Ambarella, Inc. Ordinary Shares Citi Global TMT Conference

Right. Thank you, Kelsey. First of all, thank you for joining us today. Ambarella is a fabless semiconductor company started in 2004, and throughout the years we are starting focusing on digital video application. In the last 10 years, we really focused on building solution for edge AI processing. Basically, what we are saying is that we're building an SoC that integrate not only just an inference engine, but also image processing pipeline, CPUs, and the peripheral so that we can become the SoC for the whole system. There are so many different vertical we are targeting at. Anything related to the edge device which will require AI inference, we are basically in there. The biggest markets like enterprise security to the portable video to the telematics for automotive, and now we are talking about robotic application.

In the latest earning call, we talk about how to penetrate edge infrastructure with new partners like Capgemini and Magnica. Basically, we are really focusing on edge AI for the last 10 years, and hopefully the market can start taking off as people expected. But definitely, that's really what we are focusing on.

Right. First of all, I think all confidence is based on our engagement with our customers. In fact, all of the customers we talk to, they all want to put more and more AI performance into the edge device. 10 years ago, it started with a CNN type of neural network, now they moved to transformer, then moved to large language model. All of that are available in our silicon hardware and software platform. The one thing that became very obvious in the last 12, 24 months is everybody wants to continue increase the AI performance on their device, mainly because of the large language model. However, edge AI or physical AI, people have been really talking a lot about, but the biggest problem for this market today is there is no one vertical like coding for data centers, right?

Today, majority data center revenue is generated by one big application, but there is no such application at that edge. That is where our strategy always focuses on multiple different possible vertical, and hopefully one of them will grow. You talk about the acquisition, Analog Devices, Inc. just announced a deal, which will acquire a startup company for $1.5 billion, which has little revenue and their AI performance. By the way, the AI performance we offer at Ambarella is in a family between 1 TOP to 1,000 TOPS. Based on the public information I can find for that company, it is really about sub 1 TOP to 1 TOP type of performance. Yes, they are edge AI company, but there is a little bit overlap. We are generating $400 million revenue versus Synaptics.

I really think that is indication that edge AI is happening and a lot of the company said, "I need a roadmap," and they try to find a way to by using acquisition to fill the gap.

Mm-hmm. Obviously. Every time we try to build on a design win, the biggest differentiation for us is always performance per watt. That performance can be AI inference performance per watt or video processing performance per watt or other related functions per watt, right? At the end, it's power efficiency. We understand that, in fact, most of our customer, when they build their first-generation product, they use a GPU to do it, because it's easy to program, it's widely available to do that. But when some of the application they are using is really running to the barriers of power consumption, because some of the applications just require battery life or using a very limited power dissipation solution. From that point of view, power efficiency is the most important differentiation for us.

But second one is really that because our heritage is on digital video application, our digital video processing technology is better than I think most of the competitor, maybe all the competitors out there. That's another huge differentiation. But the third, I think a lot of people ignore, is really if we look at our product portfolio, we have 15 AI SoCs that we offer to our customer. But on top of that, there's a unified SDK called Cooper that cover the whole product line. Basically, if you design one product based on our chip using Cooper, you can easily move that same application to different silicon without too much of a modification. And that software architecture, I think, is critically important for our customer who has multiple product line to build and they don't want to reinvent the software from one product to another.

Right. You're talking about three type of competitors. NVIDIA's obviously, they can deliver really high performance. That's their strength. But like I said, GPU's power consumption has been well-documented problem, and we think that for our customer who really want to have a power efficient solution, GPU is not the best solution. From that point of view, we cover all that based on power efficiency. Qualcomm is a little bit different. Qualcomm is definitely more efficient than the GPU. However, when they compare to our approach, we still have a significant power efficiency. But on top of that, we continue. But because they are closer, we definitely have a lot of overlap with Qualcomm. We always view Qualcomm as the biggest competitor to us. Synaptics is different. Synaptics just, they came into play this AGI 2 years ago by acquiring product line, and their coverage is really from 1 TOPS to maybe 10 TOPS type of application.

Yes, there are some overlap, but it is not a lot. From my point of view, we do not run into Synaptics that much, but when we go out to compete, we run into NVIDIA and Qualcomm all the time.