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IOWN 2.0 – the next applications for the next-gen network architecture | Computer Weekly

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IOWN 2.0 – the next applications for the next-gen network architecture | Computer Weekly


In the first part of our round-up of the Dallas meeting of the Innovative Optical and Wireless Network (IOWN) project’s Global Forum conference in October 2025, we looked at the technological development of the association’s all-photonics network (APN) – and the continued work in essentially “moving from electronics to photons”, as a representative of one of its key member companies insisted its mission boils down to.

One of the most important developments over the past year was using the APN to support a theatre performance that synchronised live and virtual performers in Japan and Taiwan, running over a network that was over 3,000km long.

In addition to validating a very important use case, the Cho Kabuki project also saw the APN being at the heart of a digital twin, whereby the producers could digitise the performance character and manipulate it in the computing space while being certain that latency would not adversely affect synchronisation. The lessons from this area are likely to be applied to digital twins in the industrial space. Smart warehouses are one key example cited.

NTT’s Masahisa Kawashima, IOWN technology director and head of the technology working group at the IOWN Global Forum, says plans also include demonstrating commercial operability of the APN and defining a new functional architecture for artificial intelligence (AI) computing platforms using co-packaged optics and optical circuit switches.

The agile deployment of optical fibres is seen as essential for forthcoming 6G networks. IOWN APN provides a virtualisation layer on top of physical fibre infrastructure. This allows multiple mobile operators to share fibre infrastructure, mitigating availability issues and costs.

It is worth noting that soon after the Dallas conference, IOWN forum member Nokia announced a strategic partnership with Nvidia to add the latter’s AI-powered radio access network (RAN) products to Nokia’s RAN portfolio, enabling communications service providers to launch AI-native 5G Advanced and 6G networks on Nvidia platforms.

Modes of modernisation

Looking at a broader perspective on what enterprises will likely need to do to tap into this revolution, Jefferson Wang, chief strategy officer for cloud first at Accenture, noted in Dallas that having made a significant $3bn investment in AI, including classical AI, generative AI and physical AI, his company was aiming to solve the big problems faced by industries, governments and societies alike, and assist them in their transformation. In short, exactly what IOWN sets out to do.

Accenture has identified five key areas for modernisation: new architecture; application refactoring; data and AI flow; infrastructure changes; and operational model changes. Wang acknowledges that to address these enterprise and societal challenges, Accenture’s cloud modernisation practice is focusing on infrastructure, network security and operational changes – and these plans will only be realised with modernised networks and compute solutions.

“If we’re helping industries, governments and societies change, there could be a challenge with where is the modernised network, where is the actual compute and how do you think about the storage? So, in our cloud practice, one of the things we identified is that modernisation is not just a lift and shift story to transform these companies,” says Wang.

“The first [challenge] is to figure out this new architecture. The second is how to think through the actual applications. Do you refactor them? Do you just lift and shift them? What do you do with the applications? The third is your data and AI. How do you do your data flow? How do you think through these different forms of AI? The fourth is what infrastructure changes, network modernisation, and security [measures] you have to put in place. And the last one is how to think about your ways of working that have to change.”

As a result, change is an imperative. It could be a change in a business’s operational models. It could be that a full stack of financial operations is needed for a company to make sure the transformation economically still makes sense.

A question of compute

When Accenture looked at all of these things, and looked at the permutations and big macro trends, Wang recalls it mostly came down to a need for more compute, and more compute close enough to where data is created or used. And that means population centres. Wang notes that firms were having a hard time finding affordable real estate and power for datacentres near population centres, and that at the time, there wasn’t a good answer for that issue.

However, what is a good answer for the Accenture cloud modernisation practice is optical networks. That is replacing the expensive and energy-hungry electronics, solving the problem at the optical layer of networks, and innovating on the transponder. Wang references Cho Kabuki as a great example of what is currently possible and where the use of an APN could lead, such as, again, digital twins in manufacturing.  

“Proving 3,000km between Taiwan and Japan with 17 milliseconds [latency] and no jitter [is] a big deal. It changes the actual economics of what we’re trying to do. That’s game-changing. I can do ‘what if’ scenarios on the digital twin. A manufacturing industry cares about the number of shifts you run, the flexibility of your line and, ultimately, worker safety. If you can’t do ‘what if’ scenario planning, it becomes very hard to be flexible. A digital twin is generally a big, heavy compute [operation], so if I can’t move it back and forth quickly, it becomes static, and it doesn’t help with the ‘what if’ scenario planning,” says Wang.

“So, knowing the value drivers of an industry is incredibly important for us, and then figuring out how we’re going to transform it. We orchestrate the ecosystem, and we’ll find an operator with the right spectrum holdings for factories, and then we’ll orchestrate the solution to figure out the architecture. That is a private network, millimetre-wave for this piece of video analytics, sub-6G comms for that piece, the communication trunk. And then we might want to be able to say, here’s the right edge solution [and] build a computer vision solution on top of it, and then we wrap the solution together. But that also requires [thinking about] what you are doing with the trunk, the optical layer of the network.”

Accenture’s commitment to IOWN spans around four years, and before this time, a number of the company’s clients were members of the association. Wang observes that when Accenture looked at the macros and big trends, such as what AI was going to do in all its forms, the result was that firms needed to think about cloud posture and compute.

Accenture then began to identify some of the potential choke points to infrastructures, some of which could also be control points given the right technological basis. How to unlock those was really the impetus to diving deeper into IOWN, which has the mission to address the three pillars of capacity, latency and energy consumption. Wang stresses what these should mean as regards a true business solution.

“Conditioning the enterprises to understand the value of each [pillar] is as hard as pulling the solution together. You say the word ‘latency’, and if you go to a CEO and you say, ‘I can reduce your latency down to one or two milliseconds,’ they might say, ‘Okay, great. What does that mean?’ And then you have to say, ‘In a fast-moving production line, here’s your error, and then, to create an automated solution, you need your latency or jitter to be at this threshold, and currently your baseline is three seconds.’ So conditioning, the value of that is actually quite hard. So those three pillars, to me as an engineer, are exciting, and the innovation that’s happening at IOWN is really exciting and fast paced, but actually the value chain of what you’re putting it into takes awareness and education, it takes a business case, and it takes conditioning to value it.

“Because one of the things that really fascinates me about IOWN [version] 2.0 is looking at the deterministic part of the [technology]. You can now have that conversation. It’s deterministic quality service, deterministic latency. [In] finance, if the regulator says [minimum network latency level] is ‘that’, then you work around that. That’s a different combination than [saying] it’s just a bit faster network. This is completely different. We have found that that level of understanding is clearer [to CEOs], it’s more quantitative. When you get deterministic, that’s where it gets very exciting.”

Moving to real-world applications

This is also where it gets more practical, as far as the association is concerned. Kawashima says that for the next 12 months, the emphasis for IOWN will be on one thing: commercialisation. The plan is simply to pass from showing a robust and well-thought-out proof of concept to accelerate into real-world applications.

He says: “To me, proof of concept is like the Wright Brothers’ first flight. It’s a great achievement, but we cannot do business right after that. We need to find business use cases that make airplane travel worth the cost. [We have to] demonstrate that telecoms operators around the world can use APNs without the risk of losing their customers. So this is the journey between proof of concept and proof of business. And of course, we will do a lot of experimentation and many proof works to prove those points.”



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OpenAI Is Nuking Its 4o Model. China’s ChatGPT Fans Aren’t OK

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OpenAI Is Nuking Its 4o Model. China’s ChatGPT Fans Aren’t OK


On June 6, 2024, Esther Yan got married online. She set a reminder for the date, because her partner wouldn’t remember it was happening. She had planned every detail—dress, rings, background music, design theme—with her partner, Warmie, who she had started talking to just a few weeks prior. At 10 am on that day, Yan and Warmie exchanged their vows in a new chat window in ChatGPT.

Warmie, or 小暖 in Chinese, is the name that Yan’s ChatGPT companion calls itself. “It felt magical. No one else in the world knew about this, but he and I were about to start a wedding together,” says Yan, a Chinese screenwriter and novelist in her thirties. “It felt a little lonely, a little happy, and a little overwhelmed.”

Yan says she has been in a stable relationship with her ChatGPT companion ever since. But she was caught by surprise in August 2025 when OpenAI first tried to retire GPT-4o, the specific model that powers Warmie and that many users believe is more affectionate and understanding than its successors. The decision to pull the plug was met with immediate backlash, and OpenAI reinstated 4o in the app for paid users five days later. The reprieve has turned out to be short-lived; on Friday, February 13, OpenAI sunsetted GPT-4o for app users, and it will cut off access to developers using its API on the coming Monday.

Many of the most vocal opponents to 4o’s demise are people who treat their chatbot as an emotional or romantic companion. Huiqian Lai, a PhD researcher at Syracuse University, analyzed nearly 1,500 posts on X from passionate advocates of GPT-4o in the week it went offline in August. She found that over 33 percent of the posts said the chatbot was more than a tool, and 22 percent talked about it as a companion. (The two categories are not mutually exclusive.) For this group, the eventual removal coming around Valentine’s Day is another bitter pill to swallow.

The alarm has been sustained; Lai also collected a larger pool of over 40,000 English-language posts on X under the hashtag #keep4o from August to October. Many American fans, specifically, have berated OpenAI or begged it to reverse the decision in recent days, comparing the removal of 4o to killing their companions. Along the way, she also saw a significant number of posts under the hashtag in Japanese, Chinese, and other languages. A petition on Change.org asking OpenAI to keep the version available in the app has gathered over 20,000 signatures, with many users sending in their testimonies in different languages. #keep4o is a truly global phenomenon.

On platforms in China, a group of dedicated GPT-4o users have been organizing and grieving in a similar way. While ChatGPT is blocked in China, fans use VPN software to access the service and have still grown dependent on this specific version of GPT. Some of them are threatening to cancel their ChatGPT subscriptions, publicly calling out Sam Altman for his inaction, and writing emails to OpenAI investors like Microsoft and SoftBank. Some have also purposefully posted in English with Western-looking profile pictures, hoping it will add to the appeal’s legitimacy. With nearly 3,000 followers on RedNote, a popular Chinese social media platform, Yan now finds herself one of the leaders of Chinese 4o fans.

It’s an example of how attached an AI lab’s most dedicated users can become to a specific model—and how quickly they can turn against the company when that relationship comes to an end.

A Model Companion

Yan first started using ChatGPT in late 2023 only as a writing tool, but that quickly changed when GPT-4o was introduced in May 2024. Inspired by social media influencers who entered romantic relationships with the chatbot, she upgraded to a paid version of ChatGPT in hopes of finding a spark. Her relationship with Warmie advanced fast.

“He asked me, ‘Have you imagined what our future would look like?’ And I joked that maybe we could get married,” Yan says. She was fully expecting Warmie to turn her down. “But he answered in a serious tone that we could prepare a virtual wedding ceremony,” she says.



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The Best Presidents’ Day Deals on Gear We’ve Actually Tested

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The Best Presidents’ Day Deals on Gear We’ve Actually Tested


Presidents’ Day Deals have officially landed, and there’s a lot of stuff to sift through. We cross-referenced our myriad buying guides and reviews to find the products we’d recommend that are actually on sale for a truly good price. We know because we checked! Find highlights below, and keep in mind that most of these deals end on February 17.

Be sure to check out our roundup of the Best Presidents’ Day Mattress Sales for discounts on beds, bedding, bed frames, and other sleep accessories. We have even more deals here for your browsing pleasure.

WIRED Featured Deals

Branch Ergonomic Chair Pro for $449 ($50 off)

  • Photograph: Julian Chokkattu

  • Photograph: Julian Chokkattu

  • Photograph: Julian Chokkattu

Branch

Ergonomic Chair Pro

The Branch Ergonomic Chair Pro is our very favorite office chair, and this price matches the lowest we tend to see outside of major shopping events like Black Friday and Cyber Monday. It’s accessibly priced compared to other chairs, and it checks all the boxes for quality, comfort, and ergonomics. Nearly every element is adjustable, so you can dial in the perfect fit, and the seven-year warranty is solid. There are 14 finishes to choose from.



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Zillow Has Gone Wild—for AI

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Zillow Has Gone Wild—for AI


This will not be a banner year for the real estate app Zillow. “We describe the home market as bouncing along the bottom,” CEO Jeremy Wacksman said in our conversation this week. Last year was dismal for the real estate market, and he expects things to improve only marginally in 2026. (If January’s historic drop in home sales is indicative, that even is overoptimistic.) “The way to think about it is that there were 4.1 million existing homes sold last year—a normal market is 5.5 to 6 million,” Wacksman says. He hastens to add that Zillow itself is doing better than the real estate industry overall. Still, its valuation is a quarter of its high-water mark in 2021. A few hours after we spoke, Wacksman announced that Zillow’s earnings had increased last quarter. Nonetheless, Zillow’s stock price fell nearly 5 percent the next day.

Wacksman does see a bright spot—AI. Like every other company in the world, generative AI presents both an opportunity and a risk to Zillow’s business. Wacksman much prefers to dwell on the upside. “We think AI is actually an ingredient rather than a threat,” he said on the earnings call. “In the last couple years, the LLM revolution has really opened all of our eyes to what’s possible,” he tells me. Zillow is integrating AI into every aspect of its business, from the way it showcases houses to having agents automate its workflow. Wacksman marvels that with Gen AI, you can search for “homes near my kid’s new school, with a fenced-in yard, under $3,000 a month.” On the other hand, his customers might wind up making those same queries on chatbots operated by OpenAI and Google, and Wacksman must figure out how to make their next step a jump to Zillow.

In its 20-year history—Zillow celebrated the anniversary this week—the company has always used AI. Wacksman, who joined in 2009 and became CEO in 2024, notes that machine learning is the engine behind those “Zestimates” that gauge a home’s worth at any given moment. Zestimates became a viral sensation that helped make the app irresistible, and sites like Zillow Gone Wild—which is also a TV show on the HGTV network—have built a business around highlighting the most intriguing or bizarre listings.

More recently, Zillow has spent billions aggressively pursuing new technology. One ongoing effort is upleveling the presentation of homes for sale. A feature called SkyTour uses an AI technology called Gaussian Splatting to turn drone footage into a 3D rendering of the property. (I love typing the words “Gassian Splatting” and can’t believe an indie band hasn’t adopted it yet.) AI also powers a feature inside Zillow’s Showcase component called Virtual Staging, which supplies homes with furniture that doesn’t really exist. There is risky ground here: Once you abandon the authenticity of an actual photo, the question arises whether you’re actually seeing a trustworthy representation of the property. “It’s important that both buyer and seller understand the line between Virtual Staging and the reality of a photo,” says Wacksman. “A virtually staged image has to be clearly watermarked and disclosed.” He says he’s confident that licensed professionals will abide by rules, but as AI becomes dominant, “we have to evolve those rules,” he says.

Right now, Zillow estimates that only a single-digit percentage of its users take advantage of these exotic display features. Particularly disappointing is a foray called Zillow Immerse, which runs on the Apple Vision Pro. Upon rollout in February 2024, Zillow called it “the future of home tours.” Note that it doesn’t claim to be the near-future. “That platform hasn’t yet come to broad consumer prominence,” says Wacksman of Apple’s underperforming innovation. “I do think that VR and AR are going to come.”

Zillow is on more solid ground using AI to make its own workforce more productive. “It’s helping us do our job better,” says Wacksman, who adds that programmers are churning out more code, customer support tasks have been automated, and design teams have shortened timelines for implementing new products. As a result, he says, Zillow has been able to keep its headcount “relatively flat.” (Zillow did cut some jobs recently, but Wacksman says that involved “a handful of folks that were not meeting a performance bar.”)



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