunch of questions for you.
SPEAKER_04: 9:30
Oh, yeah. So this is Australia's first, and I think one of the first in the world, of fine-tuned large language models where we've actually fine-tuned the reasoning side. So those of you, again, who go and use one of these AI models, sometimes you'll see it like thinking. People think of it as the inner monologue of an AI talking to itself. The term reasoning is the term that is often used in the industry to describe what it's doing, but it's processing some stuff before it goes and gives an answer. And I quite like the term inner monologue. It's like getting itself ready to answer in a particular way. So we've gone and fine-tuned the reasoning layer on a large language model to think like an Australian.
SPEAKER_03: 10:07
How would you think like an Australian? Does that mean like when I think of a beach, I should go to Bondi Beach? When I think of mountains, I should go to the Blue Mountains.
SPEAKER_04: 10:13
Is that I was going to say it involves beer but and cricket. Beer and cricket, I was going to say. But no, look, I think there's a lot to what it means to think like an Australian. We have to confront these issues because Australia, particularly, is a very diverse, very multicultural country with people from all over the world there. But there are a few things that make Australia Australia. The way people engage with each other, their approaches to life are slightly different. And yes, part of it is knowledge, so they know what Bondi Beach is, but part of it too is the way the culture and knowledge fit together. So our view was we've got a tremendous data set. Fine-tune the reasoning. Don't focus on the answer. The answer will take care of itself if you fine-tune the reasoning. And we're really pleased, and those out there on the podcast can visit chat.scx.ai. They can give Project Magpie a go, and they can see what it is like to think like an Australian. And we think that's the beginning of it because people want to feel that their AI understands them. They want to feel that way.
SPEAKER_03: 11:10
I can see it from the consumer context. But you said a lot of this is business and government as well. So what would those examples be?
SPEAKER_04: 11:18
Fine-tuned on the legal system, fine-tuned on the way the government works, fine-tuned on a tremendous amount of information that is appropriate for how Australians should do, not should, but do, do act. And I think that gives companies and governments the ability to implement AI faster with more confidence. And I think confidence is a big thing for some of these organizations that will help them to do it faster and better. So Magpie is proof that we can take data, we can fine-tune an outcome, and then we can run it on the high-performance inferencing machines that uh we get from San Vinova.
SPEAKER_03: 11:52
And let's talk about that. So this is a great answer. This is really helpful to understand. So as you talked about, there's a national need, there's an in-country need in Australia in specific, and then again around the world. So you're filling a critical gap in sovereign data infrastructure, right, in Australia. So what led your choice to partner with Sanbanova systems for the deployment of their low power, high throughput, ASIC architecture hardware, as well as their managed cloud platform?
SPEAKER_04: 12:19
It's a big decision because when you're building a business, you have to have typically something as fresh as this idea. You have to build something that's built to last. You have to have the partners in place that can scale with you. But you also have to have the fundamental business plan that works. And anybody out listening to this podcast who's built a business, you know how important that is. If you don't have a business plan that works, eventually it's going to catch up with you. The hype alone is not going to save you. You've got to build businesses that make money. And so I can share with with the with everyone, we we spent a significant amount of time talking to all of the folks that build the chips that create these AI outputs from big to small. We built what I believe are the most comprehensive financial models that talk about the early phases and the later phases of a business like this. And we looked at that with a view to making money, Rajib, which is really interesting because I think a lot of the time people haven't been as focused on making money. They've been more focused on burning cash and growth, right? Yeah. That's good. I'm not saying that's bad. We intend to grow. We intend to grow very aggressively. But you have to do it in a way that at least shows you can make money. And we put a lot of effort into building what I see as the most comprehensive business plan in the in the world for doing this. And we looked at all the providers. We just saw clearly in our analysis that Samba Nova was the partner that could deliver for us now, but also could continue to provide that benefit as we continue to scale the inferencing side of our business. And you know, that that was clear to us.
SPEAKER_03: 13:49
So let me ask Abi, I mean, Abhi, I know you've been working closely with Akash and David. You you guys have known each other for quite some time. So it's even helpful that prior to this, you guys have known each other, right? And then you came into this, and you're leading key parts of a top-notch firm in the area of AI hardware as well as software capabilities. So maybe talk about two things. One is you've done work in sovereign data AI infrastructures, and why you think the Soviet Nova platform is really viable for this kind of capability.
SPEAKER_00: 14:19
I'll talk a little bit about sovereign AI and why it's viable and then talk about our partnership with SCX as well. So, first, you know, building on what David said and what Akash was saying earlier, sovereign AI is all about reclaiming control and establishing context. And that's really what David was really telling you. It's not just about the control, it's about context. And you know, every time David, you said think like an Australian, that 80s song, think like an Egyptian, kind of went through my head, you know. But I try to I try to tune that out. But it's really control about the data, the models, and the systems that power them, and more importantly, the people who operate them. Okay, that is all very important. And we're seeing this shift towards sovereign infrastructure, where security is an afterthought, it's the foundation, but it's not about just security, which is sort of where GDPR sits. It's about context, it's about control, it's about who operates it. Because as David said, no country would ever outsource its entire power needs to somebody else. You would not actually rely on the mobile network of another country. That's where intelligence is at. You cannot have it somewhere else. And that's why we're super excited to work with David. And I'll tell you, working with SCX has made us actually stronger because I'll tell you the models that David has built and the scrutiny he put us to is probably the best workout that we've had for a while. And one of the things that works for them is unlike certain portions and certain countries in which power is at abundance, space at abundance, you know, perhaps the issues around global warming are not perhaps that intense, right? And money is in abundance, say the United States, for example, other markets do care about the energy efficiency deeply. They deeply care about the fact that even if it's they don't create the model, the open source models they're bringing, they have actually tuned the way David is doing with Project Magpy. And we're partnering, very proud to partner with him on that front. And then lastly, the people who operate it, why did he do it? Because he understands the context. He is talking to the banks on the ground. We can supply the energy infrastructure, we can supply the energy efficient shifts, we can apply the blindingly fast inference, we can provide the racks that allow him to shuffle models in a much smaller footprint, and we can fit into his existing data centers or in places they have no data centers, which is uniquely us. But at the end of the day, without the local understanding expertise that David brings, there is no win here. That's one of the reasons why I think sovereign AI is really a very strong partnership. Without David powering it, without David's brand on it, in a Southern Cross brand on it. The word Samba Nova might mean something in Paul Water in the United States. In Australia, it means nothing. And that's why we rely on them to take us to market.
SPEAKER_03: 16:57
That's amazing. So you're talking about the need for sovereign data or sovereign AI. You have the need for lower cost tokens per kilowatt. Maybe you want to just explain what that means, tokens per kilowatt?
SPEAKER_00: 17:08
So basically, that is a fundamental element of what Dave was talking about earlier. How does one make money? So if you think about it, all intelligence in this case is how efficiently can you convert electrons in to a such an intelligent out. And intelligence in this situation is measured in a form called tokens. Think of tokens roughly equivalent to words, like two-thirds of a word. Okay? They're gonna think roughly that way. The more efficiently you can generate them and the faster you can generate them, the more responsive the story is, the more responsive the responses, and how much you can actually get out of it. And that's what David was working on.
SPEAKER_03: 17:42
Yeah, and can you go in a little bit about the difference between training, which a lot of people do on NVIDIA-based architectures, versus the focus that you have at Salmanova, and David and Akash were both talking about the notion of inferencing as a service.
SPEAKER_00: 17:56
So training is also a spectrum. I talked about pre-training, which is when you build a certain foundational model. So ChatGPT, for example, where GPT is a foundational model, anthropic is a foundational model, Deep Seek, as you know, the big Chinese model, is a foundational model. When you first create the model, the initial training that happens requires hundreds of thousands of AI machines lashed together. That's when you actually create the model that allows you to be able to use in the future. The training is training. When it's actually used, that's inferencing. So when you type in a sentence, it completes, or you type in a query and it completes it. Or David puts it into GPT OSS, which is the open source model released by OpenAI, which he has now trained to think like an Australian. That is the use of inferencing, and that can work much more efficiently, anywhere between two to five times more energy efficient, and anywhere between four to nine times faster on Sabinova systems. But to be clear, we complement the Nvidia infrastructure which is required for training as well as for proprietary models.
SPEAKER_04: 18:59
I was going to say, Arby, it's a great example. I was going to add to that. So this project Magpie was fine-tuned on NVIDIA GPUs with support of NVIDIA, but run for inferencing on SAMO chips. So I'm sure the folks out there will understand that split. It's a really interesting split. If you get it right, that can be one of the ways they can power your business.
SPEAKER_03: 19:19
You can really nail the cost equation better, right? And so, Akash, maybe you can help me with this too. Like enterprise AI often fails, right? They're only 5% of custom pilots reach production. And it's typically due to tools lacking memory or failing to integrate deeply into existing workflows. So, how is SEX leveraging its vertical integration, deep domain expertise to overcome this critical pilot-to-production chasm for Australian enterprises?
SPEAKER_01: 19:43
A lot of it is based on cost as well. So people run these things, and when they realize that, you know, they've got to extend the same use for the entire enterprise and the cost will become cost prohibitive. You know, some of these things are put on brakes. Another reason why they're put on brakes is precisely this whole area of sovereign. You know, people don't want the intelligence. You know, you ask the company, where's the data going? You know, how are we training this model? Do we own this model? So a lot of people right now, you know, the early adopters, and this is what I wanted to talk about, have been sort of primarily Silicon Valley US-based companies. I've got a list of all the major people that are using tokens in a major way. And I've looked at them based on all the neo clouds out there. And if you look at one thing in common, you find most of the companies are venture-backed based in Silicon Valley. So they've understood and doing that. The mass adoption of AI has not really taken place in the enterprise. That is why you hear about these big numbers and big data centers being built, because people are anticipating that enterprises will start using that. A lot of enterprises are using it in pilot phases, and they are afraid of a few things. They're afraid of cost, they're afraid of data sovereignty, they're afraid of, you know, making sure that when they are training these models, that the knowledge of their company and their business is not going and being utilized by these models for the benefit of other companies. So that's where I think the the debate is out there about whether you should use a proprietary model or you should use an open source model that you fork and you train and to your own specific need, just like we did for you know, using OSS to create a project MagPi. You know, companies can do that. They can create their own version of MagPies. And so JP Morgan can have a model that's for general use within JP Morgan's employees for general intelligence, that's you know, very much investment banking centric, they're customer-centric with all of those kinds of vernaculars.
SPEAKER_03: 21:42
What you're saying here is like I can go with a closed model, like an open AI model, right? And I could run it on one of the different architectures. Like I could run it on Azure, or I think you can now run it on AWS Core Weave. If I'm building it for my business, I could also have an open source one, like a Deep Seek, and I could run it on a Salmonova, right? And then there's value to me because I can see the open source. Is there is there value to me in the training? Is value to me is the speed and the execution? Where's the value?
SPEAKER_01: 22:10
The value is in threefold. One, you can train that model specifically for your needs. So you can train the model, fine-tune the model, very similar to what David did. He took the open source version of OpenAI's model. OpenAI has released a couple of their models and made them open source. They're not their big models. And by the way, another thing that we're learning from enterprises, using OpenAI, their big model. Most of the things in that model are useless to a company. So why have that burden? So, one, you can use these open source models and think of them as forking them, sort of cutting them and saying, I only want a segment of this model and then I'll train it with my data. And then it will learn the context, it will learn my nuances and provide value to my customers or to my enterprise. So that's the benefit of doing that. So that's, I mean, that's a bigger debate, whether open source is going to win or whether these closed sources are, and what percentage of the market each will get. So look, it's pretty clear that they will coexist. You know, it's potentially maybe they'll get 50-50, maybe they'll be 70% closed and 30% open. What I've found, at least with enterprises, some of the enterprises don't know what can be done with open source models. So, for example, we're talking to one customer, they came back to us and said, We're going to use Mistral. And I said, Can you give me the use case and let me show you that same use case running on one of the open source models? What's the benefit of that to your question? One is you control it. Second, the cost.
SPEAKER_03: 23:32
You're not paying the intellectual property necessarily.
SPEAKER_01: 23:34
Yeah, well, you're not going back to where open AI is taking you or Mistral's taking you. They're not taking you to San Bonova. Let me tell you that right now. They're taking you to their cloud and to their own inferencing provider. And that is fundamentally going to be a challenge, right? Potentially, unless they're able to compete on the cost. And, you know, one of the things that Abe pointed out that's very, very important is one of the things that we are also benefiting from is that we can use technologies like Samba Nova in an existing data center. And that is very, very important to understand because, you know, there are a lot of data centers today that will get retrofitted to becoming relevant for AI. Some of them will not be able to be retrofitted because they require extreme power and cooling if you went with sort of the NVIDIA type approach. This is one of the big determinants for a company like us that, you know, we can get going and use, as David likes to say, a 2018 data center and start working in there. And that doesn't mean we're legacy and we're old school. What it means is that they've built the technology in such a way, one, it's pre-assembled in a rack. I mean, we've tried to assemble an NVIDIA rack and it's requires a Harvard MBA, let me put it this way, and an MIT degree with it to get that done.
SPEAKER_03: 24:54
Thinking more of the MIT degree. Because usually we just read about it and talk about it.
SPEAKER_04: 24:58
In to build a financial model. Do we really build financial models? Yeah, and actually, I'd love to hear what everyone's view is on this. But what I'm seeing too is two things. One is more and more, if you're building an AI company, you don't really care. And Abby can close his ears, but you don't really care what chip someone's built it on. You think all the viewers of this podcast, I'm sure, are out there with great ideas to build the next amazing AI solution, right? And I'm sure they're thinking, I'm going to use one of these AI models to power it, then I'm going to build the workflows and the structure all around it. They don't care which chip it's made on. They just don't care. What they care about is is it fast, is it reliable, and is it cost effective? They don't care what chip. Because most of them don't even know what chip it's built on, by the way. You don't know. You just need to have confidence, the right output from the right model with the right cost, the right reliability with the right performance. And I think that's what's coming in our market.
SPEAKER_03: 25:48
So basically, everyone's competing at every level. There's the chips, there's the models, there's how it's delivered, there's the data. Everyone's competing. It's like a many-to-many competitive model. It seems like there's one winner right now when you when you read about this, one winner area, but not necessarily so, right?
SPEAKER_04: 26:06
I'm old enough. I'll I'll put my hand up to remember the early days of the internet. And there was a little company out of the Bay Area called Cisco Systems that came along and pretty much for a number of years owned the build-out of the particularly routers, but switches and other kinds of devices as well. And they pretty much owned it. But eventually, the people who were buying the internet service don't know and don't care whether it's Cisco or Juniper or someone else building that infrastructure. What they want is the output of it. And we may see something like that happening here just faster. Rather than taking years for that to happen, it might happen a lot faster than it happened back then. And, you know, I think that's what I'm seeing from the customers we're talking to. Control, Kash use that we want control, they want management, they want security, they want confidence, they want unique outputs that are tuned to their way of working. But which chip it is is up to us as the provider to be able to build.
SPEAKER_03: 27:03
Let me poke on that a little bit. So I'm gonna, this is for everyone. The pace of AI innovation is accelerating globally, right? Like one of the things that Abi taught me about is how Deep Seek models are achieving highly competitive performance with far fewer resources. Like it was mind-blowing, especially this chain of reasoning capability. That means that time to market for new capabilities is a critical competitive differentiator. So now, if time is the ultimate scarcity in the AI race, where is your product roadmap focused to allow Australian AI native companies to consistently beat global competitors?
SPEAKER_04: 27:39
What a great one. I want to add even more complexity to your question before I answer it, which is think about the region around Australia. You've got Indonesia with 270 million people, you've got the Philippines, you've got Vietnam, you've got Thailand. These are developing nations with super smart people and an aggressive focus on building the quality of life for those people. And for a long time, they've struggled competing against developed nations like Australia, fully developed nations like Australia, because they didn't have access to all of the knowledge and all of the infrastructure to do that. I was at a meeting with the Asian Development Bank recently, and they're already getting applications for funding from developing nations for AI infrastructure. Because those nations believe that with AI, they take away, it narrows that, I won't say narrows, eliminates the gap that was holding their citizens back from achieving better lives. And so I think, Raji, for us, we have to recognize that across our whole region, there is competition for these capacities and the ability to move. So Australia needs to move faster. I think it's got some challenges. It hasn't been moving fast enough. I think there's a saying we use in Australia, we call it the lucky country, is what they call it inside Australia, because it has been lucky for the last, you know, hundred years, hundred plus years. Natural resources, small population, beautiful geographic area, all those lucky things. But, you know, now the world is competitive. We're taking away some of those barriers that have held back other nations. So I'm really intrigued. And I think it's important for Australia and I think other countries in the world to recognize that competitive nature.
SPEAKER_00: 29:12
I'll actually agree with David that the consumer of the product actually doesn't care what ship it is. I actually agree with him on just so you're aware. But as an inference provider, he surely cares. As Akash said before, if you actually had an infrastructure provider who could allow you to use an existing data center, which is one of the points that Akash focusing on, that's a big deal. You're avoiding a huge capex for upgrading those data centers. If you're in an area where there's not a data center, you could put things in a container, that's a big deal. 60% of the operating cost of an instance system after you spend the capex is energy. If somebody told you that a chip could provide it two to five times faster, a consumer like you might not care. But David and Akash, who are sharp minded business people, surely care. That's where we focus, and we are very aware. Of our role in the ecosystem. We're very comfortable with that role. Unlike some of our competitors who put their brand front and center, my job is to make these gentlemen successful. Okay, if I do a good job with that, they're going to come back and buy more systems for me. It's not about me putting my brand front and center. The second point about getting them to market quickly that David was talking about, everything Akash said is about actually getting them to market quicker. If you don't have to upgrade the infrastructure, guess what? I can stand them up. I do a fully managed service because it gets them to market in three to four months versus 18 to 24 months in the alternative.
SPEAKER_03: 30:33
Right. Abby, you guys are more than a provider of systems, right? One of the innovations that you brought in was to say, look, let's show people the best use case of all of our systems is to actually build a cloud, which you can buy from us or you can buy from a hyperscaler that buys from us or white labels, I don't know, from us.
SPEAKER_01: 31:01
You know, what we're going to do is what Abhi is saying is that look, this is not just a chip. Think of it as an entire system. So what they're doing as well is making sure that all of these open source models are instantiated on their system. Then they pass that on to us through this cloud. So that just think of like you and I spinning up a server on AWS and boom, we're up and running. Anybody in my company can do that. It's AI and open source models and all this stuff is not quite there. It's getting there. So one of the other things that working in the model that Abe described is that we are going to be bringing to Samba Nova and whoever our partner is lots and lots of use cases. We already have them. I think David and I were on the phone with some company that has a video model that basically he agreed to sending us the tokens to process the inference for that. And, you know, I didn't know this, but David told me right away that this model is not supported by Samba Nova. So I asked him why. And he said it's just a matter of time and bandwidth. And I said, Well, we should get this right in front of Samba Nova. And, you know, David said he'd already sent that over. So I think the other thing is what will happen is by having this model that Samba Nova has, by partnering with kind of providers like us, they're going to get stronger as well because we're going to the customers and they can't possibly go to as many customers. And we will benefit from other customers of theirs, their other OEM partners that will bring requirements. So we'll be able to support.
SPEAKER_03: 32:24
Let me push you a little bit further. So, like the question is about time is the ultimate scarcity. You talked about magpie, right? Which is the Australian adaptation of the model. Is that the idea? Is like you're going to do something for Indonesia too? You're going to do something for Thailand. You're going to like you're going to really nail this region, right? Because Australia has what, 30 million people?
SPEAKER_04: 32:41
27, 27.
SPEAKER_03: 32:43
27 million people. So now, but now you're hitting regions with hundreds of millions of people.
SPEAKER_04: 32:47
There's two answers. There's two. It's a really good question. And I love these challenging questions because there's two answers to that. One is I believe that those developing countries will need access to highly efficient, well-priced AI inferencing tokens. To talk about Arby mentioned tokens, they need that today. So I think there's going to be tremendous demand coming from those countries. And I think we'll get a good portion of that because we're in the region. Secondly, we have an opportunity to work with some of those countries to help them as they start to build their own sovereign services, which they will do. It's inevitable. It's inevitable. They will do it. And we have an opportunity to help them with intellectual support and, you know, just help them to build that out. So I think we've got opportunities in in both those areas. But, you know, look, I think back to your point about time, yeah, we've got to help everyone to make more use of this time. And the people that are flexible in mindset will get that. The interesting question for many of us in the industry is how long will it take the mass market to get that flexible mindset? When will everybody embrace that idea that they can do more? I'm intrigued, guys, by your view on this one, which is, you know, we get a lot of people talking to us. I've I've had a bunch in this last week who are saying, geez, how can you help us to replace our staff? And it sounds a bit rough, but I'll just talk about it honestly. You know, we want to cut our human resource cost. Can this AI stuff help me to replace jobs? Whether you call that digital labor or whatever you want to call it. My response back is, well, look, that's easy. Cutting costs, sure. But what about doing more? Don't think about it as cutting costs. Think about it as doing more. What could you now achieve if everybody in your organization was working at that speed you spoke about, Rajiv? Then what would we do? So I think this is a question for everyone on this panel and our world is how do we get, how do we educate people to think that they can produce this ubiquitous abundance you've heard that.
SPEAKER_03: 34:36
I think that's one of the things, right? Everyone's always concerned about cutting costs. That's the easiest thing to do. I say we're cutting costs. You heard Benioff talk about, well, I didn't have to hire 3,000 engineers this year because of AI. Really? Are you sure? Because everyone's spending more than ever on AI engineers and in applications. One example I can give you is my own company. It's under a couple of hundred people, and my engineering team's relatively modest. They're focusing on the agent architecture. And what's amazing is instead of them building the applications, the operations team is building the applications. Because now with AI and agents, I don't have to necessarily go to a separate team to build it, test it, iterate. I can actually have my team build it, the team that actually knows every nuance, build their own applications.
SPEAKER_04: 35:25
Thoughts? Quick thoughts before I move you to the next thing. My big thought on that, man, we've been speaking to a bunch of the venture investing community as well as the private equity community. And I can share with you two things. They are really concerned. You talked about something there, Rajiv, the way you talked about it. Now imagine that at scale, suddenly you can build what you used to buy. And so you've talked about Benny Off because in the conversation, you know, that's an expensive piece of software, Salesforce. It's pretty expensive. So what about a world where you build your own CRM? I mean, we're not far away. I wouldn't be advising everyone on this call to build their own CRM today, but we did it.
SPEAKER_03: 35:59
We built our own CRM for we can certainly connect multiple applications together if I want, or like you say, I can build my own.
SPEAKER_04: 36:06
I went to a visit of a well-known private equity person, I won't talk about who on this call, and they said this particular firm had $4 billion, this particular partner, $4 billion of SAS assets. And this person said, not sure what to do with those SES assets. They weren't the biggest of the big, you know, but still, $4 billion of SES assets. There could be a risk. Yeah. Abiy Akash, quick ones.
SPEAKER_01: 36:25
Yeah. I mean, look, I think that, you know, we've heard Google's engineers using, you know, AI coding tools. But, you know, I think it just moves the humans up the value chain to do much more complex tasks. So I think that some elements of things can be eliminated, but I don't think you know there's going to be mass exodus of people. So that's kind of my view.
SPEAKER_03: 36:45
New things to do. Abi, I you I mean, when I've gone to some of Sabinova's developer events, I'm blown away by some of the stuff that people are showing off. Like one line of code is doing what a whole application needs to do. So your thoughts? I know you're a techno optimist, so bring us home.
SPEAKER_00: 36:58
When I look at the long arc of history, every new technology development has said to these concerns, Rajif. What happened to all the horses and the horse carriage drivers? You know, I think this is a scenario where I agree with what Akash is saying. This is an area subject to Javon's paradox. The cheaper we make it, the easier we get it, the more people you could use. And let me ask you something. Would you want to put a curb on creating intelligence? That's what I ask. To me, this is where what David started off with. To me, intelligence is the hardest asset of all for us to replicate. We found a way to replicate it. By God, let's harness it and free people up from some of the drudgery that Akash was talking about earlier. I think will there be challenges? Undoubtedly. Will there be some displacement? Undoubtedly. Show me a technology product that has not gone through this. I think it comes down again to us having the foresight to plan for it and allowing people to find alternate ways to get initiated and find more productive users for their time.
SPEAKER_04: 37:53
But Avi, he's what happens when you've got 7 billion people that all have access to ultimate intelligence. So, what does that do for our society?
SPEAKER_00: 38:00
The way I look at it is look, there's so much prosperity created by people knowing how to code. At the most optimistic projection, we had about 40, 50 million coders. You know, Akash or David might know better. Maybe. At the stretch, we've now created an ability for 7 billion people to automate. That's fundamentally what we're doing, and that unleashes so many people who are just as smart, just as capable. They just didn't have that specific technical capability, which requires years and years of practice. I think we've unlocked 8 billion people to dream and create. And that is the promise with generative AI in my mind.
SPEAKER_03: 38:37
Yeah, I love it. I'll just give you my simple example. Let's say I have 200 people and I have 20 that are on the development side. The development folks can work on the architecture, making sure things are integrated well, are secure, right governance, right access levels, et cetera. All of a sudden, I have 180 people who can now take their knowledge and turn it into code that learns and scales. They can add their nuance and they can break into new places. It's a whole new game. And we're going to invent things that people haven't thought of. And I think that's the issue. In their minds, we can't foresee what it could be. We just look at linear paths, and maybe that's what it is.
SPEAKER_04: 39:14
Maybe it's what it is. But that's RB's lamp lighters. I mean, I think that is the thing that humans have always found a way to replace the lamp lighters. And we should find a way here too. Although I can't wait to see what they think of, Reggie. What are they what are they going to think of? It'll be fun.
SPEAKER_03: 39:28
This brings me to our next section. So all of us have MBAs, or we think we have some form of MBA. So we're going to talk about that today. So we're leaning into one of the most polarizing debates of the business world. I'm going to move you a little bit off the AI subject and move to this. The value of the MBA. Is the master of business administration still the gold standard credential? Or is it an expensive, outdated relic? With the rise of the entrepreneur, the digital investor, and AI, the $200,000 degree is facing more scrutiny than ever. So we've compiled some controversial opinions that both celebrate the MBA's enduring power and dismiss it as a two-year vacation for the elite. Get ready to decide is the MBA a necessary launch pad or an irrelevant liability in the modern economy. So here we go. Quick, quick answers from you guys. Okay. Yes, no, quick answer. MBA is the fastest, most capital efficient way to acquire a co-founder or strategic investor. The two years are an unmatched, high-stakes vetting process for talent and capital access. I'll go David Akash Abi.
SPEAKER_04: 40:36
I can only give you my long answer for you, yes, yes, and no. From an Australian perspective, if the answer is no, that's from the Australian perspective. I can't give you the equivalent answer from a US perspective. I think the answer is no from Australia.
SPEAKER_03: 40:50
Okay, thank you.
SPEAKER_04: 40:51
Gosh.
SPEAKER_01: 40:51
The answer from Silicon Valley, I think, is no, but the rest of America, perhaps yes. So I think that, you know, again, everything is nuanced. It depends on the individual, it depends on the person. If you're a builder, perhaps you can get going by just building. If you have a builder and you are only narrowly focused on building and you don't see anything outside building, then you need a co-founder with a business. And that that person may or may not need an MBA. So it's a little bit nuanced, but I think there are many people in Silicon Valley that can argue, you know, with a clear no.
SPEAKER_03: 41:22
So I got two nosed, Abby.
SPEAKER_00: 41:24
You know, I'm not going to purport to speak for the world or for Silicon Valley or the everybody else. I'll speak for myself. It was a yes because I was a computer science and math double major. I had zero business background. And I personally went to an MBA because I got tired of people telling me what to do and be in the back room. And as an engineer by training, I wanted to actually have the ability to make those decisions for myself. So for me, it was a yes, but I'm not going to purport to speak for the world. I know for me it complemented my engineering background with a set of valuable problem-solving leadership and elements. And besides, I got no great people like you and Akash.
SPEAKER_04: 42:00
So I love it. What's the meme, Rajid? It's a Silicon Valley meme, right? Which is the picture of the engineer who's saying, you know, I'm really pleased AI is here because I used to have to deal with those rotten MBAs that would cause me trouble and I didn't understand the product and didn't know the market, and they were just like annoying and slowed me down. Then the next frame of the meme is the business guy going, Oh, I'm so glad we have AI. I don't have to deal with those engineers anymore that were causing me trouble and never did what I wanted and always caused me problems. So uh interesting times.
SPEAKER_03: 42:28
We could do vibe coding, we could do vibe marketing, vibe business development. Everybody's just vibing with each other. Let me go to the next question. In the age of AI, soft skills are all that matter, and the MBA curriculum is too focused on quantitative modeling. The future leader needs emotional intelligence and narrative crafting, which a formal MBA fails to deliver. Who wrote this? Anyways, go ahead. We'll go backwards. Abi, you start.
SPEAKER_00: 42:54
I don't know which MBA you're talking about, but the MBA that I received was all about narrative crafting. In fact, people with British accents always did better in their grades, in my opinion, at HPSC. It was all about the narrative. Way better. David, you might have actually done well out there because they might have thought you were having a British accent, even though it's Australian. And it's very clear to me. So from my perspective, it does depend. I do believe that narrative crafting has always been important. Emotional intelligence is just as important. I do, though, believe that having a fundamental understanding of the concepts and then applying AI to do the drudgery for that does allow you to guide it. Even those people who frankly can't code and are being to code, having a little bit of a background in knowing how to code actually makes you able to use the AI coding tools better. So my answer is going to be at least the MBA I went through taught me a lot about thinking on my feet.
SPEAKER_01: 43:42
No way.
SPEAKER_03: 43:42
Okay. Akash.
SPEAKER_01: 43:43
Yeah, I think it's very important. I think I would have to slightly disagree. You know, I felt that it was too much focused on analysis and two by two matrices and buzzwords. You know, at the end of the day, success is about working with people and finding ways to compromise, finding ways to fill the gaps. And business is about people as much as it is about anything else. And I think some of the programs, you know, need to kind of over-index in that now that technology is coming and intelligence is in abundance. This is not in abundance. So I think that programs have to really up their level and really focus on that. You know, you can't just say fire the CEO. That's a classic HBS response. Change this, change that. You can't do any of this stuff because in reality, you're working with a set of constraints, and those constraints are people, personalities, and their opinions. You can't just do that.
SPEAKER_02: 44:34
Not everyone is Eric Peterson. Okay, go ahead, David. Your answer.
SPEAKER_04: 44:37
Well, I mean, those two folks are pretty good representations of the Harvard Business School. You've done well. You'll be getting a check in the mail from HBS, I'm sure. Look, you know, obviously it's a combination of skills that makes people successful. You've got to be able to do everything, particularly in today's world. And back to what Ivy said, you can. If you use AI as your assistant, your true assistant, you work with it, then no excuses. You should be able to do it all. And maybe today's MBA is do it all. It's all the skills. It's a combination, it's a bucket of all that stuff, and it produces the best people. And those people use the best tools, as humans have always done, to produce the best outcomes.
SPEAKER_03: 45:13
Love it. Okay. This time I'm gonna go, I'll change the order. Akash, I'll be in David. The last question in the MBA segment. A top-tier MBA is the only way to gain instant credibility when pivoting into complex fields like venture capital or private equity. You can't learn sophisticated deal structuring or fund management on YouTube.
SPEAKER_01: 45:34
Well, you can learn it on the job. So, you know, again, technically you don't need an MBA if you've worked in a finance company with an undergrad and you're around that, or you can learn it as an entrepreneur.
SPEAKER_03: 45:44
Remember, this is pivoting. The question's pivoting. Pivoting.
SPEAKER_01: 45:47
Yeah, I mean, I guess it does help with the pivoting. It's like a catalyst. Is it the only way? No, but it certainly definitely greases your chances of success doing that. And you know, you could argue do the classrooms really teach you about realistic financial situations that companies are in? I mean, those are again case studies, and they're you're you're trying to solve them mechanically through a vacuum. And again, you could argue you could feed that same information into an AI agent and it could give you a prescriptive answer. But a prescriptive answer is not what really happens. Every deal has nuances that are more complex than kind of what's shown on paper. So that's my thing. It's a start, but it's not a complete answer.
SPEAKER_00: 46:29
This one I'll go the other way. I absolutely don't think it's necessary. I mean, look, there are more than enough successful examples of founders who didn't know Jack about financial structural who've done just as well. I think today an amazing VC is somebody who's been a founder a couple of times and has gone through this process. I think that's just as valuable a skill set. And I think there's several founders who I think would put many an MBA to shame for what they've achieved. I think it just comes down to what David said earlier. It's about the set of people working together. Whether you're a founder with a technical background or an MBA, if you know how to surround yourself and know how to work with people and supplement your ego and saying he knows something better than me, or she is so far better at me than this particular area, I think the result is a better outcome for everybody. And so I don't think this is necessary in this day and age.
SPEAKER_04: 47:16
Great point. David, I'd say that's not necessary. But look, I think working together, as Abby was saying, is everything. This is the new skill. You said it before, Rajiv. It's in a world where you have ubiquitous intelligence, again, crazy to say, crazy to say, but let's just use that phrase. In a world where you have ubiquitous intelligence at the MBA level, then it's going to be about how do you work with people.
SPEAKER_03: 47:35
I'd love these opinions. I I would say from what I'm seeing today, I think Jeffrey Busgang from Harvard Business School just ran a webinar with alumni talking about how they're using AI in the classroom. And it is what you all were talking about, about the layering of skills. Like if you think of the MBA as what it was before, I mean, they're going in now. Basically, you're asking questions of the case bot, essentially, before you walk in. And now instead of setting up the case, you're walking into talking about it at a greater level of depth because you have AI to have those initial conversations and really jump in. So it's about the MBA being used in an appropriate way, building upon your skills and learning who to work together. I mean, look, because of those classes, I got to know Abi, and years later, I'm still chatting and working with him. So it's people. It provides a tremendous value from that point of view. These are great answers. I appreciate it. And so will all the top business schools. So now we're going to move to the Spark Tank. All right. So this is where you get to really put on your fun hat. Today we're joined by three exceptional leaders who are building sovereign, scalable, cost-efficient AI infrastructure at Southern Cross and over at Salmanova. So we have founder, CEO David Keene, Chief Strategy Officer and Co-founder Akash Agraval, and Chief Strategy and Product Officer Abi Angle of Salmanova. So for now, we're setting aside the high-stakes world of AI to look at a different kind of mania. Pickleball. This sport has blown up, creating an entire culture of devotion and sometimes extreme behavior. Here's the deal. One is a complete fabrication designed to sound just plausible enough to make you second guess your judgment. I'll count down three, two, one, and all three of you will reveal your answers simultaneously. Ready to separate pickleball fact from absolute fiction?
SPEAKER_01: 49:37
Let's go. Let's go. Let's go. Let's do it.
SPEAKER_03: 49:39
I'm waiting for Akasha to clap his hands. The pickleball massive.
SPEAKER_01: 49:42
Let's go. I got the pickleball.
SPEAKER_03: 49:44
He's got it. He's got it. He is the pickleball coach of the year. All right. Two shoots and a lie. Pickleball maniacs. Here's question one. At the 2024 National Pickle Fest, two fans legally changed their names to Dink Vader at Smasherella after hitting 300 volleys without dropping a shot. Number two, a group called the Pickle Breakers set a Guinness World Record in 2025 for the longest pickleball marathon ever. 36 straight hours of mixed doubles in Carrollton, Texas, raising $18,000 for charity and allegedly surviving on energy gels, beef jerky, and pickle juice. Number three, pickleball's popularity explosion led to some U.S. towns establishing official quiet hours after neighbors complained that the sound of the pock drove their dog into chaos. Okay. Three, two, one. One for David, two for Akash.
SPEAKER_04: 50:51
Nobody hits 300 shelves in a row like that.
SPEAKER_03: 50:53
Come on. So David says one. Wait, Akash, what do you say?
SPEAKER_01: 50:56
Two, two.
SPEAKER_03: 50:57
Two, and Abby says one. Okay. David says nobody hit 300 volleys while dropping a shot. And he is right. So that is the lie. While Dink Vader would absolutely dominate, there's no record of legal name changes at a pickle fest. Though pickle themed nicknames are wildly common among super fans. So they're not maybe you can't hit 300 volleys.
SPEAKER_00: 51:17
What is Akash's pickle name?
SPEAKER_01: 51:19
Akash, I don't have a pickle name.
SPEAKER_03: 51:21
You don't have one like DJ Cash. You don't have the cut. No, I don't have a pickle master. Okay. The pickle breakers 36-hour match raised funds for Taylor's Gift Foundation, combining athletic endurance with a heartfelt cause, a rare mix of exhaustion and empathy. And the pickleball noise restrictions, number three, are very real. Some cities even conducted acoustic research to reduce paddle clatter.
SPEAKER_01: 51:43
Well, they won't let you build a pickleball court in certain Bay Area neighborhoods anymore. That's right. In Atherton, the the country club there is under severe pressure to reduce the noise. So what some innovators have done is built these new paddles that absorb the noise.
SPEAKER_03: 51:58
Oh, that's a good idea. Number two, the oldest pickleball player, Joyce Jones, holds the Guinness World Record at age 95, saying her only secret is pickleball, Pilates, and prunes. That's the that's answer one. Number two, a Wisconsin man once had pickleball patties carved into his wedding cake design, with the newspaper quoting his spouse, who approvingly called it love at first dick. And number three, in 2025, four players in Montana attempted a marathon pickleball session that lasted 25 hours, just pausing every hour for five-minute hydration breaks, and one spontaneous interpretive dance to Eye of the Tiger. Okay, so first one oldest player, second one, pickleball patties, third one marathon pickleball session 25 hours, and Eye of the Tigers. Ready? Which one is a lie? Three, two, one. I'll be as three, David. It's two. Akash, you are three, three. Okay, David. Why do you think number two?
SPEAKER_04: 53:01
Nobody's wife would agree to that on their wedding day.
SPEAKER_03: 53:04
All right. No, Akash, would your wife approve of this?
SPEAKER_01: 53:08
No, she wouldn't, she wouldn't. But you know, I know there are people out there because my wife's not playing pickleball, but there's some wives that playing pickleball, so they would agree.
SPEAKER_02: 53:16
Which one did you pick again?
SPEAKER_01: 53:17
I picked three. I picked three.
SPEAKER_02: 53:19
Why'd you pick three?
SPEAKER_01: 53:20
It's just too long. I think it's just too long. 25 hours, whatever. Yeah. Well, guess what? David is right. Wow, David's got two out of two. David is the lead. It's thinking like an Australian. Exactly. He's thinking like an Australian. He's fine-tuned the model. Yeah, he's fine-tuned the pickleball model. Yeah, there you go.
SPEAKER_03: 53:39
Okay, so David thought correctly. Although wedding cakes have indeed featured pickleball paddles, there's no record of Love at First Inc. as a headline just yet, but it could happen. Number one, Joyce Jones' record at 95 cemented her as a living icon. Guinness recognized her for lifelong vigor and funky neon sneakers. And number three, the Missoula-Montana marathon was real, cementing the idea that endurance pickleball is a thing, not a punchline. All right, let's see who can come back on this way. Here's number three, number one point, or number one truth or lie. In 2023, a group in Wisconsin broke the Guinness World Record for the longest pickleball volley rally, lasting more than 14,000 consecutive hits, with players taking turns using slow motion dinking to keep the rally alive. Number two, pickleball fans once organized a competition called the paddle limbo, where players see how low they can go under the net without dropping their paddle or losing a point. The championship record is limboing under a 10-inch net. And number three, in 2025, US pickleball reported that over 4,200 new pickleball locations opened nationwide, catering to the sport's explosive growth. Which one is the lie? Three, two, one. Two Abby, two David, two.
SPEAKER_04: 55:08
We better be right, guys. We're with you on this one.
SPEAKER_03: 55:10
Why do you think Paddle Limbo won't work?
SPEAKER_04: 55:12
It's just too low. Ten inches is too low. Oh, we're just too old, guys. We just too old.
SPEAKER_03: 55:17
Obviously, that was a layup. Thank you, staff. So all three of you win on that one. So I get to give each one of you a point. While Paddle Limbo sounds like a hilarious fan idea, it's not a recognized or sanctioned competition. Number one, the Wisconsin rally set a record for the longest volley rally, verified by Guinness and covered by local news, illustrating fans' stamina and creativity with slow motion techniques. And number three, the 2025 growth report confirmed a massive surge of new courts with over 4,200 added the prior year. Pickleball is just exploding. So here's the final one. And in this one, let's make it interesting. I will make it so that the winner gets two points. So this is a chance to beat David. Which one's a lie? A 2024 tournament in Florida created a pickleball costume day with players dressed as giant pickles, paddles, or even jars of brine, drawing crowds and even viral TikTok videos. Number two, in 2023, a pickleball fan from Oregon held the world's first ever pickleball hot dog eating contest between matches at a local tournament, drawing over 500 spectators. Number three, the quote dill ball has been unofficially adopted as the sports mascot, complete with custom jerseys and a theme song played at major tournaments since 2023. You ready? Three, two, one, go! This is the chance to win. David has three. I see Akash at three. I see Abby at two. Okay, Abi, support your case.
SPEAKER_00: 56:49
Oregon hot dogs. I mean, it just didn't seem logical to me at all. Like the crazy things that pickleball fans do, like dressing up in pickles, is plausible. The last one is so plausible. The second one, what if hot dogs got to do with pickleball? I have no idea. Just didn't seem logical to me.
SPEAKER_03: 57:04
Akash, take them down. Take down Abi.
SPEAKER_01: 57:06
Yeah, people eat hot dogs with everything. So, you know, why not pickleball?
SPEAKER_03: 57:10
David, do you have anything else on that?
SPEAKER_04: 57:12
I had to pick three because if if there was a different national theme song for pickleball, Akash would have already played it. It'd be playing in his house all the time, so it can't be that.
SPEAKER_01: 57:20
Yeah, yeah. Yeah, David spent some time with me.
SPEAKER_04: 57:22
If there was one, Akash would be playing it. Yeah, Akash would know it, I guess.
SPEAKER_01: 57:26
That's just a good point. That's a good point. I didn't know about it either. I don't know any song that's pickleball song. David's right. I would have known about it whether I'd play in front of David or not, and I haven't. Maybe I missed it. I've been busy lately here.
SPEAKER_03: 57:38
Well, the correct lie and the winner is number three, is false.
SPEAKER_01: 57:45
So David has won it again.
SPEAKER_03: 57:47
Perfect score. So David is the winner. He gets the extra two points.
SPEAKER_04: 57:51
Just like the cricket, guys. Just like the cricket.
SPEAKER_03: 57:53
While Dill Ball would be an incredible mascot, no official or unofficial mascot with that name exists in the sport, which is correct because apparently Akash would know that. And the pickleball costume day, the number one one events have cropped up at various tournaments, especially in Florida, sparking festive atmosphere and a viral social media buzz. And number three, the Oregon Hot Dog Eating Contest was a well-documented, quirky side event at a pickleball tournament showing fans' appetite for fun and food. There you go. You guys did great. That was a fun pickleball game. It'll certainly do well on our YouTube shorts. So I appreciate you guys humoring me for that. Let's get on to uh some personal closures. Okay, David, if you had to pick a superpower based purely on making daily life more convenient, not saving the world, what would it be?
SPEAKER_04: 58:40
The flesh. Speed of the flesh. Get a lot more done, see more people, experience the world.
SPEAKER_03: 58:45
Okay. What's something you used to be really into that you now find completely baffling about your past self?
SPEAKER_01: 58:52
Worrying about things that don't matter in life, really. I mean, I think maybe I was not taking into account people's feelings as much. So I think that those are critical. I think that, you know, perhaps I didn't pay as much attention to that. So, you know, it's it's sort of a reverse answer in the sense that I didn't worry about them, but I worry about them now. So I think that's very important as you get older and a little bit more what people think of what you might say. So I think that's very, very important.
SPEAKER_03: 59:20
That's an incredible answer. Abi, what's something you're grateful your younger self did or didn't do that's paying off now?
SPEAKER_00: 59:27
My mom enrolled me when I was in the fifth grade summer in a computer coding class, and I was pissed off. And I'm just so grateful and that she did that. And actually, today's her 12th death anniversary. So I thank her for everything that I have and everything I am every single day. Amazing.
SPEAKER_03: 59:42
Definite love to your mom. She's an amazing person. Okay. If you could give everyone in the world one piece of information or one realization, what would it be?
SPEAKER_04: 59:51
Well, I was gonna say they should visit scx.ai to experience the future of sovereign AI. But apart from that, it's that the world is all about people, it's about making sure that. That you have people in your life like the folks on this podcast that you love working with and you can build a life around other people.
SPEAKER_03: 1:00:06
Akash, what's the most interesting thing you've learned recently from a random internet rabbit hole?
SPEAKER_01: 1:00:13
There was someone, was it you, Dave, who told me this about the Bitcoin example?
SPEAKER_04: 1:00:17
The Bitcoin duplicator.
SPEAKER_01: 1:00:18
Yeah, the Bitcoin duplicator. So what was that, David? Can you share more about that one?
SPEAKER_04: 1:00:23
If anybody's on this podcast, don't visit the Bitcoin duplicator where they ask you to put in your blockchain ID and they promise to give you back twice the number of bitcoins that you put in because it always works.
SPEAKER_01: 1:00:34
Yeah, that was the one. That was the one. So hopefully I won't fall.
SPEAKER_03: 1:00:37
You chase that one down?
SPEAKER_01: 1:00:38
Yeah, I didn't chase it down, but I was very curious. I was very curious. Right down. Yeah, exactly. Right down to zero, yes.
SPEAKER_03: 1:00:45
Okay, Abby, what's something you do to feel like yourself when life gets chaotic or overwhelming?
SPEAKER_00: 1:00:51
I go for a long bike ride with friends and just exhaust myself, or I go for a walk with my dog and my wife. There's nothing more relaxing for me than that.
SPEAKER_03: 1:01:00
I thought you were gonna say I go to Rajiv's house.
SPEAKER_00: 1:01:03
That too. That was the third thing if I was allowed a third thing. That was his backup. When the other two don't work, he comes to that.
SPEAKER_01: 1:01:10
Yeah.
SPEAKER_03: 1:01:10
All right. What's the most memorable meal you've ever had and what made it so special beyond just the food?
SPEAKER_04: 1:01:16
People shouldn't cry at this, but it's dinner with my wife last night. Because I've been traveling a lot and I got to have proper dinner with my wife at a lovely Italian restaurant downtown in Boston. It was the best meal I've ever had.
SPEAKER_01: 1:01:27
Wow, what a romantic David. Yeah.
SPEAKER_00: 1:01:30
Well, his answers are perfect. Avi, can you believe it? I think he's using magpie. I think he's got magpie embedded in his brain. Exactly. There's something, yeah.
SPEAKER_04: 1:01:38
You still have to have the competition, uh, you know, Raji. We still have to know whoever can identify what the bank pie used first in the comments gets what should we give them? A thousand dollars of free tokens on scx.ai. Whoa.
SPEAKER_03: 1:01:49
You heard it here.
SPEAKER_04: 1:01:50
That's it. But they're gonna identify what it is.
SPEAKER_03: 1:01:52
Let's do it. Thank you. Thank you for all those extra comments, folks. I appreciate it.
SPEAKER_00: 1:01:57
I think for all of my memories of food are actually tinged with memories of the people I've had them with. So it's really honestly, sometimes I don't even remember the food. It's the laughs we had at the table or the special event is at. So I kind of with David on this one. I'm not gonna go syrupy and say it was just with my wife. But over the years, it's a series of special experiences to me. Meals and people are things that just make life worth it.
SPEAKER_01: 1:02:21
I would just say I find street food with people just joking around, uh standing. You don't need to even be sitting to be quite entertaining. And you know, different cultures with different people that know those cultures. So on travels, you you know, I try and meet with people in their local countries and try and indulge in some of their local street food. So that gives me joy.
SPEAKER_03: 1:02:41
I appreciate that. Yeah, that's a great way of putting it because you really see what's in their heart.
SPEAKER_01: 1:02:45
Yeah, yeah, exactly. You know, how how the taxi drivers or the local people enjoy, you know, their snacks and their culture.
SPEAKER_03: 1:02:52
Amazing. Okay, Akash, one pickleball factoid that we didn't know about.
SPEAKER_01: 1:02:57
You can actually go in the kitchen. How's that? So, you know, they say you can't go in the kitchen. You can go in the kitchen. You can go in the kitchen when the ball has bounced. You can go in the kitchen by going and standing on the side of the kitchen and putting your arm out and preventing the ball. Physically, your legs can't be in the kitchen and pick a ball. So there's a couple of workarounds. One is when the ball's bounced, you can stand near the post and basically put your arm out and stop the ball. That's so that's one. And the other one is that when you're serving, you can serve into the opponent's body and you'll win the point. If the ball touches your opponent's body, you win the point. So that's a technical rule and nobody can argue against it. So when you're playing with someone and it's 11-0 or it's 12-11 and you really want to win the point, serve the ball into you didn't hear it from me. You can serve the ball into the recipient, the person that's standing near the kitchen, and he can't. If basically you're gonna win the point unless he avoids the ball. Because if it touches his paddle, if it touches him, you win the point. That's what happened to me in a tournament. I didn't know this rule. It was 12-11, and the guy looked at me and laughed, and he said, Clearly, you should have known the rules. I said, You're right.
SPEAKER_03: 1:04:05
That's the new Akash. He actually said, You're right.
SPEAKER_01: 1:04:07
My my sense is our car saying something really rude back to him. That's what I'm thinking. I didn't say anything because that was the wrong. There were three other people, so you got to be careful. I would have gotten another point taken away if I'd said something rude.
D; SPEAKER_03: 1:04:21
I want to thank you all for being with us today. I definitely would love it if you guys all go to scx.ai and learn more about sovereign data. I think it's more than Australia. I think there's Australia, but it's a great model for what could be an incredible phenomenon around the world. And I think, you know, we should all go check out Salmanova's website, which a certain company helped design and develop, you should check out and learn more about the multi-layered solution they have. And I thank all three of you for joining us today. You guys were really amazing. This is fast emerging, and so I'm really excited to have all you guys come together. Thank you so much.
SPEAKER_01: 1:04:55
Thank you for having us.
SPEAKER_04: 1:04:56
Thank you so much. Great event.
SPEAKER_01: 1:04:59
Yeah, great event. Thank you guys. Bye-bye.
SPEAKER_03: 1:05:06
That was really interesting and fun from people who I've played pickleball with. What I took away was there's three people who've been executives and entrepreneurs with somewhat similar backgrounds, but diverse backgrounds, talking about how they're building this incredibly disruptive, innovative set of businesses. And this whole notion of sovereign AI may sound very esoteric to you, but is very personal. And I think David really pulled it out when he talked about the need in Australia to have things about the way people in Australia talk and act, their customs, their legal language, their regulations, the way they look at things, in the way their AI applications, conversations, capabilities are developed. And then there was the greater notion of splitting the notion of training and inferencing. And Abi explained it so well, kind of like AI 101 for business. If you really understand inferencing and training and how they're two different things, you can turbocharge the way you look at budgets and how you build applications and how you drive them. And then we learned a lot about competition and how this AI world isn't necessarily leading towards winner take all, even though it may seem that way today. There was a time when Yahoo was dominant. There was a time where in the browser space, Microsoft was dominant. Nowadays, there's even new browsers coming from the different LLMs. You know, Chrome was supposed to be dominant. That's blowing up too. So it's the amazing nature of technology and the sense of optimism in terms of what is potentially out there. This isn't job replacement necessarily. This could be uplifting to you in your career and your life. And that's the kind of interesting optimism I saw from all three of them. And during the MBA portion, wasn't it notable how each one thought of their MBA experience and what's notable today about the new one? You can relate to what was happening in the past, but it's changed dramatically of what's happening today. But in many ways, these folks have known each other prior to this through various events that some of which I'm proud of putting them together for. They've met each other and now they're working together and doing business together and making a difference together. And that's the power of the network. And that's the power, as we talked about in our last episode of going to that extra event, going to meet folks, just putting yourself out there and not having any expectation other than openness to serendipity. Of course, we had a lot of fun, a lot of playfulness. And I think this is something to aspire to if you're out there and you're steadying yourself up and saying, wow, you know, you have David, who's a multi-time entrepreneur, same thing with Akash, same thing with Abi. These guys are amazing folks who keep hitting different levels in their life and they never, they never stop going. And it's something that inspires me every single day when I get to hang out with folks like them and play pickleball with them. All right, thanks for listening. If you enjoyed the pod, please take a moment to rate it and comment. You can find us on Apple, Spotify, YouTube, and everywhere podcasts can be found. You saw David's promotion about the$1,000 token credit. Take advantage of that today. Go to SCX.ai. This show is produced by Sunday Parik and Adam Shah with production assistance by Taryn Talley and edited by Laura Ballant. I'm your host, Rajiv Parik from Position Squared. We are an AI enabled growth marketing company based in Silicon Valley. Come visit us at position2.com. This has been an F Funny production, and we'll catch you next time. And remember, folks, be ever curious.
