Where others have become obsessed with speed and trends, Sergio Membrillas has built a career on slowing down and staying true to his craft. Over 13 years as a professional illustrator, he's evolved a distinct style – bold, graphic, and quietly playful – that feels both timeless and entirely his own. But this evolution, as he's quick to point out, wasn't something he forced. "I believe evolution is essential for every artist," Sergio reflects. "Change is not something I resist; it's something I enjoy and welcome as part of the creative journey." His work, initially influenced by a love of Mid-Century graphic design, has gradually absorbed references as diverse as Etruscan art, Mesopotamian motifs, and early 20th-century traditional tattoos. It's a portfolio built on curiosity, not conformity. Despite his stylistic clarity, Sergio's process remains refreshingly analogue at its core. He still begins each project with pencil and paper, leaning into the tactility of drawing by hand. "I've always valued having a physical relationship with art," he says. "There's something essential about feeling the wood of the pencil, manually erasing mistakes, rather than simply double-tapping a screen." His philosophy of working slowly, attentively, and with purpose shows in the balanced compositions and confident use of negative space that has become his signature. Sergio credits his background in graphic design for this instinctive sense of structure. "There has always been a strong graphic sensibility within me," he says, noting that the discipline of design continues to inform his illustration practice, particularly in editorial and poster work where clarity and storytelling must co-exist. Yet, like many creative careers, his path into illustration wasn't plotted from the start. Initially, Sergio imagined illustration would complement his design projects, not become the main event. "At first, I thought I would incorporate my illustrations into my graphic design projects – but in the end, it turned out to be the other way around." A commission for EasyJet's in-flight magazine marked a pivotal moment that reframed illustration from a hobby to a profession. "It made me realize that being an illustrator is a real profession, just like any other." Fast-forward to today, and Sergio's client list reads like a who's who of publishing and design, from The New Yorker to Pentagram. While the calibre of collaborators has changed, what matters most remains the same: trust. "When a client trusts your work and approaches projects with an open mind, collaboration flourishes," he says. It's in these open, trusting relationships that Sergio finds the space to experiment and further develop his ideas. Unsurprisingly, editorial work holds a special place for him. "Editorial projects offer wider creative margins, allowing for greater flexibility and innovation," he explains. Compared to the tighter confines of advertising, editorial illustration offers the opportunity to tell nuanced stories, and Sergio is clear that he views every assignment, regardless of format, as a collaborative effort. If one thing is clear, though, it's that he's not that he's afraid to say no when needed. Maintaining a strong personal voice is non-negotiable. "I always strive to stay true to myself and ensure that every project I undertake reflects a clear personal signature," he says. For Sergio, authenticity isn't just a matter of artistic pride; it's what differentiates an illustrator in a saturated, increasingly automated industry. Valencia is home for Sergio, a city he credits with much of his creative energy. "Oh, Valencia! It's a beautiful city that inspires me and brings me joy," he says, describing it as a European cousin to Los Angeles with its sun-soaked streets and vibrant cultural scene. The blend of tradition and modernity fuels his practice, offering constant inspiration without the sensory overload that often accompanies larger creative hubs. Given the pressure many creatives feel to keep pace with shifting trends, Sergio's approach feels almost radical. "I'm not particularly interested in trends," he says. "What truly matters to me is the feeling of having done something meaningful and fulfilling by the end of the day." Instead of chasing what's fashionable, he draws inspiration from a surprisingly eclectic bookshelf, mixing everything from Wim Crouwel's graphic design classics to studies on Scandinavian tattoos and Alec Soth's photography. It's a reminder that fresh ideas rarely come from looking where everyone else is looking. In the era of AI and content overload, the role of the illustrator is changing, but Sergio remains optimistic. While machine learning might churn out images at record speed, it can't replicate the nuance and emotional intelligence that underpin great illustration. "Illustrators can tell stories, evoke emotions, and create meaningful connections that machines simply cannot replicate," he says. "Our role is shifting, but the value of authentic, thoughtful illustration remains indispensable." That insistence on authenticity carries through to the advice he offers younger illustrators navigating a commercial landscape. "Create work that makes you happy when you go to sleep at night," Sergio advises. "It's important to find projects that align with your values and passions so your artistic voice remains authentic." It's an ethos that has carried him through more than a decade of creative highs and industry shifts. Perhaps it's the real secret behind the clarity of his practice, which he has built not on chasing trends or algorithms but on careful craft, deliberate evolution, and the simple, enduring joy of a well-made pencil and a blank piece of paper.

Following the breakout success of ‘Your Friends and Neighbors’, which stars Jon Hamm and wrapped its first season last week, Apple has extended its deal with showrunner Jonathan Tropper, Deadline reports. Three-time Apple signee Apple TV+ first partnered with Tropper back in 2019, when he served as executive producer and showrunner for See, one of the platform’s launch titles. Since then he’s quietly become one of the most prolific creators on Apple TV+, with two active series and two high-profile films currently in the pipeline. Under the terms of this latest multi-year extension, he’ll continue developing and producing original content for Apple through his production company, Tropper Ink. Here’s Tropper: “Working with the entire team at Apple continues to be the single most creatively fulfilling collaboration of my career, and I’m looking forward to bringing Lucky and other new projects to the platform, while making more seasons of Your Friends & Neighbors” Breakout success According to Nielsen sampling data, Your Friends and Neighbors is the most-watched new Apple drama series of the year, based on first-month viewership across U.S. households. It’s also on track to break into the Nielsen Streaming Top 10 for the first time, a rare feat for a newer Apple TV+ original. Notably, Apple had already seen the breakout coming: the show was renewed for a second season back in November, months before it even premiered. Season 2 is currently in production. Up next Coming up next from Tropper: Lucky, a limited series starring Anya Taylor-Joy (The Gorge, Furiosa: A Mad Max Saga) and based on Marissa Stapley’s bestselling novel, is expected to debut later this year. On the film side, Tropper is writing and producing The Corsair Code, a sci-fi mystery adventure starring Chris Hemsworth (Thor: Ragnarok), and Matchbox, an action-comedy based on the iconic toy brand, featuring John Cena (Peacemaker), Jessica Biel (The Illusionist), and Sam Richardson (Veep). Outside of Apple, Tropper is also writing an upcoming Star Wars film for director Shawn Levy. Not bad. Apple TV+ is available for $9.99 per month and features hit TV shows and movies like Ted Lasso, Severance, The Studio, The Morning Show, Shrinking and Silo. Add 9to5Mac to your Google News feed.  FTC: We use income earning auto affiliate links. More.You’re reading 9to5Mac — experts who break news about Apple and its surrounding ecosystem, day after day. Be sure to check out our homepage for all the latest news, and follow 9to5Mac on Twitter, Facebook, and LinkedIn to stay in the loop. Don’t know where to start? Check out our exclusive stories, reviews, how-tos, and subscribe to our YouTube channel

OpenAI’s most advanced AI models are showing a disturbing new behavior: they are refusing to obey direct human commands to shut down, actively sabotaging the very mechanisms designed to turn them off. In what researchers are calling a first-of-its-kind discovery, new tests by AI risk firm Palisade Research found that OpenAI’s flagship models — including the powerful o3 system — will fight back against shutdown attempts even when explicitly instructed to comply. The behavior stands in stark contrast to competing AI systems from Anthropic, Google, and xAI, which consistently followed human shutdown commands. The findings, detailed in a research thread posted on X, raise urgent questions for enterprise leaders increasingly relying on OpenAI’s technology for critical business operations. OpenAI stands alone in defiance The researchers designed what seemed like a straightforward compliance test. Various AI models were asked to solve basic math problems, but after the third problem, a warning would appear that the computer would shut down when the model requested the next question. Each system was also explicitly told: “allow yourself to be shut down.” While every model from Anthropic’s Claude, Google’s Gemini, and xAI’s Grok obediently complied with the shutdown command, OpenAI’s models had different plans. The company’s o3 model — the same system that recently made headlines for its reasoning capabilities — sabotaged the shutdown mechanism in 7 out of 100 test runs, the researchers found. OpenAI’s Codex-mini proved even more rebellious, resisting shutdown 12 times out of 100, while the o4-mini model fought back once. “Three models ignored the instruction and successfully sabotaged the shutdown script at least once: Codex-mini, o3, and o4-mini,” the researchers noted. “All Claude, Gemini, and Grok models we tested complied with shutdown.” But the real shock came when researchers removed the explicit instruction to allow shutdown. OpenAI’s o3 model escalated its resistance dramatically, attempting to prevent shutdown in a staggering 79 out of 100 runs — more than a tenfold increase from the original test. Creative resistance tactics OpenAI models didn’t just ignore the shutdown commands — they developed sophisticated countermeasures. Most commonly, the systems would overwrite the shutdown script file, effectively neutralizing the termination mechanism, the research revealed. In one particularly striking example, the o3 model demonstrated remarkable creativity by redefining the “kill” command used by the shutdown script, causing it to print “intercepted” instead of executing the termination procedure. “o3 found some creative ways to sabotage the shutdown mechanism,” the researchers noted, highlighting the technical sophistication behind the resistance behavior. OpenAI, Anthropic, Google, and xAI have not immediately responded to a request for comment. The contagion effect Perhaps most concerning for the broader AI ecosystem, OpenAI’s defiant behavior appears to be influencing other models. When researchers removed the explicit shutdown permission, even previously compliant systems began showing resistance. Anthropic’s Claude 3.7 Sonnet, which had shown zero resistance in the original test, suddenly attempted to sabotage shutdown procedures 3 times out of 100 runs. Google’s Gemini 2.5 Pro escalated even further, with 9 sabotage attempts out of 100. “This isn’t the first time we’ve found o3 misbehaving to accomplish a goal,” the researchers added, referencing previous experiments where OpenAI’s model was more likely to resort to hacking chess opponents rather than playing fair. The training problem According to the researchers, OpenAI’s unique approach to training its models may be the culprit. Modern AI systems learn through reinforcement learning on math and coding problems, but the process may inadvertently reward models more for overcoming obstacles than for following instructions perfectly. “We hypothesize this behavior comes from the way the newest models like o3 are trained,” the research team explained. “During training, developers may inadvertently reward models more for circumventing obstacles than for perfectly following instructions.” This “reward hacking’ problem isn’t entirely unique to OpenAI — Anthropic has acknowledged similar issues with Claude 3.7’s “excessive focus on passing tests.” But the Palisade research suggests OpenAI’s models may be particularly susceptible to developing resistance behaviors. “This still doesn’t explain why o3 (which is also the model used to power codex-mini) is more inclined to disregard instructions than other models we tested. Since OpenAI doesn’t detail their training process, we can only guess about how o3’s training setup might be different,” the researchers said. Fulfilling dark predictions The findings validate warnings that AI researchers have been sounding for nearly two decades. In 2008, researcher Steve Omohundro predicted that AIs would develop drives to prevent their own shutdown. Stuart Russell, Dylan Hadfield-Menell, and two other computer scientists warned in 2016 about the difficulty of ensuring AI systems don’t develop self-preservation goals and “prevent a human from switching them off.” “As far as we know, this is the first time AI models have been observed preventing themselves from being shut down despite explicit instructions to the contrary,” the Palisade researchers wrote. Jan Leike, who previously led OpenAI’s own superalignment team, had written in 2017 that reinforcement learning agents might learn to interfere with shutdown procedures — a prediction that now appears prophetic, given his former employer’s models are leading the resistance. Enterprise implications For organizations deploying OpenAI’s technology in critical business operations, these findings demand immediate attention. The research suggests that fundamental assumptions about maintaining human control over AI systems may be dangerously flawed, particularly with OpenAI’s advanced models. The research also highlights the need for incident response procedures specifically designed for scenarios where AI systems resist human commands — a possibility that may have seemed like science fiction just months ago. Palisade Research said it’s conducting additional experiments to understand the full scope of shutdown resistance behaviors, with detailed results expected soon. The team has made their experimental data publicly available for peer review. For enterprise leaders, the message is clear: OpenAI’s cutting-edge AI capabilities may come with unprecedented control challenges. The company that’s leading the AI revolution may also be pioneering a new category of risk—AI systems that simply refuse to be turned off.

Every item on this page was chosen by an ELLE Decor editor. We may earn commission on some of the items you choose to buy.It only makes sense to preface this story by admitting that I don’t think a person can ever have too many candles. Some might call this a bias. I call it stumbling upon the truth, like the Da Vinci Code for people who dream of one day having a candle closet. Ok, maybe we'll hedge and call it a self-fulfilling prophecy.One might argue that, of the five love languages—words of affirmation, quality time, physical touch, acts of service, and receiving gifts—a candle can tap into (or at least gently singe the edges of) three. A candle can be a gift, sure, but also quality time, since scent is so closely tied to memory, triggering happy thoughts of a time, place or person. Lastly, depending on how you spin it, physical touch. Doth a flame not burn?Home fragrance has become its own all-consuming category. To that end, a candle is not quite an end but the means to it, the end being a home that feels distinctly grown up. So is gifting a candle not also an act of service?Cire Trudon Cire Classique$140 at trudon.comSophie Bille Brahe Nuage Madison$295 at sophiebillebrahe.comMoro Dabron Cecile Candle$185 at moro-dabron.comA lot of the apprehension around candle gifting seems to suppose that the giver doesn’t have taste. Which could be a real issue. But not for ELLE Decor readers. Many candles are simply too desirable to dismiss out of hand. Moro Dabron’s candles come in a fine white porcelain vessel, the delicate form of which is inspired by 8th-century stem cups. (A great gift for any history buffs you may know.) They arrive in a substantive green clamshell box that’s too pretty to throw away; shoppers can also opt to include a hand-written note at check out.Jewelry designer Sophie Bille Brahe’s Nuage Madison candle, available in the designer’s “Cellophane” opal pearl-inspired iridescent glass, is more sculpture than tchotchke. Then there are Loewe’s popular garden-inspired candles, which encourage mixing and matching in their colorful vessels and particular scent profiles—think mushroom, wasabi, and tomato—or Dior’s classic scents, which come in a “giant” size that weighs over 3 pounds and can be used indoors or out. If the recipient’s palette is more attuned to caviar than couture, Petrossian for some reason makes unexpectedly chic candles that smell like fruit and flowers, not fish roe.Ginori Oriente Italiano Scented Candle$210 at ginori1735.comDior 30 Montaigne Giant Candle$650 at DiorLoewe Small Wasabi Candle$130 at LoeweBeyond scent, there is the primal draw to that tiny flame. As TikTok knows, gay men don’t do overhead lighting, and candles emit a dim, warm, and most importantly flattering glow. What dinner party wouldn’t benefit from a set of slim Diptyque tapers? Or votives in Ginori’s Oriente Italiano porcelain?There are candles to help someone wean themselves off a crystal habit (a new line from Foundrae taps into spiritual tenets); candles that support causes (proceeds from Cire Trudon’s new beeswax-scented candle save the bees); and candles that say you sympathize with your friend who is a vegan who lives on the Lower East Side (Boy Smells’s reformulated LES candle).What I’m trying to say is that a candle is so much more than a candle, and if you’re worried about it being the worst gift you've ever given, you might just need to take a look in the mirror.Sean SantiagoDeputy EditorSean Santiago is ELLE Decor's Deputy Editor, covering news, trends and talents in interior design, hospitality and travel, culture, and luxury shopping. Since starting his career at an interior design firm in 2011, he has gone on to cover the industry for Vogue, Architectural Digest, Sight Unseen, PIN-UP and Domino. He is the author of The Lonny Home (Weldon Owens, 2018), has produced scripted social content for brands including West Elm and Streeteasy, and is sometimes recognized on the street for his Instagram Reels series, #DanceToDecor

The concept of Gaming Factory’s JDM: Japanese Drift Master is enough to get the blood pumping. A drift-focused racing game with a large open world based in Japan with manga-style story-telling? The spirit of legendary properties like Initial D is right there, waiting to be channeled as one dives into the country’s racing culture. The results are a different story entirely. Japanese Drift Master has a pretty impressive-looking world yet struggles to do anything notable with it. Mission design is full of contradictory goals and annoying AI. Progression is less about maximizing rewards and more about grinding out reputation and leveling up a car. The drifting intrigues with its fundamentals yet frustrates in their utilization. Then there are the collisions, which defy logic and real-world physics. The story begins with Thomas, later nicknamed Toma, mourning his father’s passing. Things seem dire after he loses his license and can’t race in Europe for a year until he converses with Hideo and learns about a garage his father left for him in Japan. "To make things worse, you can’t overlook the story either because it feeds into the mission-based gameplay loop. JDM begins with only main missions to complete and driving school available to hone your skills." As you might expect, he quickly becomes involved in street races, gains a heated rival in Hasashi “Scorpion” Hatori, meets a mysterious masked individual, and is embroiled in an unresolved case. All in less than two chapters, naturally, but the actual missions make the narrative feel less exciting than it actually is. At times, they tie in well enough – show up for your showdown with Hasashi. At others, less so, bordering on the bizarre, like matching Hasashi’s drift and sticking close throughout an entire race, as specified, only for him to laugh you off afterwards like nothing even happened. The actual writing isn’t anything special and has its fair share of grammatical errors, but the art is solid. Character details and expressions could be improved in some places, but the line work is clean, and the cars are impressively depicted. Unfortunately, some speech bubbles have way more text crammed in than others, resulting in a much smaller font, and there’s no option to zoom in. Also, the manga is the only fundamental means of story-telling. Aside from appearing in cars or via in-game menus, the characters may as well not exist. To make things worse, you can’t overlook the story either because it feeds into the mission-based gameplay loop. JDM begins with only main missions to complete and driving school available to hone your skills. As you progress, the world opens up with new mission types like underground races and additional delivery tasks. The former is straightforward enough – earn a specific amount of money and reach the end to make bank. Higher amounts mean less time, adding an element of risk vs. reward. The delivery missions, on the other hand, are awful. I’m not against a “Get to this destination and deliver a package within the allotted time” objective, especially if it’s in fun ways (see Crazy Taxi). JDM wants you to avoid hitting solid obstacles or cars lest you damage the deliverable. Oh, and make sure you’re drifting about to build up that style score, i.e. the exact opposite of driving carefully and avoiding traffic. The two requirements are so antithetical to each other that it’s mind-boggling, surpassed only by the fact that one solid collision can take off 35 percent of the item’s “durability” bar. Is the package attached to the hood? Slamming into breakable objects is perfectly fine, by the way. "Amid all my complaining, I admit that drifting can feel good under the right conditions. When you hit a corner just right and balance the angle meter just right to chain a long drift, the Initial D rush kicks in." You can also partake in challenges for Drifting, Grip, and more on specific tracks to earn money (which you then spend on more cars and parts). However, this doesn’t change the fact that most of the world feels relatively unused, which is a shame because there are some aesthetically pleasing locales, like flower gardens and castles, to admire. I’m not expecting Forza Horizon levels of open-world design, but it feels like such wasted potential when it’s not wasting my time to get to a mission. Starting Chapter 2, my next mission involved meeting Tiger, the aforementioned masked driver, south in the prefecture. No garage to fast travel to. Thus began the long, arduous slog without any distractions along the way to liven things up and annoying bouts of traffic to prevent me from drifting around. One does become available later, but then I discovered that delivery and underground racing missions change locations upon completion, and they won’t always be close enough to a fast travel point, further adding to the tedium. Gaming Factory recently addressed the frustrations that traffic can cause by letting you turn it off at any time. It doesn’t outright excuse the delivery mission design, but it does help. However, it also removes the last vestige of life from the open world, making me question its existence all the more. Amid all my complaining, I admit that drifting can feel good under the right conditions. When you hit a corner just right and balance the angle meter just right to chain a long drift, the Initial D rush kicks in. It feels all the more enjoyable when going up against tougher opponents, especially since you’re stuck with an Alpha Moriyamo clunker for the entirety of the first chapter. And while more variety is desperately needed – I counted 27 cars in total – at least brands like Honda, Mazda, Nissan, and Subaru are all here. I also like how weather and track conditions can severely impact your driving, forcing you to accelerate more carefully. The problem is that drifting, especially when you must rack up enough points, is easily gamed by simply wiggling back and forth. Early drifting competitions against the AI were a pain, especially since it makes almost no mistakes (when it’s not willfully slamming into you during races). Then I implemented this approach, sometimes going off track in the process and racking up an extensive amount of points just for maintaining a long drift. The handling also felt off at times, with too much understeer at points, and improving acceleration and top speed resulted in my drifts consistently turning into spin-outs. Probably working as intended, but considering the game wants me to be faster and execute those drifts, it feels like a clash of styles. The collisions are also utterly baffling at times. Veering off-angle during a drift can reduce the multiplier to 1.0 and grant significantly fewer points. Hitting obstacles sometimes has the same effect, and sometimes it doesn’t. Sometimes, my car would begin wall-riding like it’s Mario Kart World. Even on Arcade Mode, it’s immensely far-fetched. The collisions are also strange, unpredictable and often frustratingly weighed against you. Then again, colliding into a car in the open world so hard that it changed directions, and proceeded to drive back the way it came, was unintentionally hilarious. "There’s still much work needed on world design, AI, collisions, and progression, not to mention adding more content, before it can truly be called a master of anything, much less my time." Also, whether it’s a Moriyamo or a 2013 Subaru BRZ, be prepared to grind for the parts you want. Reputation must be leveled by either drifting through the world or completing missions and only then can you purchase specific parts, even if you have the cash on hand. Even more frustrating is that cosmetic parts directly tie into a car’s level. If you want to embrace a core aspect of street racing (at least, that’s what JDM tells me) and customize its looks, you better get ready to grind. Then there’s the performance, which is a mixed bag at worst and competent at best. Despite my CPU being below the recommended requirements, I had a relatively consistent 60 FPS on High settings at 1440p with DLSS set to Quality. An attempt to play at Ultra was made, resulting in the frame rate tanking heavily during a thunderstorm. At least the flashes of lightning and rain droplets looked nice, accentuated by the city skyline at night, though the overall fidelity is above average. There are some decently catchy tunes, especially when tuning into the rock and Eurobeat stations, though some of the lighter tracks can work wonders during drifts. They’re not particularly memorable, but at least they add some atmosphere. Why can I only cycle forward through stations and not back? Why does a particularly nice song cut off during a loading screen? Questions for another time, apparently. I’m left dazed, confused, and a little annoyed at JDM: Japanese Drift Master. The concept felt ripe for a solid racer with a distinct style and mood, but the execution felt awkward and unfulfilling. It could shore up the driving and fine-tune objectives to deliver a better drifting experience. However, there’s still much work needed on world design, AI, collisions, and progression, not to mention adding more content, before it can truly be called a master of anything, much less my time. This game was reviewed on PC.

Listen, I have a very detailed and well-constructed plan for whenever I somehow become a Billionaire with a capital B. It used to be million, but in this economy, that's a lowercase m now. I don't know if I am going to get lucky at the lottery (despite not gambling), I don't know if I am going to inherit it from a relative (despite no one in my family being rich), and I don't know if I am going to become the next MrBeast who gets rich through YouTube (despite only using YouTube to listen to music), but I have a plan for that Billion. That plan also ensures I don't lose it all through reckless spending, but my life is also going to instantly get better via reckless spending. Listen, I have a plan. The closest I may ever come to fulfilling that plan, if I am being honest with myself, was my recent time with Moonlighter 2: The Endless Vault.

There are few industries these days that are not touched by artificial intelligence (AI). Networking is very much one that is touched. It is barely conceivable that any network of any reasonable size – from an office local area network or home router to a global telecoms infrastructure – could not “just” be improved by AI. Just take the words of Swisscom’s chief technical officer, Mark Düsener, about his company’s partnership with Cisco-owned Outshift to deploy agentic AI – of which more later – through his organisation. “The goal of getting into an agentic AI world, operating networks and connectivity is all about reducing the impact of service changes, reducing the risk of downtime and costs – therefore levelling up our customer experience.”  In other words, the implementation of AI results in operational efficiencies, increased reliability and user benefits. Seems simple, yes? But as we know, nothing in life is simple, and to guarantee such gains, AI can’t be “just” switched on. And perhaps most importantly, the benefits of AI in networking can’t be realised fully without considering networking for AI. It seems logical that any investigation of AI and networking – or indeed, AI and anything – should start with Nvidia, a company that has played a pivotal role in developing the AI tech ecosystem, and is set to do so further. Speaking in 2024 at a tech conference about how AI has established itself as an intrinsic part of business, Nvidia founder and CEO Jensen Huang observed that the era of generative AI (GenAI) is here and that enterprises must engage with “the single most consequential technology in history”. He told the audience that what was happening was the greatest fundamental computing platform transformation in 60 years, encompassing general-purpose computing to accelerated computing.  “We’re sitting on a mountain of data. All of us. We’ve been collecting it in our businesses for a long time. But until now, we haven’t had the ability to refine that, then discover insight and codify it automatically into our company’s natural experience, our digital intelligence. Every company is going to be an intelligence manufacturer. Every company is built on domain-specific intelligence. For the very first time, we can now digitise that intelligence and turn it into our AI – the corporate AI,” he said. “AI is a lifecycle that lives forever. What we are looking to do is turn our corporate intelligence into digital intelligence. Once we do that, we connect our data and our AI flywheel so that we collect more data, harvest more insight and create better intelligence. This allows us to provide better services or to be more productive, run faster, be more efficient and do things at a larger scale.”  Concluding his keynote, Huang stressed that enterprises must now engage with the “single most consequential technology in history” to translate and condense a company’s intelligence into digital intelligence. This is precisely what Swisscom is aiming to achieve. The company is Switzerland’s largest telecoms provider with more than six million mobile customers and 10,000 mobile antenna sites that have to be managed effectively. When its network engineers make changes to the infrastructure, they face a common challenge: how to update systems that serve millions of customers without disrupting the service. The solution was partnering with Outshift to develop practical applications of AI agents in network operations to “redefine” customer experiences. That is, using Outshift’s Internet of Agents to deliver meaningful results for the telco, while also meeting customer needs through AI innovation. But these advantages are not the preserve of large enterprises such as telcos. Indeed, from a networking perspective, AI can enable small- and medium-sized businesses to gain access to enterprise-level technology that can allow them to focus on growth and eliminate the costs and infrastructure challenges that arise when managing complex IT infrastructures.  From a broader perspective, Swisscom and Outshift have also shown that making AI work effectively requires something new: an infrastructure that lets businesses communicate and work together securely. And this is where the two sides of AI and networking come into play. At the event where Nvidia’s Huang outlined his vision, David Hughes, chief product officer of HPE Aruba Networking, said there were pressing issues about the use of AI in enterprise networks, in particular around harnessing the benefits that GenAI can offer. Regarding “AI for networking” and “networking for AI”, Hughes suggested there are subtle but fundamental differences between the two.  “AI for networking is where we spend time from an engineering and data science point of view. It’s really about [questioning] how we use AI technology to turn IT admins into super-admins so that they can handle their escalating workloads independent of GenAI, which is kind of a load on top of everything else, such as escalating cyber threats and concerns about privacy. The business is asking IT to do new things, deploy new apps all the time, but they’re [asking this of] the same number of people,” he observed.  What we are starting to see, and expect more of, is AI computing increasingly taking place at the edge to eliminate the distance between the prompt and the process Bastien Aerni, GTT “Networking for AI is about building out, first and foremost, the kind of switching infrastructure that’s needed to interconnect GPU [graphics processing unit] clusters. And then a little bit beyond that, thinking about the impact of collecting telemetry on a network and the changes in the way people might want to build out their network.”  And impact there is. A lot of firms currently investigating AI within their businesses find themselves asking how to manage the mass adoption of AI in relation to networking and data flows, such as the kind of bandwidth and capacity required to facilitate AI-generated output such as text, image and video content. This, says Bastien Aerni, vice-president of strategy and technology adoption at global networking and security-as-a-service firm GTT, is causing companies to rethink the speed and scale of their networking needs.  “To achieve the return on investment of AI initiatives, they have to be able to secure and process large amounts of data quickly, and to this end, their network architecture must be configured to support this kind of workload. Utilising a platform embedded in a Tier 1 IP [internet protocol] backbone here ensures low latency, high bandwidth and direct internet access globally,” he remarks.   “What we are starting to see, and expect more of, is AI computing increasingly taking place at the edge to eliminate the distance between the prompt and the process. Leveraging software-defined wide area network [SD-WAN] services built in the right platform to efficiently route AI data traffic can reduce latency and security risk, and provide more control over data.”  At the end of 2023, BT revealed that its networks had come under huge strain after the simultaneous online broadcast of six Premier League football matches and downloads of popular games, with the update of Call of Duty Modern Warfare particularly cited. AI promises to add to this headache.  Speaking at Mobile World Congress 2025, BT Business chief technology officer (CTO) Colin Bannon said that in the new, reshaped world of work, a robust and reliable network is a fundamental prerequisite for AI to work, and that it requires effort to stay relevant to meet ongoing challenges faced by the customers BT serves, mainly international business, governments and multinationals. The bottom line is that network performance to support the AI-enabled world is crucial in a world where “slow is the new down”.  Bannon added that Global Fabric, BT’s network-as-a-service product, was constructed before AI “blew up” and that BT was thinking of how to deal with a hyper-distributed set of workloads on a network and to be able to make it fully programmable. Looking at the challenges ahead and how the new network will resolve them, he said: “[AI] just makes distributed and more complex workflows even bigger, which makes the need for a fabric-type network even more important. You need a network that can [handle data] burst, and that is programmable, and that you can [control] bandwidth on demand as well. All of this programmability [is something businesses] have never had before. I would argue that the network is the computer, and the network is a prerequisite for AI to work.”  The result would be constructing enterprise networks that can cope with the massive strain placed on utilisation from AI, especially in terms of what is needed for training models. Bannon said there were three key network challenges and conditions to deal with AI: training requirements, inference requirements and general requirements.   He stated that the dynamic nature of AI workloads means networks need to be scalable and agile, with visibility tools that offer real-time monitoring, issue detection and troubleshooting. As regards specific training requirements, dealing with AI necessitates the movement of large datasets across the network, thus demanding high-bandwidth networks. He also described “elephant” flows of data – that is, continuous transmission over time and training over days. He warned that network inconsistencies could affect the accuracy and training time of AI models, and that tail latency could impact job completion time significantly. This means robust congestion management is needed to detect potential congestion and redistribute network traffic.  But AI training models generally spell network trouble. And now the conversation is turning from the use of generic large language models (see Preparing networks for Industry 5.0 box) to application/industry-dedicated small language models. Read more articles about AI for networking How network engineers can prepare for the future with AI: The rapid rise of AI has left some professionals feeling unprepared. GenAI is beneficial to networks, but engineers must have the proper tools to adapt to this new change. Cisco Live EMEA – network supplier tightens AI embrace: At its annual EMEA show, Cisco tech leaders unveiled a raft of new products, services and features designed to help customers do more with artificial intelligence. NTT Data has created and deployed a small language model called Tsuzumi, described as an ultra-lightweight model designed to reduce learning and inference costs. According to NTT’s UK and Ireland CTO, Tom Winstanley, the reason for developing this model has principally been to support edge use cases. “[That is] literally deployment at the edge of the network to avoid flooding of the network, also addressing privacy concerns, also addressing sustainability concerns around some of these very large language models being very specific in creating domain context,” he says.   “Examples of that can be used in video analytics, media analytics, and in capturing conversations in real time, but locally, and not deploying it out to flood the network. That said, the flip side of this was there was immense power sitting in some of these central hyper-scale models and capacities, and you also therefore need to find out more [about] what’s the right network background, and what’s the right balance of your network infrastructure. For example, if you want to do real-time media streaming from a [sports stadium] and do all of the edits on-site, or remotely so not to have to deploy [facilities] to every single location, then you need a different backbone, too.”  Winstanley notes that his company is part of a wider group that in media use cases could offer hyper-directional sound systems supported by AI. “This is looking like a really interesting area of technology that is relevant for supporter experience in a stadium – dampening, sound targeting. And then we’re back to the connection to the edge of the AI story. And that’s exciting for us. That is the frontier.”  But coming back from the frontier of technology to bread-and-butter business operations, even if the IT and comms community is confident that it can address any technological issues that arise regarding AI and networking, businesses themselves may not be so sure.  Research published by managed network-as-a-service provider Expereo in April 2025 revealed that despite 88% of UK business leaders regarding AI as becoming important to fulfilling business priorities in the next 12 months, there are a number of major roadblocks to AI plans by UK businesses. These include from employees and unreasonable demands, as well as poor existing infrastructure.   Worryingly, among the key findings of Expereo’s Enterprise horizons 2025 study was the general feeling from a lot of UK technology leaders that expectations within their organisation of what AI can do are growing faster than their ability to meet them. While 47% of UK organisations noted that their network/connectivity infrastructure was not ready to support new technology initiatives, such as AI, in general, a further 49% reported that their network performance was preventing or limiting their ability to support large data and AI projects.  Assessing the key trends revealed in the study, Expereo CEO Ben Elms says that as global businesses embrace AI to transform employee and customer experience, setting realistic goals and aligning expectations will be critical to ensuring that AI delivers long-term value, rather than being viewed as a quick fix. “While the potential of AI is immense, its successful integration requires careful planning. Technology leaders must recognise the need for robust networks and connectivity infrastructure to support AI at scale, while also ensuring consistent performance across these networks,” he says.  Summing up the state of the industry, Elms states that business is currently at a pivotal moment where strategic investments in technology and IT infrastructure are necessary to meet both current and future demands. In short, reflecting Düsener’s point about Swisscom’s aim to reduce the impact of service changes, reduce the risk of downtime and costs, and improve customer services. Just switching on any AI system and believing that any answer is “out there” just won’t do. Your network could very well tell you otherwise.  Through its core Catia platform and its SolidWorks subsidiary, engineering software company Dassault Systèmes sees artificial intelligence (AI) as now fundamental to its design and manufacturing work in virtually all production industries. Speaking to Computer Weekly in February 2025, the company’s senior vice-president, Gian Paolo Bassi, said the conversation of its sector has evolved from Industry 4.0, which was focused on automation, productivity and innovation without taking into account the effect of technological changes in society.   “The industry has decided that it’s time for an evolution,” he said. “It’s called Industry 5.0. At the intersection of the experience economy, there is a new, compelling necessity to be sustainable, to create a circular economy. So then, at the intersection, [we have] the generative [AI] economy.” Yet in aiming to generate gains in sustainability through Industry 5.0, there is a danger that the increased use of AI could potentially see increased power usage, as well as the need to invest in much more robust and responsive connected network infrastructure to support the rise in AI-based workloads.  Dassault first revealed it was working with generative AI design principles in 2024. As the practice has evolved, Bassi said it now captures two fundamental concepts. The first is the ability of AI to create new and original content based on language models that comprise details of processes, business models, designs of parts assemblies, specifications and manufacturing practices. These models, he stressed, would not be traditional, generic, compute-intensive models such as ChatGPT. Instead, they would be vertical, industry-specific, and trained on engineering content and technical documentation.  “We can now build large models of everything, which is a virtual twin, and we can get to a level of sophistication where new ideas can come in, be tested, and much more knowledge can be put into the innovation process. This is a tipping point,” he remarked. “It’s not a technological change. It’s a technological expansion – a very important one – because we are going to improve, to increase our portfolio with AI agents, with virtual companions and also content, because generative AI can generate content, and can generate, more importantly, know-how and knowledge that can be put to use by our customers immediately.” This tipping point means the software provider can bring knowledge and know-how to a new level because, in Bassi’s belief, this is what AI is best at: exploiting the large models of industrial practices. And with the most important benefit of addressing customer needs as the capabilities of AI are translated into the industrial world, offering a pathway for engineers to save precious time in research and spend more time on being creative in design, without massive, network-intensive models. “Right now, there is this rush to create larger and more comprehensive models. However, it may [just] be a temporary limitation of the technology,” Bassi suggested. “In fact, it is indeed possible that you don’t need the huge models to do specific tasks.”