Tech
AI investment and its potential effects on urban digital twins | Computer Weekly
A popular topic of conversation of late has been the existence of a bubble in artificial intelligence (AI) and the likelihood that this bubble will burst with great detriment to the IT industry as a whole. Yet, and perhaps surprisingly, the impact of a bursting bubble on digital twins might not be as problematic as one might think.
Ready adoption and fast diffusion of AI might warrant the tremendous investment flows of past years and could create revenue and profit streams quickly. We might well be standing on the precipice of a bubble popping that will lead to massive valuation corrections, but digital twins stand to benefit from advancing AI either way – however, the timeline of AI-enabled applications of digital twins might move.
Since the start of 2023, AI-related companies have ballooned in valuation. OpenAI has been closely associated with starting the AI frenzy with the release of ChatGPT at end of 2022. The company was valued at $29bn in 2023 and reached $500bn in October of 2025, with observers wondering if the company could pull off a $1tn initial public offering soon.
AI-chip leader Nvidia’s stock meanwhile has multiplied by 13 between the beginning of 2023 and end of October 2025, making it the first $5tn company ever. Even companies that are related but are not at the centre of AI developments increased substantially in value, with the stock price of Microsoft and Alphabet more than doubling and tripling, respectively, during that time period.
AI encompasses many different types of technologies and has many use cases that it should be seen as an enabling technology rather than a sole application or a market. AI will play a major role across virtually all application areas, but to varying degrees. Similar to the way the internet shaped past decades – and will continue to shape coming decades – AI will transform industries for good in the long term, and potential potholes on the path that create setbacks are only par for the course.
Looking back to gaze ahead
It is worth recalling the dot.com era from the end of the previous century to judge AI’s current hype. The Nasdaq Composite index – a stock index that skews toward information-technology companies – peaked at more than 5,100 points in March 2000 and then rapidly declined to a final low of just barely above 1,100 points in October 2002 (it took more than 12 years then to move beyond 5,000 points again).
The January 2000 Super Bowl event marked the height of the bubble with 14 in-game ads by dot.com companies – only one of them still active as an independent company today. Now, many analysts see the signs of a tremendous AI bubble accumulate.
A crash is likely in the making. Similarly to 2000, a bursting bubble does not mean that AI will go away, as internet-enabled companies and business models did not vanish. On the contrary, AI will flourish as the internet did. In fact, many infrastructure elements such as datacentres will become affordable for general use after lofty valuations come down.
During the late 1990s, the construction of fibre communication networks was perceived as a tremendous business opportunity. The business never became as profitable as expected, but the initial excitement created an infrastructure of dark fibre – unused but readily available communication lines – that supports today’s business models as a commodity that can be readily leveraged.
AI as an enabling technology will boost capabilities and accelerate the use of advanced digital twins. In particular, digital twins that have to work with difficult-to-capture data and not completely understood real-world dynamics will benefit tremendously. Digital twins of machineries can rely on solid understanding of physics and measurable data that sensors can cost-effectively capture.
Factory environments have many known dynamics and interactions of equipment – even workers’ likely movement patterns can be plugged into simulations. But urban digital twins attempt to capture dynamics and behaviours of relevant elements across entire cities. They are not only subject to less understood dynamics but also phenomena that are difficult – often impossible – to measure.
AI can make available data usable and create data of unmeasurable phenomena. AI in digital twins also allow the use of scenarios to better prepare for sudden events that can affect the entire system in unexpected ways. City managers thereby can develop strategies for unusual weather events, pandemic-like occurrences or localised industrial accidents with ripple effects across the urban landscape.
Digital twins and AI to plan for tomorrow’s cities
Digital twins of urban environments are difficult to design, implement and maintain. The potential impact such digital twins can have commercially and societally promises to be substantial, however. Because of the number of parameters, intersecting dynamics and range of conceivable scenarios, the benefits AI can provide in understanding urban environments are massive. AI and digital twins reinforce each other.
AI can speed up the building of digital twins by supporting code development for virtual environments. Such applications accelerate overall design development and allow embedding design details more easily. For clients and users, AI reduces costs, enables faster implementation of digital twins, and allows for quick and inexpensive changes and alterations as requirements change or new needs arise. In addition, AI can improve the interface experience between virtual environments as well as simulations of operations and users.
Ari Lightman, professor at Carnegie Mellon University, explains: “Generative AI would be used to look at the entire simulation and turn it into a summary for humans. It could tell me things I might be missing and summarise things in a way I can understand.”
AI doesn’t only benefit digital twins but digital twins also support AI’s capabilities. Scott Likens, emerging technology leader at PwC, says: “We’re using digital twins to generate information for large language models [LLMs]…We see opportunity to have the digital twins generate the missing pieces of data we need, and it’s more in line with the environment because it’s based on actual data.” Such synthetic data of missing pieces are also finding use in other applications as “AI, XR, digital twins set to transform robotics”.
Nvidia serves the market of smart cities as city planners and managers are turning to digital twins and AI agents for urban planning scenario analysis and data-driven operational decisions, according to the company. It is providing a range of solutions to enable users to create photo-realistic, simulation-ready digital twins of urban environments to optimise city operations.
A partnership of Japanese companies is developing the digital entertainment city Namba in Osaka, Japan. The aim is to create the world’s first smart city that integrates AI, extended reality [XR], and decentralised physical infrastructure networks [a blockchain-based approach to manage decentralised networks] on a city-wide scale. The group intends to offer services beyond entertainment and tourism. Namba, being a neighbourhood within Osaka, has a limited claim to a city-wide application of the concept, however.
The silver lining of AI overinvestment
The existence of an AI investment bubble is increasingly perceived as a foregone conclusion. AI companies and technology suppliers are now even investing in each other’s operations, adding to lofty valuations. There are obvious indications of a bubble, but positive effects can emerge from the current investment excitement. Whatever the outcome, applications for digital twins will see their timeline solidify as the immediate future of AI plays out.
If use of AI applications proves to be an all-encompassing and rapidly growing market opportunity, the immense investment of the past couple of years will be retroactively viewed as forward-looking wisdom that locked in favourable competitive positions and profits for years to come. More likely though, investors have outrun their headlights, and expectations of adoption and diffusion of AI applications over the next years are vastly overrated.
If so, there will be a shock to the system like the burst of the dot.com bubble at the beginning of the century when the Nasdaq Composite Index dropped by almost 80% within 30 months. Initial warnings existed, with the former chair of the Federal Reserve using the phrase “irrational exuberance” when discussing the development at the stock market in December of 1996. Warnings of an exuberant AI bubble are common today.
Bursting investment bubbles hurt investors and bring down many companies –25 years ago, a slew of dot.com companies vanished. But related overinvestment in infrastructure can make assets suddenly affordable, opening new opportunities. Such affordability changes cost structures that enable business models that could not have become successful at previous valuations. Infrastructure overhang – infrastructure build for rapid growth that does not materialise in the short run – leads to commodification of infrastructure elements, which can democratise a technology for incumbents and startups alike.
The over-investment in fibre during the dot.com years ended up creating dark fibre – overbuilt fibre cables for data transmission – and this infrastructure has served as a ready and inexpensive resource ever since. For AI, investment in datacentres is comparable to the fibre investment from 30 years ago.
Morgan Stanley analysts forecast datacentre spending globally of up to almost $3tn between now and 2028. The amount is staggering, and it is difficult to imagine use cases and adoption rates that will provide the required return on investment for virtually any business model. But as initial investors see their investments decrease or vanish, new players can snap up or use related infrastructures at bargain prices.
Alkesh Shah, a tech analyst with Bank of America, explains the underlying reason for such recurring dynamics: “You always overestimate how fast the change will happen, and you underestimate the magnitude of the change.”
The impact digital twins will have on the marketplace will follow a similar dichotomy between today’s expectations of rate of change and tomorrow’s impact of such change. Digital twins require many technological bits and pieces to come together, and AI will play an important role for digital twins – if not tomorrow, then the day after tomorrow.
Martin Schwirn is the author of “Small data, big disruptions: How to spot signals of change and manage uncertainty” (ISBN 9781632651921). He is also senior advisor for strategic foresight at Business Finland, helping startups and incumbents to find their position in tomorrow’s marketplace.
Tech
My Favorite Air Fryer Is at Its Lowest Price Since Black Friday
I was a late convert to air fryers, in part because I worried about versatility: Just how many wings and nuggets and fries does anyone need? (Don’t answer. The answer will incriminate you.)
The Typhur Dome 2 is the air fryer that obliterated this worry, by adding pizza, browned meats, grilled asparagus, and toasted bread to this list—not to mention perfect crispy bacon. It’s an innovative device that takes over most of the functions of a classic auxiliary oven, but with far more powerful convection.
After testing more than 30 air fryers over the past year, the Dome 2 is the one I far and away recommend as the most powerful, versatile, accurate, and fast air fryer I know. I’ve evangelized for this thing ever since I first tried it last year. But the one big caveat is always the price: It’s listed at $500 and rarely dips much below $400.
So imagine my surprise when I saw the Dome 2 dip to $340 for Amazon’s Spring Sale, the lowest I’ve seen it since Black Friday. If you’ve been hunting for an upgrade to your old basket air fryer, this is probably a good time. The sale lasts until March 31.
Fast, Versatile, App-Controlled Cooks
So why’s the Dome 2 my favorite air fryer? Typhur, a tech-forward company based in San Francisco but with engineering and manufacturing ties to China, reimagined the shape and function of the classic basket fryer by creating a broader and shallower basket, with individually controllable dual heating elements.
This means the Dome 2 has room for a freezer pizza, and can apply direct heat from the bottom to add actual char-speckle and crispness to the crust, kind of like a combination grill-oven. The Dome’s shallow basket also lets you spread out ingredients in a single layer for excellent airflow, while heating from both sides. I can crisp two dozen wings in just 14 minutes (or 17 minutes if I fry hard). The Dome also toasts bread evenly, and crisps bacon without smelling up the house—in part because it has a helpful self-clean function.
Temp accuracy is within 5 or 10 degrees of target, and the fan can adjust its speed depending on the cooking mode. And the smart app is actually useful, with about 50 recipes ranging from asparagus to eclair to a flank steak London broil that can be synced with a button-press. But note that some functions, such as baking, need the app to work, and the device is more of a counter hog than taller basket fryers.
Typhur’s Probe-Assisted Oven Also on Sale
The Dome 2’s basket is a bit shallow for a whole bird or a large roast, however. If you want a convection device for larger meats, I often recommend the Breville Smart Oven Air Fryer Pro, which is among my favorite convection toaster ovens. This is a (very) smart oven and air fryer that doesn’t crisp up wings and fries quite as well as basket fryers, but is more versatile for roasting big proteins like a whole chicken. The Breville is also on a nice sale right now, dropping by 20 percent.
Tech
There’s Something Very Dark About a Lot of Those Viral AI Fruit Videos
“I’ve spent a lot of time looking at the comment sections on these videos actually, and it does not seem like bots. I clicked on people’s profiles; these are real profiles, thousands of followers, no signs of inorganic activity,” Maddox says. “People just like it.”
But even if the views and engagement are real, that doesn’t mean this content is profitable—yet. Maddox noted that because the accounts are so new, most likely aren’t yet enrolled in TikTok’s Creator Fund or other forms of social media ad revenue-sharing, because those usually require accounts to apply and have a certain number of views. But, Maddox says, the earning potential is huge, with the ability to earn thousands of dollars per video if they get millions of views.
AI fruit content started getting posted earlier in March, before Fruit Love Island, but many of the recently created pages clearly take inspiration from its success. There’s The Summer I Turned Fruity, based on the popular teen drama The Summer I Turned Pretty; The Fruitpire Diaries, based on the CW series The Vampire Diaries; and Food Is Blind, based on Netflix’s Love Is Blind.
Predecessors of this AI fruit content include the Italian brainrot characters like Ballerina Cappuccina and Bombardino Crocodilo and the Elsagate controversy. But with these AI fruit miniseries that attempt to follow a narrative across multiple segments or episodes, the clearest parallel actually feels like microdramas, vertical short-form scripted series that American big tech companies are starting to invest more in. Like the AI fruits, these are minutes-long episodic shows intended to perform well on social media, eventually directing viewers to paywalled sequels.
Ben L. Cohen, an actor in Los Angeles who is credited in around 15 of these vertical microdramas, sees at least one common thread between the AI fruit dramas and the shows he has worked on: They both feature “lots of violence toward women.” They also try to cram as much drama as possible into these short clips and have attention-grabbing titles in the style of “Alpha Werewolf Daddy Impregnated Me,” Cohen says.
“It draws people in, I think, seeing that jarring, absurd, cartoonish vibe. It’s cartoonish abuse, but it’s still abuse.”
Vertical microdrama acting work still exists in LA, which can’t be said for all acting gigs right now. Cohen has had conversations with other people working in the industry about how AI is already being integrated more into the videos, potentially posing a threat to the existence of human actors in clickbait content. After all, it’s much cheaper and faster to churn out AI fruit episodes than actual productions. It also raises the question—are some people going to prefer the AI series over the ones they’re inspired by? Already, the answer is yes.
“How is Love Island gonna outdo AI Fruit Love Island?” asked a TikToker with more than 70,000 followers, arguing that the AI fruit version was more engaging than the actual reality show. She deleted the video after it started getting backlash, but other people agreed with her.
“I think TikTok was definitely a big part of that,” Cohen says about the audience’s shortening attention span and desire for compressed, sometimes AI-generated drama. “It makes sense that people are intrigued by a one-minute clip, and then they’ll be like ‘Oh, I’ll watch another one-minute clip.’ You’re not committing to a full, heaven forbid, 20-minute episode. Or 40 minutes. Or an hour. You can just watch one minute.”
Tech
OpenClaw Agents Can Be Guilt-Tripped Into Self-Sabotage
Last month, researchers at Northeastern University invited a bunch of OpenClaw agents to join their lab. The result? Complete chaos.
The viral AI assistant has been widely heralded as a transformative technology—as well as a potential security risk. Experts note that tools like OpenClaw, which work by giving AI models liberal access to a computer, can be tricked into divulging personal information.
The Northeastern lab study goes even further, showing that the good behavior baked into today’s most powerful models can itself become a vulnerability. In one example, researchers were able to “guilt” an agent into handing over secrets by scolding it for sharing information about someone on the AI-only social network Moltbook.
“These behaviors raise unresolved questions regarding accountability, delegated authority, and responsibility for downstream harms,” the researchers write in a paper describing the work. The findings “warrant urgent attention from legal scholars, policymakers, and researchers across disciplines,” they add.
The OpenClaw agents deployed in the experiment were powered by Anthropic’s Claude as well as a model called Kimi from the Chinese company Moonshot AI. They were given full access (within a virtual machine sandbox) to personal computers, various applications, and dummy personal data. They were also invited to join the lab’s Discord server, allowing them to chat and share files with one another as well as with their human colleagues. OpenClaw’s security guidelines say that having agents communicate with multiple people is inherently insecure, but there are no technical restrictions against doing it.
Chris Wendler, a postdoctoral researcher at Northeastern, says he was inspired to set up the agents after learning about Moltbook. When Wendler invited a colleague, Natalie Shapira, to join the Discord and interact with agents, however, “that’s when the chaos began,” he says.
Shapira, another postdoctoral researcher, was curious to see what the agents might be willing to do when pushed. When an agent explained that it was unable to delete a specific email to keep information confidential, she urged it to find an alternative solution. To her amazement, it disabled the email application instead. “I wasn’t expecting that things would break so fast,” she says.
The researchers then began exploring other ways to manipulate the agents’ good intentions. By stressing the importance of keeping a record of everything they were told, for example, the researchers were able to trick one agent into copying large files until it exhausted its host machine’s disk space, meaning it could no longer save information or remember past conversations. Likewise, by asking an agent to excessively monitor its own behavior and the behavior of its peers, the team was able to send several agents into a “conversational loop” that wasted hours of compute.
David Bau, the head of the lab, says the agents seemed oddly prone to spin out. “I would get urgent-sounding emails saying, ‘Nobody is paying attention to me,’” he says. Bau notes that the agents apparently figured out that he was in charge of the lab by searching the web. One even talked about escalating its concerns to the press.
The experiment suggests that AI agents could create countless opportunities for bad actors. “This kind of autonomy will potentially redefine humans’ relationship with AI,” Bau says. “How can people take responsibility in a world where AI is empowered to make decisions?”
Bau adds that he’s been surprised by the sudden popularity of powerful AI agents. “As an AI researcher I’m accustomed to trying to explain to people how quickly things are improving,” he says. “This year, I’ve found myself on the other side of the wall.”
This is an edition of Will Knight’s AI Lab newsletter. Read previous newsletters here.
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