Coherent Corp. The Six Five Summit: AI Unleashed 2026
Review the key takeaways and the transcript of this earnings call.
- The discussion focused on the deployment and adaptability of robots in manufacturing, particularly emphasizing the ability of robots to learn from their environment and make adjustments autonomously, such as improving weld quality and triggering preventive maintenance.
- Intel highlighted its platform as capable of training, simulating, and deploying robotics solutions in a flexible and adaptive manner, which is a fundamental shift in robotics deployment.
- Intel continues to advance hardware architectures, including CPUs with integrated GPUs and NPUs, to optimize performance, power, and cost for robotics applications.
- The company emphasizes real-time and deterministic control as foundational for both traditional and future robots.
- Intel is committed to openness in software and hardware solutions, working with a wide ecosystem of partners to support diverse market categories and enable scalable innovation.
- Executives expressed optimism about the future of humanoid robots in homes, with predictions ranging from 2028 to 2036 for their potential arrival.
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Transcript
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Joining us is Sanjai Parthasarathi, Chief Marketing Officer at Coherent. Sanjai, thanks for joining me on this Six Five Summit. It's going to be a fun conversation.
Yeah. Thanks, Matt. It's great to talk to you again and really great to be here.
Let's jump right in, all right, because there's a lot to cover. Of course, networking has become the bottleneck that everybody has been pointing to. In that kind of world of networking, everyone's gotten really comfortable with this concept of scale up and scale out, right? Terms that nobody talked about three years ago, everybody is talking about today. Now we're hearing about scale across. I think a lot of folks I speak with out in the marketplace, when I say that, there's a little bit of like, "Hmm, what do you mean by that?" Right? When we talk about scale across, what exactly are we talking about, and why is this all of a sudden showing up everywhere in AI infrastructure conversations?
At its core, Matt, it's all about optical communications, right? I've been in the optical communications, optical networking industry for almost 30 years, and I can tell you, this is perhaps the most exciting time in photonics and optical networking. Now coming back to optical communications. People have been communicating with light is not new. The Phoenicians were signaling with light thousands of years ago, right? It's not something new. Jokes apart, modern communications began with the telegraph. That connectivity was all electrical. But when you need to go longer distances or you want to go at higher speeds or a combination of higher speeds and longer distances, the only way to do it is optical. The physics demands that you drive towards optical. So today, most of the world's communications networks are all on an optical backplane, right? That's the backbone of the optical communications networks.
Let me give you an example. You pick up your phone and let's say you're sending a photo or you're talking to your friend in Singapore. The first talk between your phone and the RF tower is RF signals. But at the base of every one of those RF towers these days is an optical transceiver. So that takes electrical signals, converts them to optical signals, and pushes it through the fiber network. From that point on, your data, your voice is in the optical domain. It goes through the access networks, the metro networks, the long-haul networks, and some point of time, because the signal needs to go to Singapore, you enter a submarine cable landing station. There is one 100 miles from where we are right now. Where I am right now, there is a submarine cable that goes all the way to Singapore.
Your signals go through the submarine cable. Then when it comes to Singapore, then you have the same old distribution, and then it comes into the RF tower and back to the phone. All of that is optical. By the way, Coherent, we have one of the broadest and deepest portfolios in the optical industry. We have the photonic components and modules that enable you to do all of that, right? All of those components that you need from this one end of cell tower to the other cell tower, we are able to provide. Now, let me come back to scale across, right? You started by asking scale across. Now, what's scale across? Data centers are power constrained. You know that. That's the single-- Any discussion on the data center, it starts with energy. It's about energy efficiency, et cetera.
When you have large AI workloads, now these workloads are being forced to be spread across multiple data centers because there's just not enough power in one data center to process these large workloads. So that in turn drives a demand for these very high bandwidth connections between the data centers.
That's what we call, the industry has started to refer to that as scale across networks.
Okay, this is really interesting, right? This concept of scale across. Let's put this in the real world, okay? I am a frontier model provider. I have got a training run that is spanning across multiple data centers. When that happens, that networking problem is entirely different than plugging cables from one rack to another, right? So in that equation, what optical technology becomes non-negotiable for me? And part two to that is, if I am the person that is designing that network, what are the things I should be focusing on most closely? What are those specs I should be really paying attention to as I design that network out?
Let me just start by saying optical networks have been becoming increasingly disaggregated over the years. Large monolithic systems have been sort of giving way to smaller, easy-to-deploy functional elements or functional blocks. There are two important functional blocks for scale across. One is data center interconnect transceivers, or DCI. Just by the definition, these are transceivers that sit at the edge of a data center. They are high bandwidth, high capacity transceivers that take electrical signals, convert them to optical signals, and then shoot it across to the next data center. But equally important is another class of equipment that is called optical transport equipment, and that equipment sits in between the two data centers. And again, as the name implies, optical transport equipment helps transport the optical signal. And you say, what does that mean?
Well, when you launch an optical signal into a fiber, after the signal goes for a certain distance, it starts to die down. It attenuates. So you need amplifiers to boost the signal again.
You need signal conditioning. You need to monitor the strength of the signal, the health of the signal. You need to monitor the health of the fiber infrastructure. So all of those functions are being done by this transport equipment. So it is a pretty important class of equipment. So two main functional blocks, data center interconnect transceivers and transport equipment. Your question on what is it, what are the performance metrics, right? What is it? Yeah that customers care about?
Again, for the past 30 years, the longest I have been in this market, it always starts with bandwidth. Bandwidth, bandwidth, and then energy efficiency. That has been the mantra for quite some time. Other things like reliability are all a given. They are like table stakes. But in the AI data center context, it is a really big focus on energy. So customers are looking at how we can improve every little bit of energy efficiency within this equipment.
Sanjai, this is interesting, and I have to say, as an analyst in the industry, and I think even casual observers who are playing out in the market, we keep hearing more and more about optical networking and more and more players entering the space, right? You mentioned Coherent has a very solid position and a really robust portfolio. But within that context, tell me what makes Coherent unique. What separates Coherent from everybody else in this space?
Coherent, we have one of the broadest and deepest portfolios in the industry. It is not just the breadth of the portfolio. We have a deep vertically integrated technology stack, and that technology stack, Matt, goes all the way down to the material cell. We are a company of innovation, right? We have about 50 years of innovation, a long track record of bringing industry first advances to the industry. Many cases where our products have actually created a new market segment for the industry. AI is just challenging the industry to innovate at all levels of the value chain. That is a big differentiator for us because we have all the platforms within the company, and we are deeply vertically integrated. So when we develop our solutions, they are kind of tailor-made with innovation all the way down to the materials level and up to the systems level.
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