OFC 2025: industry reflections
Gazettabyte is asking industry figures for their thoughts after attending the recent 50th-anniversary OFC show in San Francisco. Here are the first contributions from Huawei’s Maxim Kuschnerov, NLM Photonics’ Brad Booth, LightCounting’s Vladimir Kozlov, and Jürgen Hatheier, Chief Technology Officer, International, at Ciena.
Maxim Kuschnerov, Director of R&D, Huawei
The excitement of last year’s Nvidia’s Blackwell graphics processing unit (GPU) announcement has worn off, and there was a slight hangover at OFC from the market frenzy then.
The 224 gigabit-per-second (Gbps) opto-electronic signalling is reaching mainstream in the data centre. The last remaining question is how far VCSELs will go—30 m or perhaps even further. The clear focus of classical Ethernet data centre optics for scale-out architectures is on the step to 448Gbps-per-lane signalling, and it was great to see many feasibility demonstrations of optical signalling showing that PAM-4 and PAM-6 modulation schemes will be doable.
The show demonstrations either relied on thin-film lithium niobate (TFLN) or the more compact indium-phosphide-based electro-absorption modulated lasers (EMLs), with thin-film lithium niobate having the higher overall optical bandwidth.
Higher bandwidth pure silicon Mach-Zehnder modulators have also been shown to work at a 160-175 gigabaud symbol rate, sufficient to enable PAM-6 but not high enough for PAM-4 modulation, which the industry prefers for the optical domain.
Since silicon photonics has been the workhorse at 224 gigabits per lane for parallel single-mode transceivers, a move away to thin-film lithium niobate would affect the density of the optics and make co-packaged optics more challenging.
With PAM-6 being the preferred modulation option in the electrical channel for 448 gigabit, it begs the question of whether the industry should spend more effort on enabling PAM-6 optical to kill two birds with one stone: enabling native signalling in the optical and electrical domains would open the door to all linear drive architectures, and keep the compact pure-silicon platform in the technology mix for optical modulators. Just as people like to say, “Never bet against copper,” I’ll add, “Silicon photonics isn’t done until Chris Doerr says so.”
If there was one topic hotter than the classical Ethernet evolution, it was the scale-up domain for AI compute architectures. The industry has gone from scale-up in a server to a rack-level scale-up based on a copper backplane. But future growth will eventually require optics.
While the big data centre operators have yet to reach a conclusion about the specifications of density, reach, or power, it is clear that such optics must be disruptive to challenge the classical Ethernet layer, especially in terms of cost.
Silicon photonics appears to be the preferred platform for a potential scale-up, but some vendors are also considering VCSEL arrays. The challenge of merging optics onto the silicon interposer along with the xPU is a disadvantage for VCSELs in terms of tolerance to high-temperature environments.
Reliability is always discussed when discussing integrated optics, and several studies were presented showing that optical chips hardly ever fail. After years of discussing how unreliable lasers seem, it’s time to shift the blame to electronics.
But before the market can reasonably attack optical input-output for scale-up, it has to be seen what the adoption speed of co-packaged optics will be. Until then, linear pluggable optics (LPO) or linear retimed optics (LRO) pluggables will be fair game in scaling up AI ‘pods’ stuffed with GPUs.
Brad Booth, CEO of NLM Photonics
At OFC, the current excitement in the photonics industry was evident due to the growth in AI and quantum technologies. Many of the industry’s companies were represented at the trade show, and attendance was excellent.
Nvidia’s jump on the co-packaged optics bandwagon has tipped the scales in favour of the industry rethinking networking and optics.
What surprised me at OFC was the hype around thin-film lithium niobate. I’m always concerned when I don’t understand why the hype is so large, yet I have still to see the material being adopted in the datacom industry.
Vladimir Kozlov, CEO of LightCounting
This year’s OFC was a turning point for the industry, a mix of excitement and concern for the future. The timing of the tariffs announced during the show made the event even more memorable.
This period might prove to be a peak of the economic boom enabled by several decades of globalisation. It may also be the peak in the power of global companies like Google and Meta and their impact on our industry.
More turbulence should be expected, but new technologies will find their way to the market.
Progress is like a flood. It flows around and over barriers, no matter what they are. The last 25 years of our industry is a great case study.
We are now off for another wild ride, but I look forward to OFC 2050.
Jürgen Hatheier, Chief Technology Officer, International, at Ciena
This was my first trip to OFC, and I was blown away. What an incredible showcase of the industry’s most innovative technology
One takeaway is how AI is creating a transformative effect on our industry, much like the cloud did 10 years ago and smartphones did 20 years ago.
This is an unsurprising observation. However, many outside our industry do not realise the critical importance of optical technology and its role in the underlying communication network. While most of the buzz has been on new AI data centre builds and services, the underlying network has, until recently, been something of an afterthought.
All the advanced demonstrations and technical discussions at OFC emphasise that AI would not be possible without high-performance network infrastructure.
There is a massive opportunity for the optical industry, with innovation accelerating and networking capacity scaling up far beyond the confines of the data centre.
The nature of AI — its need for intensive training, real-time inferencing at the edge, and the constant movement of data across vast distances between data centres — means that networks are evolving at pace. We’re seeing a significant architectural shift toward more agile, scalable, and intelligent infrastructure with networks that can adapt dynamically to AI’s distributed, data-hungry nature.
The diversity of optical innovation presented at the conference ranged from futuristic Quantum technologies to technology on the cusp of mainstream adoption, such as 448-gigabit electrical lanes.
The increased activity and development around high-speed pluggables also show how critical coherent optics has become for the world’s most prominent computing players.
Will AI spur revenue growth for the telcos?
- A global AI survey sponsored by Ciena highlights industry optimism
- The telcos have unique networking assets that can serve users of AI.
- Much is still to play out and telcos have a history of missed opportunities.
The leading communications service providers have been on a decade-long journey to transform their networks and grow their revenues.
To the list of technologies the operators have been embracing can now be added artificial intelligence (AI).
AI is a powerful tool for improving their business efficiency. The technology is also a revenue opportunity and service providers are studying how AI traffic will impact their networks.
“This is the single biggest question that everyone in this industry is struggling with,” says Jürgen Hatheier. “How can the service providers exploit the technology to grow revenues?”
However, some question whether AI will be an telecom opportunity.
“The current hype around AI has very little to do with telcos and is focused on hyperscalers and specifically the intra-data centre traffic driven by AI model training,” says Sterling Perrin, senior principal analyst at HeavyReading. “There is a lot of speculation that, ultimately, this traffic will spread beyond the data centre to data centre interconnect (DCI) applications. But there are too many unknowns right now.”
AI survey
Hatheier is chief technology officer, international at Ciena. He oversees 30 staff, spanning Dublin to New Zealand, that work with the operators to understand their mid- to long-term goals.
Ciena recently undertook a global survey (see note 1, bottom) about AI, similar to one it conducted two years ago that looked at the Metaverse.
Conducting such surveys complements Ciena’s direct research with the service providers. However, there is only so much time a telco’s chief strategy officer (CSO) or chief technology officer (CTO) can spend with a vendor discussing strategy, vision, and industry trends.
“The survey helps confirm what we are hearing from a smaller set,” says Hatheier.
Surveys also uncover industry and regional nuances. Hatheier cites how sometimes it is the tier-two communications service providers are the trailblazers.
Lastly, telcos have their own pace. “It takes time to implement new services and change the underlying network architecture,” says Hatheier. “So it is good to plan.”
Findings
The sectors expected to generate the most AI traffic are financial services (46 per cent of those surveyed), media and entertainment (43 per cent), and manufacturing (38 per cent). Hatheier says these industries have already been using the technology for a while, so AI is not new to them.
Sterling Perrin
For financial services, an everyday use of AI is for security, detecting fraudulent transactions and monitoring video streams to detect anomalous behavior at a site. The amount of traffic AI applications generate can vary greatly. This is common, says Hatheier; it is the use that matters here, not the industry.
“I would not break it down by the industries to say, okay, this industry is going to create more traffic than another,” says Hatheier. “For financial services, if it is transaction data, it’s a few lines of text, but if it is video for branch security, the data volumes are far more significant.”
AI is also set to change the media and entertainment sector, challenging the way content is consumed. Video streaming uses content delivery networks (CDNs) to store the most popular video content close to users. But AI promises to enable more personalised video, tailored for the end-user. Such content will make the traffic more dynamic.
Another example of personalised content is for marketing and advertising. Such personalisation tends to achieve better results, says Hatheier.
AI is also being applied in the manufacturing sector. Examples include automating supply-chain operations, predictive maintenance, and quality assurance.
Car manufacturers check a vehicle for any blemishes at the end of a production line. This usually takes several staff and lasts 10-15 minutes. Now with AI, the inspection can be completed as the cars passes by. “This is a potent application that could run on infrastructure within the manufacturing site but use a service provider’s compute assets and connectivity,” says Hatheier.
The example shows how AI produces productivity gains. However, AI also promises unique abilities that staff cannot match.
Traffic trends
If the history of telecoms is anything to go by, applications that drove traffic in the network rarely lead to revenue growth for the service providers. Hatheier cites streaming video, gaming, and augmented reality as examples.
However, the operators have assets at network edge and the metro that can benefit AI usage. They also have central offices that can act is distributed data centres for the metro and network edge.
Hatheier says users have an advantage if they consume AI applications across a fibre-based broadband network. But certain countries, such as Saudi Arabia and India, mainly use wireless for connectivity.
“AI applications will need to adapt to what is available, and if people want to consume low-latency applications, there is 5G slicing,” says Hatheier. “At the end of the day, there is no way around fibre.”
Optical networking
Government policy regarding AI and regulations to ensure data does not cross borders also play a part.
“It’s an important decision criterion, as we saw in the survey response,” says Hatheier. “So private AI and local computing will be an important decision factor.”
Another critical decision influencing where data centres are built is power. “We see all the gold rush in the Nordics right now with their renewable power and cool climates,” says Hatheier. “You don’t need to cool your servers as much, and it requires a lot of connectivity.”
However, as well as these region-specific data centre builds, there will also be builds in metropolitan areas using smaller distributed data centres.
“Let’s say there are 20 sizable edge or metro compute centres for AI, and you would need three or four to run a big training job,” says Hatheier. “You will not create a permanent end-to-end connection between them because sometimes there will not be four that need to work together, but five, seven, and 11.”
Such a metro network would require reconfigurable optical add-drop multiplexer (ROADM) technology to connect wavelengths between those clusters based on demand to keep sites busy, to avoid expensive AI clusters being idle.
These are opportunities for the CSPs. And while much is still to happen, such discussions are taking place between systems vendors and the telcos.
For Heavy Reading’s Perrin, the more telling opportunity is the telcos’ own use of AI rather than the networking opportunity.
“As a vertical industry, telecom is not typically a leading-edge adopter of any new technology due to many factors, including culture, size, legacy infrastructure and processes, and government regulations,” he says. “I don’t believe AI will be any different.”
Hatheier points to the survey’s finding of general optimism that sees AI as an opportunity rather than a challenge or business risk.
“We have seen very little differences between countries,” says Hatheier. “That may have to do with the fact that emerging countries get as much attention of data centre investment than more developed ones.”