Okay. You mentioned some of the applications. What are the kinds of industries that you're getting the most interest from?
And right now, it's, I would say, across the board. And I'll give you the spectrum, and then I'll amplify the areas where I believe that's going to be the highest traction. So we are engaged with the top five customers in robotics, top five customers in the government sector, the aerospace and defense sector, automotive, medical, transportation tech, agricultural technologies, and also a category of smart vision, that's a Venn diagram, oral app or industrial automation, right?
So visual inspection, factory flow automation. So these are all the applications, and we have as a company in the last five and a half years, engaged with the top customers in each one of these market segments. Play this out five years from now, where will we see the highest volume, highest growth?
I think clearly, automotive, just by the nature of it, is going to be a key area of focus for us and the driver. Right behind it, I estimate would be robotics. I think there is a resurgence of a lot of focus on robotics.
COVID brought a lot of the supply chain issues and the legacy architectures coming in the way of global productivity in a big way. But I also think that there's a lot of articles written up on labor shortages globally. And people really want to bring in a lot of automation into the factory floor environments.
So you're going to see a lot of AMRs or robotic environments across quite a few warehouses. There's a lot of talk around humanoid robots. This is a new area of development.
Some of these may not pan out or as with everything in life, may take much longer than anybody's estimate. But the fact that I think robotics is going to play a very large portion of our lives, that's a given.
Yeah.
With these edge applications, they work with the Cloud, right? I mean, they're not intended to work independent of the Cloud, are they?
It depends on the customer's architecture. Take, for example, R-chip. R-chip is capable of working independent of the Cloud.
So you could fundamentally train an application, and you could infer that at the edge. There is really no need for the application to be connected to the Cloud, unless you choose to do so, right? And so the application is fully capable of being entirely independent, running on its own with no connectivity.
And many applications, really if you think through it in the real world, may not have connectivity elements, and or may struggle to get connectivity. And you don't want to be dependent on the connectivity alone, right? So we built a chip that's entirely capable of being self-managed, and being out there with no need for a Cloud connectivity.
But if the customer chooses to have a Cloud connectivity, either for updating the algorithms, or to really do a nightly upload of information or analytics, we enable that also.
Yeah. Are you working with, I would assume you are with many drone manufacturers, because this sounds like what you would need on drones.
Absolutely. And so we have built a platform that is the best in class in performance and power, and the programming environment we believe is the best ease of use in the industry compared to our peers, if you will. And drones are a poster child that needs all three.
They want the highest performance, the longest flight time, lowest battery consumption. And I would say we are better poised to serve that compared to anybody else. And so absolutely, we are engaged with the market leaders on unmanned aircrafts and drones.
And we see a lot of good traction for technology in that market.
Yeah. And the processing that's taking place is computer vision and analytics and control, I guess. Are there others that I'm not thinking of?
No, I think there is also navigation.
Right.
You could argue navigation fits in the context of computer vision. So there is fundamentally a camera subsystem or some kind of a LIDAR radar subsystem. So gathering location-specific data and you're computing and you're making decisions.
So it's a combination of computer vision, perception, localization, segmentation, and really distributing the workload, both from an AI context, but also into classic computer vision. And you also have control plane functions to watch your flight navigation, and really ensuring that I think you're combining all that into a single chip. And this is kind of what we do well.
And given that we are a heterogeneous computer platform, we do more than AI workloads. And so you could actually put the control plane, the navigation, the decision-making, and have it all work on a single chip.
Yeah. And how large are the chips? Is there a standard product that you talk about it being a heterogeneous genus?
I'm glad I'm not the only one that struggles with that.
Yeah, that's right. How large are the chips? Because certainly, you know, the Nvidia packages or systems are, you know, getting, you know, you need a truck to move them.
And they're certainly not going to fly in a drone. So how large are your chip packages?
We are really big. That's it. And so you can almost visualize what I see in my thumb.
That's about the size of what we need to have. And that's what we deliver. And so we, that's the chip.
We also provide bold form factors so that customers can easily integrate that into our existing structures. And one of the benefits in having spent 30 odd years is I've spent a lot of time studying, not just me, our entire team, what we need to be at in terms of cost, power, form factor. And we have put all of that into really what we have built eventually.
And I think the opportunity we have had is we have built something from grounds of purpose built. I am not a public company that's got a lot of legacy. I have zero legacy.
So we have said, hey, this is our learning. This is what we need to do. And we have raised a good amount of capital.
And we said, let's put the capital that we could use and build something really for the customers.
The other side of what's happening in the chip world are the foundries. You're designing chips, but you need a foundry to etch the chips. And, you know, there's various companies are building foundries for various types in the United States.
But for the time being, TSMC and Taiwan really is the one place where you can get this done. How do you get capacity with them?
I keep joking that though we're in the technology business, it increasingly more and more is a relationship business. And one of the side benefits of growing old is you get to know a lot of people that are all in key decision making positions at all these companies. A very, very small company.
We are fantastically happy with the partnership we have with TSMC. They've been an amazing partner to us from day one. And they've given us and they've made us feel like a big public company.
And so I'm very lucky that our problems are all demand related and not supply related. And so we have worked very hard with them and we have done a good job in managing the inventory needs and the market demand and really planning well. And I would say I think it's never an easy thing to do, but you've done something for 30 years, you tend to become reasonable at it.
And so I think the team is a very well-qualified team, but we won't be here without our partnership with TSMC. So we're very proud of what we've done together with them.
Yeah. Is there something different in the equipment required to build these chips? I mean, I would presume in that you're trying to build them small, that you want to use the smallest, I'm not sure what it's called, but nanometer gates or whatever.
And what size are you at? And are you looking, I would presume you are looking at the new founders being built and is your architecture something that could be produced at any foundry or is it a particularly, particular kind of foundry that you would need?
Great set of questions. I think one of the key things we decided to do early on was we recognized that our software-centric approach gave us a lot of opportunity to get better performance and power. We decided to scale back in what you referred to as process technology.
And so we created our Gen 1 silicon product at 16 nanometer, 1.6. And this is at least 10 to 12 year old technology. So we did not want to take very advanced process technologies and take a lot of risk.
There's also a cost equation and a development equation. And as you get more aggressive or more newer nodes, the cost, the mask set to reproduce the chip, but also the development cost both really go up quite a bit. So Gen 1, we said, hey, we're getting amazing performance and power compared to anybody else.
And in real applications, we're 10x of the very best companies. So we said, let's stay back in process technology in Gen 1. We did 16 nanometer.
And in Gen 2, which we have now gone public, we have announced that we'll be at 6 nanometer. So we'll be getting a 2x improvement over what we have done in Gen 1 on a performance per watt, right, which is a huge leap. Typically in our business, you get 10-15% improvement, Gen 1 to Gen 2.
For us to get a 100% leap is pretty phenomenal. And we now feel like we have the right opportunity to do it, and our customers will usually derive the benefits of it. And to answer your question, we are tracking very closely where we get our chips manufactured, and we have the luxury of getting them manufactured now in the US as well.
And at the appropriate time, we'll take full advantage of every opportunity that we have. And within TSMC, I think we definitely have the choice of being manufactured any place. And just one thing is, and I think we are, our business doesn't work in that you build a design and you could go to anybody.
And so, yes, at a design implementation level, I think you have that opportunity. But I think once you get into the chip development, you fundamentally locked into one entity. That's typically how our companies work, and we are too small to play with too many players.
And our volumes are too low to really play the game. And if you redo it, it's uneconomical or economically not viable. And so I think we really want to work with the best in class, and TSMC is as good as it gets.
And they have done a phenomenal job, and they truly understand that this is a services business. And even today, I'm very impressed that as a startup, we get the same attention, if not perhaps more than a public company. And so all of those really are huge positives.
Yeah. So you're five years in. Are your chips deployed now in any edge devices, or are you still working toward that?
So we are deployed. I would still say it takes a long time in our business to really scale. Like the cloud business or the consumer business, where the design and cycle is fast, the embedded space thinks takes a long time.
But then the other positive is that they stay for production for 15, 20 years. So it's a game of inertia. Getting in is pretty hard, and the opportunity to stay in production is also pretty significant.
So we have quite a few customers that are moving to production with us globally. And over the next year or two, we are excited about scaling more and more customers to get into production with us.
Yeah. And how many people are at the company right now? And how do you scale a company like this?
Because as you said, the demand is massive.
We are about 160 of us today. And with a lot of consultants, I think, or contractors, we are on 200. So I would say wrongly, we are 200 people working at the company.
We are lean. We are credit lean for what we are doing. And it really is kudos to everybody that works here in that it's a startup and we do whatever it takes to make things happen.
And we are in some ways doing what many companies use, tens of thousands of people to get done. And I'm a big, big admirer of everybody that we have here. I'm biased and these are all more than employees, family for us and that we do whatever it takes to go make things happen.
The macro thing that is a priority for us is scaling. Is scaling our go-to-market and how do we touch 40,000 customers in scaling our go-to-market partners that we have, reps and distributors and VARs and ODMs and ISVs. And again, I go back to not only myself, but I think we have had a lot of experience scaling businesses in our career before.
And so we retain the core of the company to be small. But through a partner network, we expand our footprint and where we go look to. The underlying thing that really enables us, Craig, is really our software.
And more self-managed the software is, the more the customers can manage themselves. That's a large, large component of how we can enable the scaling. If every one of them needed a hand holding, we don't have a company.
One day, I think, we are going to touch tens of thousands of customers and it will be a very exciting scaling opportunity for us.
Yeah. And the biggest market, I would assume right now is the United States, but I don't know. I mean, this is a global phenomenon.
Absolutely.
I think by footprint, North America would be the largest market for us, no doubts. But we are enjoying the benefit of our customer traction in Europe, Japan, in Korea and India too. And about 70 of our team members are based in Bangalore in India.
And we also are building out sales and go to market activities in India. And I think India is going to be a massive growth, in general, a doctor of AI. And we feel like we are one of the leaders and pioneers in this category of edge market scaling.
And I am quite convinced that I think in the next 10 years, this is going to be a high priority for every nation, a high priority for every industry sector. And people that don't have an AI-enabled environment are going to be left behind. And I think it's a matter of now who's wanting to gain leadership position.
There's going to be a fear of missing out that's going to go through the entire customer base.
Yeah. And you were talking about how I'm going to avoid the word again, but how you use your chip is not specialized one particular application. But is there an application that at some point it seems, if not in the design of the chip in scaling your sales and marketing and all of that, you've got to focus on a few applications and let the others come to you.
Which are you guys focused on?
I would say robotics, industrial automation, and vision systems. If you really do a Venn diagram of those three, I think that'd be a key gravity area for us. And I should expand on that and saying, every day our struggle is specificity versus generality.
So we've got to really make this balance happen. And I've built products before that will work for 40,000 customers, where you build one thing, every one of them is doing something radically different than the other, but it all still ends up being mostly the performance, mostly the power, mostly the cost that they need. Not easy to go to.
And we have learned and built good businesses earlier in our career, and we have used that experience to build it. And I would say, though I explained our gravity point of our highest volume, where I think we're going to drive, most people are going to find out that I think we are better than everybody else for their application as well, and all the other market segments we've already talked about.
Yeah, this wasn't, I wasn't going to ask this, but it just occurs to me on this question of scaling. You know, the big boys are all chasing this market as well. What's your future?
Do you think you guys will end up as part of a larger, you know, Google or Nvidia or somebody at that scale? Or is your expectation to stay independent and grow to that scale?
Really good question. And I would maybe give you two or three things that I think maybe I should mention. One is what I've learned now in five and a half years, and all my career I've been in large public companies, and this is my very first startup.
I started and what I've really come to recognize and truly internalize this, it's not the size of the dog, but it's the size of the fight in the dog that matters. I've been in very large companies and I always wondered, my God, we need more to get things done. There are 200 people and we are doing things of 10,000, 20,000, 100,000 people companies.
When you really build yourself into an element of, this is our team and this is what we're going to go do, and this is our life and blood, you operate very differently. That's one thing. The second thing I should say is, I have no idea how to predict the future.
What I do know is if you have results, you have options. We have really submitted ourselves to not worry about what outcome is ahead of us. We don't know.
What I do know is if I drive results, I have outcomes. And if I don't have results, I don't need to worry about outcomes. And so we single-mindedly put our head down to really focus on driving to be the best in the category that we are in.
And we cannot be everything to everybody. We really need to focus and do a good job of what we do. And our company definitely has been interesting to a lot of people.
I think that should be a fair thing for me to validate. And I think it would be fair to say that I think we are definitely noticed by everybody, by our customers, by our peers. So what our future really holds?
TBD. When I wake up every day and go, there's one thing to get done, and I drive back home saying, yeah, we got that done today. And I'm happy.
Yeah. And this is getting off subject, but I'm curious about the fundraising journey. How easy was it to get the initial capital?
And are you still raising funds?
I would say two things. I think for a long time, investments in chips had dried up. Chips were no longer really a high priority and a focus just because of the investment amount needed to the return cycle.
It just didn't fit every C mold. And so almost from 2005 till maybe even 2016, 2018, there are hardly any chip startups. It's now a key gold rush, and there's an enormous amount of attention and span put into it.
And I would say raising money is hard. Anybody that starts a company, if you walk in assuming that raising money is easy, I would urge you just really pragmatically internalize that it's hard to do. But I also simultaneously held the notion that the right kind of idea, the right kind of system and a setup always is capable of attracting good capital in any circumstance.
And we've been very lucky. We have raised around 270 million so far. And we have amazing investors that are all deep pedigree investors.
And it's public information that I think are key investors, Fidelity, Dell Technologies, Amplify Partners, and recently we extended around and added in Maverick and also Point72. So these are a few and these are household names as it comes to deep tech, and also companies with deep pockets. So having money always helps.
Having great people around you that know everybody and can connect you helps. Having a great board helps. And you need all of that to really go pull this off.
And so it's my day job to be raising money every day. I'm thinking about raising money every day. We have done well so far.
We also manage the money well. And I think we have carved ourselves out to be an industry-leading company. And I do think that I think at some point we'll be earning some more capital to further our growth and our growth.
Yeah. The other the other difficult thing is hiring good people. I mean, they're particularly when you have somebody like Nvidia, you know, vacuuming up people.
Has that been a challenge?
I would say it's been less of a challenge than I had expected. It would be my answer. Again, hiring is really difficult.
Hiring good people is harder. Hiring amazing people is even harder. And in a startup, you better have amazing people.
And how do you get 200 people to do something that tens of thousands are doing, right? And it's not just amazing people, amazing people that are good team players. So you do the and function of all of this.
You kind of come back to a very small universe of human beings that really fit all of that. And what we do is not just chips, it's software, it's AI, it's computer vision, it's automotive. Not easy thing to go to.
And so what's really helped us is network. I've spent 30 years. I've known a lot of good people that collectively believed in me and I believed in them.
And so there's a network, not just me, everybody that's around me has a network. And so the network's really helped a lot. The second thing is we're building something that's industry leading.
And I'm an engineer. You want to be part of a winning formula. You want to be part of a David vs. Goliath fight. You want a story in your life where you said, hey, we started with nothing and we built something that beat the very best. So we have done that now and that also attracts a lot of people and that people like success.
And they're like, wow, 200% company. And we have publicly validated that we are the best in class in the category that we are in. And people want to be a part of the winning problem.
So I would say it's been easier than I had expected, but every single hire is hard. Every single hire is something we pay a lot of attention to. And even now, though we are close to 200 people, I know everybody in the company and I kind of know their spouse and I know their children.
And we need that family environment to really attract more people. And then it's not just hiring, retention too is hard. And people in our trade are the most sought after personalities in software and hardware and AI.
And so it's not just hiring, but it's also retaining and creating an environment where it's motivating and they choose to stay and choose to really be part of a winning formula. So that's, I would say, you've covered fundrais, you've covered people, you've covered solving tough problems, you've covered customers and winning. And that's what I wake up to every day and it's my day job to make sure I play my part.
But luckily, I have amazing people around me that also do way better than me luckily. I'm really glad to see them become a good company.
Where do you see the chips going? I mean, we're getting into specialized accelerators. There's now, I had somebody from Western University in Australia.
I think that's the name of the university. They're building a brain scale, neuromorphic computer using FFPGA. Is that right?
Yeah.
Programmable arrays. And where do you see this going? Are we going to end up with a highly fragmented chip market where depending on your use case, you'll use one kind of a chip?
Or do you think that and then there's quantum chips? Sure. Is neuromorphic and quantum, do you think that they're going to eventually take a big share of the market away from the market?
Great question, Craig. And hard to predict the future because you're probably going to be more wrong than right. And with that caveat out there, so what actually motivates architectural choices very rarely silicon alone.
It's actually software. And so part of the reason why neuromorphic and quantum, though these are not new concepts, they've been around for a long time, is the ability to scale software to deliver the eventual performance and power that you need with the ease of use. It always ends up being the case.
And case point, neural networks are not new. AI is not new. It's been talked about from Turing Times 100 years ago.
End of the day, it's math. It's all Newtonian calculus end of the day. And so you need to really wait for the software maturity and the right silicon ability to deliver that.
That's really the form of where things are. My observation is that I think everything gets hyped a little too much too quick. And things take way longer than people estimate.
And what people underestimate is, how do you scale a proof point? And so a proof point is easy. How do you scale a proof point to becoming an industry standard?
And it always is 10 to 15 years longer than people estimate. So I have no doubts that there is a large portion of a future that's going to be a combination of some version of technologies we have today. No doubts neuromorphic has a play, no doubts analog has a play, no doubts quantum computing has to be a part of it.
And each one brings various different benefits. But they also have large deltas of things that need to be solved for scaling. A proof point doesn't make a product.
Yeah. And so that's really where the gap's at. So I definitely think that the world will have a plethora of choices ahead of it.
And to play this out, there's also biocomputers, DNA computing. And so there's a lot, I think, still ahead of us. And I would say, what I think I foresee for the next 10 plus years is still going to be the mainstream technology driving, or the known that we have today, still being the majority of the deployments, maybe 95, 99 percent of all the deployments.
But I think 10, 20, 30 years old, I think there will be an opportunity for newer elements to come together. So that's my jaded 30 years of seeing this and expecting and hoping and things being delayed story. But I think I'm a little more right on this than wrong, I think.
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no subject
And right now, it's, I would say, across the board. And I'll give you the spectrum, and then I'll amplify the areas where I believe that's going to be the highest traction. So we are engaged with the top five customers in robotics, top five customers in the government sector, the aerospace and defense sector, automotive, medical, transportation tech, agricultural technologies, and also a category of smart vision, that's a Venn diagram, oral app or industrial automation, right?
So visual inspection, factory flow automation. So these are all the applications, and we have as a company in the last five and a half years, engaged with the top customers in each one of these market segments. Play this out five years from now, where will we see the highest volume, highest growth?
I think clearly, automotive, just by the nature of it, is going to be a key area of focus for us and the driver. Right behind it, I estimate would be robotics. I think there is a resurgence of a lot of focus on robotics.
COVID brought a lot of the supply chain issues and the legacy architectures coming in the way of global productivity in a big way. But I also think that there's a lot of articles written up on labor shortages globally. And people really want to bring in a lot of automation into the factory floor environments.
So you're going to see a lot of AMRs or robotic environments across quite a few warehouses. There's a lot of talk around humanoid robots. This is a new area of development.
Some of these may not pan out or as with everything in life, may take much longer than anybody's estimate. But the fact that I think robotics is going to play a very large portion of our lives, that's a given.
Yeah.
With these edge applications, they work with the Cloud, right? I mean, they're not intended to work independent of the Cloud, are they?
It depends on the customer's architecture. Take, for example, R-chip. R-chip is capable of working independent of the Cloud.
So you could fundamentally train an application, and you could infer that at the edge. There is really no need for the application to be connected to the Cloud, unless you choose to do so, right? And so the application is fully capable of being entirely independent, running on its own with no connectivity.
And many applications, really if you think through it in the real world, may not have connectivity elements, and or may struggle to get connectivity. And you don't want to be dependent on the connectivity alone, right? So we built a chip that's entirely capable of being self-managed, and being out there with no need for a Cloud connectivity.
But if the customer chooses to have a Cloud connectivity, either for updating the algorithms, or to really do a nightly upload of information or analytics, we enable that also.
Yeah. Are you working with, I would assume you are with many drone manufacturers, because this sounds like what you would need on drones.
Absolutely. And so we have built a platform that is the best in class in performance and power, and the programming environment we believe is the best ease of use in the industry compared to our peers, if you will. And drones are a poster child that needs all three.
They want the highest performance, the longest flight time, lowest battery consumption. And I would say we are better poised to serve that compared to anybody else. And so absolutely, we are engaged with the market leaders on unmanned aircrafts and drones.
And we see a lot of good traction for technology in that market.
Yeah. And the processing that's taking place is computer vision and analytics and control, I guess. Are there others that I'm not thinking of?
No, I think there is also navigation.
Right.
You could argue navigation fits in the context of computer vision. So there is fundamentally a camera subsystem or some kind of a LIDAR radar subsystem. So gathering location-specific data and you're computing and you're making decisions.
So it's a combination of computer vision, perception, localization, segmentation, and really distributing the workload, both from an AI context, but also into classic computer vision. And you also have control plane functions to watch your flight navigation, and really ensuring that I think you're combining all that into a single chip. And this is kind of what we do well.
And given that we are a heterogeneous computer platform, we do more than AI workloads. And so you could actually put the control plane, the navigation, the decision-making, and have it all work on a single chip.
no subject
I'm glad I'm not the only one that struggles with that.
Yeah, that's right. How large are the chips? Because certainly, you know, the Nvidia packages or systems are, you know, getting, you know, you need a truck to move them.
And they're certainly not going to fly in a drone. So how large are your chip packages?
We are really big. That's it. And so you can almost visualize what I see in my thumb.
That's about the size of what we need to have. And that's what we deliver. And so we, that's the chip.
We also provide bold form factors so that customers can easily integrate that into our existing structures. And one of the benefits in having spent 30 odd years is I've spent a lot of time studying, not just me, our entire team, what we need to be at in terms of cost, power, form factor. And we have put all of that into really what we have built eventually.
And I think the opportunity we have had is we have built something from grounds of purpose built. I am not a public company that's got a lot of legacy. I have zero legacy.
So we have said, hey, this is our learning. This is what we need to do. And we have raised a good amount of capital.
And we said, let's put the capital that we could use and build something really for the customers.
The other side of what's happening in the chip world are the foundries. You're designing chips, but you need a foundry to etch the chips. And, you know, there's various companies are building foundries for various types in the United States.
But for the time being, TSMC and Taiwan really is the one place where you can get this done. How do you get capacity with them?
I keep joking that though we're in the technology business, it increasingly more and more is a relationship business. And one of the side benefits of growing old is you get to know a lot of people that are all in key decision making positions at all these companies. A very, very small company.
We are fantastically happy with the partnership we have with TSMC. They've been an amazing partner to us from day one. And they've given us and they've made us feel like a big public company.
And so I'm very lucky that our problems are all demand related and not supply related. And so we have worked very hard with them and we have done a good job in managing the inventory needs and the market demand and really planning well. And I would say I think it's never an easy thing to do, but you've done something for 30 years, you tend to become reasonable at it.
And so I think the team is a very well-qualified team, but we won't be here without our partnership with TSMC. So we're very proud of what we've done together with them.
no subject
And what size are you at? And are you looking, I would presume you are looking at the new founders being built and is your architecture something that could be produced at any foundry or is it a particularly, particular kind of foundry that you would need?
Great set of questions. I think one of the key things we decided to do early on was we recognized that our software-centric approach gave us a lot of opportunity to get better performance and power. We decided to scale back in what you referred to as process technology.
And so we created our Gen 1 silicon product at 16 nanometer, 1.6. And this is at least 10 to 12 year old technology. So we did not want to take very advanced process technologies and take a lot of risk.
There's also a cost equation and a development equation. And as you get more aggressive or more newer nodes, the cost, the mask set to reproduce the chip, but also the development cost both really go up quite a bit. So Gen 1, we said, hey, we're getting amazing performance and power compared to anybody else.
And in real applications, we're 10x of the very best companies. So we said, let's stay back in process technology in Gen 1. We did 16 nanometer.
And in Gen 2, which we have now gone public, we have announced that we'll be at 6 nanometer. So we'll be getting a 2x improvement over what we have done in Gen 1 on a performance per watt, right, which is a huge leap. Typically in our business, you get 10-15% improvement, Gen 1 to Gen 2.
For us to get a 100% leap is pretty phenomenal. And we now feel like we have the right opportunity to do it, and our customers will usually derive the benefits of it. And to answer your question, we are tracking very closely where we get our chips manufactured, and we have the luxury of getting them manufactured now in the US as well.
And at the appropriate time, we'll take full advantage of every opportunity that we have. And within TSMC, I think we definitely have the choice of being manufactured any place. And just one thing is, and I think we are, our business doesn't work in that you build a design and you could go to anybody.
And so, yes, at a design implementation level, I think you have that opportunity. But I think once you get into the chip development, you fundamentally locked into one entity. That's typically how our companies work, and we are too small to play with too many players.
And our volumes are too low to really play the game. And if you redo it, it's uneconomical or economically not viable. And so I think we really want to work with the best in class, and TSMC is as good as it gets.
And they have done a phenomenal job, and they truly understand that this is a services business. And even today, I'm very impressed that as a startup, we get the same attention, if not perhaps more than a public company. And so all of those really are huge positives.
no subject
So we are deployed. I would still say it takes a long time in our business to really scale. Like the cloud business or the consumer business, where the design and cycle is fast, the embedded space thinks takes a long time.
But then the other positive is that they stay for production for 15, 20 years. So it's a game of inertia. Getting in is pretty hard, and the opportunity to stay in production is also pretty significant.
So we have quite a few customers that are moving to production with us globally. And over the next year or two, we are excited about scaling more and more customers to get into production with us.
Yeah. And how many people are at the company right now? And how do you scale a company like this?
Because as you said, the demand is massive.
We are about 160 of us today. And with a lot of consultants, I think, or contractors, we are on 200. So I would say wrongly, we are 200 people working at the company.
We are lean. We are credit lean for what we are doing. And it really is kudos to everybody that works here in that it's a startup and we do whatever it takes to make things happen.
And we are in some ways doing what many companies use, tens of thousands of people to get done. And I'm a big, big admirer of everybody that we have here. I'm biased and these are all more than employees, family for us and that we do whatever it takes to go make things happen.
The macro thing that is a priority for us is scaling. Is scaling our go-to-market and how do we touch 40,000 customers in scaling our go-to-market partners that we have, reps and distributors and VARs and ODMs and ISVs. And again, I go back to not only myself, but I think we have had a lot of experience scaling businesses in our career before.
And so we retain the core of the company to be small. But through a partner network, we expand our footprint and where we go look to. The underlying thing that really enables us, Craig, is really our software.
And more self-managed the software is, the more the customers can manage themselves. That's a large, large component of how we can enable the scaling. If every one of them needed a hand holding, we don't have a company.
One day, I think, we are going to touch tens of thousands of customers and it will be a very exciting scaling opportunity for us.
Yeah. And the biggest market, I would assume right now is the United States, but I don't know. I mean, this is a global phenomenon.
Absolutely.
I think by footprint, North America would be the largest market for us, no doubts. But we are enjoying the benefit of our customer traction in Europe, Japan, in Korea and India too. And about 70 of our team members are based in Bangalore in India.
And we also are building out sales and go to market activities in India. And I think India is going to be a massive growth, in general, a doctor of AI. And we feel like we are one of the leaders and pioneers in this category of edge market scaling.
And I am quite convinced that I think in the next 10 years, this is going to be a high priority for every nation, a high priority for every industry sector. And people that don't have an AI-enabled environment are going to be left behind. And I think it's a matter of now who's wanting to gain leadership position.
There's going to be a fear of missing out that's going to go through the entire customer base.
Yeah. And you were talking about how I'm going to avoid the word again, but how you use your chip is not specialized one particular application. But is there an application that at some point it seems, if not in the design of the chip in scaling your sales and marketing and all of that, you've got to focus on a few applications and let the others come to you.
Which are you guys focused on?
I would say robotics, industrial automation, and vision systems. If you really do a Venn diagram of those three, I think that'd be a key gravity area for us. And I should expand on that and saying, every day our struggle is specificity versus generality.
So we've got to really make this balance happen. And I've built products before that will work for 40,000 customers, where you build one thing, every one of them is doing something radically different than the other, but it all still ends up being mostly the performance, mostly the power, mostly the cost that they need. Not easy to go to.
And we have learned and built good businesses earlier in our career, and we have used that experience to build it. And I would say, though I explained our gravity point of our highest volume, where I think we're going to drive, most people are going to find out that I think we are better than everybody else for their application as well, and all the other market segments we've already talked about.
Yeah, this wasn't, I wasn't going to ask this, but it just occurs to me on this question of scaling. You know, the big boys are all chasing this market as well. What's your future?
Do you think you guys will end up as part of a larger, you know, Google or Nvidia or somebody at that scale? Or is your expectation to stay independent and grow to that scale?
Really good question. And I would maybe give you two or three things that I think maybe I should mention. One is what I've learned now in five and a half years, and all my career I've been in large public companies, and this is my very first startup.
I started and what I've really come to recognize and truly internalize this, it's not the size of the dog, but it's the size of the fight in the dog that matters. I've been in very large companies and I always wondered, my God, we need more to get things done. There are 200 people and we are doing things of 10,000, 20,000, 100,000 people companies.
When you really build yourself into an element of, this is our team and this is what we're going to go do, and this is our life and blood, you operate very differently. That's one thing. The second thing I should say is, I have no idea how to predict the future.
What I do know is if you have results, you have options. We have really submitted ourselves to not worry about what outcome is ahead of us. We don't know.
What I do know is if I drive results, I have outcomes. And if I don't have results, I don't need to worry about outcomes. And so we single-mindedly put our head down to really focus on driving to be the best in the category that we are in.
And we cannot be everything to everybody. We really need to focus and do a good job of what we do. And our company definitely has been interesting to a lot of people.
I think that should be a fair thing for me to validate. And I think it would be fair to say that I think we are definitely noticed by everybody, by our customers, by our peers. So what our future really holds?
TBD. When I wake up every day and go, there's one thing to get done, and I drive back home saying, yeah, we got that done today. And I'm happy.
Yeah. And this is getting off subject, but I'm curious about the fundraising journey. How easy was it to get the initial capital?
And are you still raising funds?
I would say two things. I think for a long time, investments in chips had dried up. Chips were no longer really a high priority and a focus just because of the investment amount needed to the return cycle.
It just didn't fit every C mold. And so almost from 2005 till maybe even 2016, 2018, there are hardly any chip startups. It's now a key gold rush, and there's an enormous amount of attention and span put into it.
And I would say raising money is hard. Anybody that starts a company, if you walk in assuming that raising money is easy, I would urge you just really pragmatically internalize that it's hard to do. But I also simultaneously held the notion that the right kind of idea, the right kind of system and a setup always is capable of attracting good capital in any circumstance.
And we've been very lucky. We have raised around 270 million so far. And we have amazing investors that are all deep pedigree investors.
And it's public information that I think are key investors, Fidelity, Dell Technologies, Amplify Partners, and recently we extended around and added in Maverick and also Point72. So these are a few and these are household names as it comes to deep tech, and also companies with deep pockets. So having money always helps.
Having great people around you that know everybody and can connect you helps. Having a great board helps. And you need all of that to really go pull this off.
And so it's my day job to be raising money every day. I'm thinking about raising money every day. We have done well so far.
We also manage the money well. And I think we have carved ourselves out to be an industry-leading company. And I do think that I think at some point we'll be earning some more capital to further our growth and our growth.
Yeah. The other the other difficult thing is hiring good people. I mean, they're particularly when you have somebody like Nvidia, you know, vacuuming up people.
Has that been a challenge?
I would say it's been less of a challenge than I had expected. It would be my answer. Again, hiring is really difficult.
Hiring good people is harder. Hiring amazing people is even harder. And in a startup, you better have amazing people.
And how do you get 200 people to do something that tens of thousands are doing, right? And it's not just amazing people, amazing people that are good team players. So you do the and function of all of this.
You kind of come back to a very small universe of human beings that really fit all of that. And what we do is not just chips, it's software, it's AI, it's computer vision, it's automotive. Not easy thing to go to.
And so what's really helped us is network. I've spent 30 years. I've known a lot of good people that collectively believed in me and I believed in them.
And so there's a network, not just me, everybody that's around me has a network. And so the network's really helped a lot. The second thing is we're building something that's industry leading.
And I'm an engineer. You want to be part of a winning formula. You want to be part of a David vs. Goliath fight. You want a story in your life where you said, hey, we started with nothing and we built something that beat the very best. So we have done that now and that also attracts a lot of people and that people like success.
And they're like, wow, 200% company. And we have publicly validated that we are the best in class in the category that we are in. And people want to be a part of the winning problem.
So I would say it's been easier than I had expected, but every single hire is hard. Every single hire is something we pay a lot of attention to. And even now, though we are close to 200 people, I know everybody in the company and I kind of know their spouse and I know their children.
And we need that family environment to really attract more people. And then it's not just hiring, retention too is hard. And people in our trade are the most sought after personalities in software and hardware and AI.
And so it's not just hiring, but it's also retaining and creating an environment where it's motivating and they choose to stay and choose to really be part of a winning formula. So that's, I would say, you've covered fundrais, you've covered people, you've covered solving tough problems, you've covered customers and winning. And that's what I wake up to every day and it's my day job to make sure I play my part.
But luckily, I have amazing people around me that also do way better than me luckily. I'm really glad to see them become a good company.
Where do you see the chips going? I mean, we're getting into specialized accelerators. There's now, I had somebody from Western University in Australia.
I think that's the name of the university. They're building a brain scale, neuromorphic computer using FFPGA. Is that right?
Yeah.
Programmable arrays. And where do you see this going? Are we going to end up with a highly fragmented chip market where depending on your use case, you'll use one kind of a chip?
Or do you think that and then there's quantum chips? Sure. Is neuromorphic and quantum, do you think that they're going to eventually take a big share of the market away from the market?
Great question, Craig. And hard to predict the future because you're probably going to be more wrong than right. And with that caveat out there, so what actually motivates architectural choices very rarely silicon alone.
It's actually software. And so part of the reason why neuromorphic and quantum, though these are not new concepts, they've been around for a long time, is the ability to scale software to deliver the eventual performance and power that you need with the ease of use. It always ends up being the case.
And case point, neural networks are not new. AI is not new. It's been talked about from Turing Times 100 years ago.
End of the day, it's math. It's all Newtonian calculus end of the day. And so you need to really wait for the software maturity and the right silicon ability to deliver that.
That's really the form of where things are. My observation is that I think everything gets hyped a little too much too quick. And things take way longer than people estimate.
And what people underestimate is, how do you scale a proof point? And so a proof point is easy. How do you scale a proof point to becoming an industry standard?
And it always is 10 to 15 years longer than people estimate. So I have no doubts that there is a large portion of a future that's going to be a combination of some version of technologies we have today. No doubts neuromorphic has a play, no doubts analog has a play, no doubts quantum computing has to be a part of it.
And each one brings various different benefits. But they also have large deltas of things that need to be solved for scaling. A proof point doesn't make a product.
Yeah. And so that's really where the gap's at. So I definitely think that the world will have a plethora of choices ahead of it.
And to play this out, there's also biocomputers, DNA computing. And so there's a lot, I think, still ahead of us. And I would say, what I think I foresee for the next 10 plus years is still going to be the mainstream technology driving, or the known that we have today, still being the majority of the deployments, maybe 95, 99 percent of all the deployments.
But I think 10, 20, 30 years old, I think there will be an opportunity for newer elements to come together. So that's my jaded 30 years of seeing this and expecting and hoping and things being delayed story. But I think I'm a little more right on this than wrong, I think.
By popular demand, Netsuite has extended its one-of-a-kind, flexible financing program for a few more weeks. Head to netsuite.com/eye On AI. That's Eye On AI, E-Y-E-O-N-A-I, all run together.
Again, head to netsuite.com/eye On AI. netsuite.com/eye On AI, where it's one-of-a-kind, flexible financing program.
From Eye On A.I.: #206 Krishna Rangasayee: Why Edge AI is the Next Big Thing in Tech, Sep 4, 2024
https://podcasts.apple.com/us/podcast/206-krishna-rangasayee-why-edge-ai-is-the-next-big/id1438378439?i=1000668396023
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