Why media networks are being rewired for the speed of light

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The elimination of OB trucks is just the start of the light revolution. For the media industry, a rewiring of the transport network from electrons to photons promises to unlock AI‑driven production, immersive formats, and globalised workflows while dramatically cutting energy consumption.

“Bandwidth demand has exploded,” says Dr. Masahisa Kawashima, IOWN Technology Director at Japanese telco NTT. “What used to be less than one gigabit per customer is now tens of gigabits for media applications, and hundreds of gigabits for AI workloads.”

Momentum is building behind photonics – laser light - as replacement for electronics. An All Photonics Network (APN) has gained the support of 170 major telcos, device and chip vendors and internet powerhouses including Nokia, Ericsson, Orange, KDDI, Intel, Nvidia, Cisco, Ciena, Samsung, Sony, Microsoft and Google under the Innovative Optical and Wireless Network (IOWN) Global Forum.

“UHD contribution, multi‑camera remote production, VR capture, and AI‑assisted workflows have all accelerated bandwidth demand far beyond what legacy electrical switching architectures were designed to handle,” says Kawashima, who is also Chair of the IOWN Global Forum’s Technology Working Group. “At the same time, AI workloads, particularly large‑scale model training and inference, have introduced traffic patterns that are both bursty and massive, often exceeding hundreds of gigabits per second per node. The bottleneck is the network.”

Optical transport technologies have long been used to connect routers and switches in data networks. Traditionally, these routers and switches connect electrically through a telecom carrier’s optical transport system. But bandwidth demand is reaching a point where this model is no longer efficient.

The IOWN initiative proposes to move long‑distance optical transport capabilities directly into customer premises equipment (CPE), enabling end‑to‑end photonic paths with minimal electrical conversion.

“Optical transport technology has evolved to the extent that it’s both practical and cost effective to deploy long‑distance optical systems directly at customer sites,” he says.

For decades, electrons have been the carriers of data inside devices, performing all computation and routing. But electrons come with limits: heat generation, power inefficiency, and bandwidth bottlenecks. Every time a signal switches between optical and electronic domains, latency and energy cost increase.

Photonics replaces some of these electrical pathways with optical ones, allowing data to travel at the speed of light while reducing energy consumption dramatically.

The result, according to NTT, is to reduce power consumption to one-hundredth of existing output, increase data capacity 125 times and slash network latency to a fraction of a percent of its current levels.

True virtual remote production

For broadcasters and live‑production companies, the implications are profound. Media networks are increasingly indistinguishable from data‑centre networks. Today’s live production workflows still rely heavily on outside broadcast vans, specialist crews, and on‑site infrastructure.

“OB vans are expensive, and broadcasters can only own a limited number,” Kawashima says “Skilled editing crews are another bottleneck.”

APN changes the equation, he claims. By enabling direct, high‑bandwidth optical connectivity from venues to centralised production hubs, “APN removes the need for OB vans and dramatically reduces on‑site staffing. The result is a more flexible, scalable, and financially sustainable model.”

By eliminating the buffering resulting from optical-to-electrical-to-optical conversions in current networking latency is deterministic – ideal for live cloud switching.

“In media production, from multi-camera sports coverage to immersive, free-viewpoint experiences, precise synchronisation is critical,” says ,” Katsutoshi Itoh, Chair of the Use Case Working Group at IOWN and head of Sony’s Swedish R&D lab. “Even minor latency variations can disrupt 3D reconstruction and real-time interactivity. APN means predictable, tightly controlled timing across the network.”

This shifts the bottleneck from physical logistics to network provisioning and unlocks the long‑tail of live content. “With lower production overheads, broadcasters can cover more events (local sports, niche competitions, cultural performances) that were previously uneconomical.”

Tests have been made: Sony and Japanese broadcaster TBS claimed the first successful remote production a live music event using APN. 64 audio streams from The Japan Record Awards held at Tokyo’s New National Theatre were relayed for remote production to TBS’s Akasaka studio with a roundtrip of 5 milliseconds.

Enabling AR, holography, and 6DoF video

Emerging formats such as 6DoF video, volumetric capture, holographic replay and AR overlays for live events require multi‑camera arrays and significant AI compute. These workloads generate enormous traffic between capture nodes and compute clusters.

“APN is essential for these,” says Kawashima. He points to the VAR-style Automated Balls and Strikes (ABS) challenge system introduced for MLB baseball coverage this season. It uses 12 Hawk-Eye cameras placed around the stadium that continuously track the baseball in 3D.

“AI synthesises entirely new viewpoints—angles that no single camera could capture,” he says. “This six‑degree‑of‑freedom video experience is a glimpse of what’s coming. APN provides the bandwidth and low latency needed to make them practical.”

How APN integrates with today’s networks

Crucially, APN does not require ripping out existing carrier infrastructure. Instead, it changes where the optical transceivers live.

The key component are Dense Wavelength Division Multiplexing (DWDM) transceivers that convert electrical signals into optical signals and vice versa, using multiple wavelengths to send information through a single fibre optic cable.

Carriers already operate optical transport systems, and those remain in place. The difference is where the optical transceivers sit. Today, they are installed in the carrier’s transport equipment. In APN, the transceivers are installed directly in the customer’s routers and switches, which then connect directly to the carrier’s optical infrastructure.”

“The most efficient method,” Kawashima explains, “is to connect customer routers and switches directly to a DWDM optical network. Directly connecting customer routers and switches with optical transport transceivers is already feasible today.”

Optical transceivers themselves are currently more expensive, but Kawashima expects the market to evolve quickly. “Think of smartphones,” he says. “The components inside are extremely expensive, yet business models make them accessible. The same will happen with APN transceivers.”

Industry consensus required

The next challenge is ecosystem alignment. IOWN was preceded in 2015 by OpenROADM which similarly aims to define and promote open optical data plane specifications. Its supporters include AT&T, Deutsche Telekom, NTT and Cisco.

Other vendor and carrier‑led groups have emerged to promote their own compute and optical technologies. These include the Open Compute Project (OCP - which has Meta, Microsoft, Nvidia and Google on its steering committee) and the OCI MSA (Optical Compute Interconnect Multi-Source Agreement) group which intends to establish an open, interoperable optical interconnect specification for AI. It’s also backed by Meta, Microsoft, Nvidia plus Broadcom and OpenAI.

“We have a strong collaboration with the OCP,” says Kawashima. “Together we’ve launched the AI Computing Continuum, which aims to define technology standards for a computing space spanning multiple clouds and edges.

“What differentiates IOWN is that we define concrete use cases—financial data centres, remote media streaming—and then specify end‑to‑end system designs. With that foundation, we collaborate with consortia like OCP and OpenROADM.

OCI MSA launched in February and IOWN is yet to engage directly. But Kawashima believes it will appreciate IOWN’s work “because we define use cases for their optical devices and show how customers can build full end‑to‑end systems using them.”

Interoperability for APN requires standardised long‑reach coherent transceivers suitable for CPE as well as operational models for provisioning photonic paths directly to enterprise sites.

“Once interoperability standards are established, the cost impact will be modest,” he says.

2030 APN roadmap

IOWN’s 2030 roadmap is ambitious: a global computing and communications fabric built on photonics, low‑latency architectures, and distributed AI. Parts of this vision are already commercially deployed.

NTT launched its first APN services in Japan two to three years ago, initially offering 100 Gbps connectivity in limited regions. Coverage and performance have been expanding ever since. Higher throughput, with per‑customer links scaling to 100G, 400G, and beyond is envisaged.

“The basic concept is already in service,” he says. “We continue to upgrade, but the foundation is real.”

Emerging architectures such as co-packaged optics (CPO) bring optical data transceivers directly next to compute chips, cutting power and latency by shortening conversion distances.

Nvidia is building CPO networking switches to scale AI for industrial use. Other developers are lining up to incorporate optical semiconductors, switchers and interconnects including Twinstar Technologies, Delta Electronics, and Corning Incorporated.

Beyond this, technologies like optical interposers and fully all-optical computing systems, where photons handle processing without conversion, are rapidly progressing.

One of the most urgent use cases is sovereign AI infrastructure. Nations are racing to build regional AI clouds to maintain competitiveness, but high‑performance compute is only half the story. “You must also connect customer locations to these AI systems with enough bandwidth,” Kawashima says.

Financial services are another early adopter. As banks transform into digital‑platform‑driven businesses, ultra‑low‑latency, high‑bandwidth connectivity becomes essential. Photonics offers both.

Photonics and the Quantum future

Looking further ahead, photonics will be essential for quantum computing. Quantum systems will be centralised in specialised data centres, not distributed to every enterprise. The challenge will be moving enormous matrix‑based datasets in and out of those facilities.

“High‑bandwidth, low‑latency connectivity will be critical,” Kawashima says. “APN is well suited to that requirement.

Oriole Networks, which spun out of UCL in 2023, set out to build the highest-performing AI network imaginable, “pushing toward theoretical limits” with photonics as a key enabler.

“It is a massively performant AI network based on incredibly efficient photonics,” says CEO James Regan of his company’s PRISM platform which boasts a 50 Exabit per second throughput.

The Netherlands is another photonics hotspot. Eindhoven-based Photon Bridge’s laser‑on‑silicon approach “redefines photonic integration to make light scalable, manufacturable, and infrastructure-ready.​”

“Photonics is the physical foundation of the next digital economy,” says Mark Rushworth,  founder and CEO of UK start up Finchetto which is working on an optical packet switch. “AI, quantum computing, and cloud networking all depend on the ability to move and process data faster, cooler, and smarter. In the ongoing race to optimisation, light wins every time.”