It’s becoming clearer that we are in a perilous financial situation globally. Fears over an “AI bubble” are being cited by the Bank of England, the International Monetary Fund and the boss of JP Morgan, Jamie Dimon.
If you want a sense of how insane the narrative is around AI investments, consider this: Thinking Machines Lab, an AI startup, recently raised $2bn funding on a valuation of $10bn.
The company has zero products, zero customers and zero revenues. The only thing it made public to its investors was the resume of its founder, Mira Murati, formerly chief technology officer at OpenAI. If that’s not hubris meeting market exuberance, what is?
But narrative is crucial here because it’s what’s driving all this insane investment in the future of AI or so-called artificial general intelligence (AGI), and it’s important to examine which narrative you believe in if you are to protect yourself for what’s to come.
If I were to pick between the views of a politician such as UK prime minister Keir Starmer, and a writer such as Cory Doctorow, I’d put my bet on Doctorow. Contrast these two statements and see which you feel more comfortable with…
Doctorow suggests the AI bubble needs to be punctured as soon as possible to “halt this before it progresses any further and to head off the accumulation of social and economic debt”.
He suggests doing that by taking aim at the basis for the AI bubble – namely, “creating a growth story by claiming that AI can do your job”.
AI is the asbestos we are shovelling into the walls of our society and our descendants will be digging it out for generations Cory Doctorow
Claims about jobs disappearing to AI have been around since 2019 with Sam Altman, then leader of venture capital (VC) fund Y Combinator, speaking about radiology jobs disappearing in the future: “Human radiologists are already much worse than computer radiologists. If I had to pick a human or an AI to read my scan, I’d pick the AI.”
Fast forward six years to 2025 and look how that worked out. According to a recent report by Works in Progress, despite the fact that radiology combines digital images, clear benchmarks and repeatable tasks, demand for human radiologists is at an all-time high.
The report authors’ conclusions drive a horse and cart through the current AI/AGI narrative that if left unstopped will cause severe global economic pain: “In many jobs, tasks are diverse, stakes are high, and demand is elastic. When this is the case, we should expect software to initially lead to more human work, not less. The lesson from a decade of radiology models is neither optimism about increased output nor dread about replacement. Models can lift productivity, but their implementation depends on behaviour, institutions and incentives. For now, the paradox has held – the better the machines, the busier radiologists have become.”
Across other sectors too, the mythology around job losses is slowly being interrogated – for example, Yale University Budget Lab found no discernible disruption to labour markets since ChatGPT’s release 33 months ago.
The research goes on to state: “While this finding may contradict the most alarming headlines, it is not surprising given past precedents. Historically, widespread technological disruption in workplaces tends to occur over decades, rather than months or years. Computers didn’t become commonplace in offices until nearly a decade after their release to the public, and it took even longer for them to transform office workflows. Even if new AI technologies will go on to impact the labour market as much, or more dramatically, it is reasonable to expect that widespread effects will take longer than 33 months to materialise”.
Normal technology
In other words, AI is just, well, technology as we have always known it – or as experts Aryind Narayanan and Sayash Kapoor call AI, just “normal technology”.
Importantly in their paper, AI as normal technology – An alternative to the vision of AI as a potential superintelligence, they identify key lessons from past technological revolutions – the slow and uncertain nature of technology adoption and diffusion; continuity between the past and future trajectory of AI in terms of social impact; and the role of institutions in shaping this trajectory. They also “strongly disagree with the characterisation of generative AI adoption as rapid, which reinforces our assumption about the similarity of AI diffusion to past technologies”
A good example of AI as normal technology without all the hype, hyperbole and billion-dollar burn rate, is the City of Austin, Texas. Here, an on-premise AI system helped the local government process building permits in days instead of months.
According to David Stout, CEO of WebAI, this was done “with no spectacle. No headlines. Just efficiency gains that will outlast the market cycle. He said, “That’s the point too often missed in the frenzy. Mega-models attract headlines, consume billions in capital, and struggle to demonstrate sustainable economics. Meanwhile, smaller, domain-specific systems are already delivering efficiency gains, cost savings and productivity improvements. The smart play isn’t to abandon AI, but to pivot towards models and deployments that will endure”.
Technology like we have always known it to be – not the insane fantasy of “superintelligence” that is powering this dangerous bubble.
The question to ask is, given the prediction of at least a 33-month lag before any return on investment, however small, will the markets wait another 33 months for their returns to materialise?
Protracted crisis
A recent report on MarketWatch suggests the AI bubble is now ”seventeen times the size of the dot com frenzy and four times the sub-prime bubble”. MarketWatch quotes financial analyst Julien Garran, who previously led UBS’s commodities strategy team, who said “AI now accounts for over four times the wealth trapped in the 2008 sub-prime mortgage bubble, which resulted in years of protracted crisis across the globe”.
Warnings from the Bank of England in its semi-annual Financial Policy Committee report are equally stark: “Uncertainty around the global risk environment increases the risk that markets have not fully priced in possible adverse outcomes, and a sudden correction could occur should any of these risks crystallize.”
The bank also warned of “the risk of a sharp market for global financial markets amid AI bubble risks and political pressure on the Federal Reserve.”
What a sudden correction means is that a collapse of the AI investment bubble will take trillions of investment with it, impacting us all.
Even more worrying is the issue of debt financing among those competing in the AI race – that is, all the tech bros. It now appears, according to Axios, that these companies are turning to private debt markets and special purpose vehicles for cash, which means this kind of borrowing does not have to show on their balance sheets.
Meta, for example, recently sought $29bn from private capital firms for its AI datacentres. This off-book debt financing should ring more alarm bells that something is terribly wrong with the AI growth narrative.
After all, as pointed out by the Axios analysts, “If hugely profitable tech companies need to mask their borrowings to fund AI spending, it signals they’re not confident that they’ll soon get the returns needed to justify such investments. That suggests the very spending powering today’s earnings boom can’t last forever.”
Unit economics
To go back to Cory Doctorow’s argument, we are not in the early days of the web, or Amazon, or other dot com companies that lost money before becoming profitable: “Those were all propositions with excellent unit economics. They got cheaper with every successive technological generation and the more customers they added, the more profitable they became”.
AI companies do not have excellent unit economics – in fact they have the opposite, according to Doctorow: “Each generation of AI has been vastly more expensive than the previous one, and each new AI customer makes the AI companies lose more money”.
[Only] about 5% of tasks will be able to be profitably performed by AI within 10 years Daron Acemoglu
And if that’s not sobering enough for the VC and private equity firms, then the circular investing going on between these tech firms should be a huge concern.
Microsoft is investing $10bn in OpenAI by giving free access to its servers. OpenAI reports this as an “investment,” then redeems these tokens at Microsoft datacentres, which Microsoft books as $10bn in revenue.
Bain & Co says the only way to make today’s AI investments profitable “is for the sector to bring in $2tn by 2030,” which, according to the Wall Street Journal, is more than the revenue of Amazon, Google, Microsoft, Apple, Nvidia and Meta – combined.
Taking a closer look at US economic growth is surely more cause for concern.
According to Harvard economist Jason Furman’s analysis, GDP growth in the first half of 2025 was driven almost entirely by investment in information processing equipment and software. This spending was largely tied to the rapid expansion of AI infrastructure and datacentres.
While these tech sectors only made up 4% of total GDP, they contributed a staggering 92% of growth. Absent this investment, Furman estimates US GDP growth would have hovered around 0.1% on an annualised basis – barely above zero.
There is a lot riding on a technology that’s supposed to be godlike and all powerful but which, according to MIT Institute professor Daron Acemoglu, is far less likely to achieve the insane hyperbolic claims being made by the tech bros in an effort to win an unwinnable race.
Acemoglu estimates the 10-year effect of AI in the US will be that only “about 5% of tasks will be able to be profitably performed by AI within that timeframe,” with the GDP boost likely to be closer to 1% over that timespan. If that’s not a recipe for stock market collapse, what is?
Emperor’s new clothes
Going back to the AI booster narrative and how it’s driving things, Doctorow is again incisive: “The most important thing about AI isn’t its technical capabilities or limitations. The most important thing is the investor story and the ensuing mania that has teed up an economic catastrophe that will harm hundreds of millions or even billions of people. AI isn’t going to wake up, become super intelligent and turn you into paperclips – but rich people with AI investor psychosis are almost certainly going to make you much, much poorer”.
I’m not an economist, so I did what we are all supposed to do now for our enlightenment. I gave the machines built by the tech bros all the same prompt: “What fable best encapsulates the current AI bubble?”
Gemini, Perplexity and ChatGPT were all in agreement with nearly the same explanation of why they all picked the same story: “The emperor’s new clothes remains the best classic fable to explain the AI bubble, as it encapsulates the collective willingness to believe in – and profit from – an imagined reality, until facts and external shocks eventually break the spell.”
Coats Digital is delighted to announce that VTL Group, one of the largest vertically integrated textile manufacturers in the Mediterranean region, has adopted Coats Digital’s GSDCost solution to standardise production methods, increase productivity, and improve pricing accuracy across its Tunisian operations. The initiative is already showing a significant impact, with VTL reducing standard minute values (SMVs) by 15–20% and increasing line output by 10% across its three, key sewing facilities.
With over 5,000 employees and 3,000 sewing machines across 90 sewing lines, VTL Group specialises in jersey knits and denim, producing up to 20 million garments per year for world-renowned brands such as Lacoste, Adidas, G-Star, Hugo Boss, Replay and Paul & Shark. The company operates six garment production units, along with dedicated facilities for screen printing, knitting, dyeing and textile finishing. This extensive vertical integration gives VTL complete control over quality, lead-times and cost-efficiency, which is vital for meeting the stringent demands of its global customer base.
VTL Group has adopted Coats Digital’s GSDCost to standardise production, boost productivity, and improve pricing accuracy across its Tunisian operations.
The solution cut SMVs by 15–20 per cent, raised line output by 10 per cent, and enhanced planning, cost accuracy, and customer confidence, enabling competitive pricing, lean operations, and stronger relationships with global fashion brands.
Prior to implementing GSDCost, VTL calculated capacity and product pricing using data from internal time catalogues stored in Excel. This approach led to inconsistent and inaccurate cost estimations, causing both lost contracts due to inflated production times and reduced margins from underestimations. In some cases, delays caused by misaligned time predictions resulted in increased transportation costs and operational inefficiencies that impacted customer satisfaction.
Hichem Kordoghli, Plant Manager, VTL Group, said: “Before GSDCost, we struggled with inconsistent operating times that directly impacted our competitiveness. We lost orders when our timings were too high and missed profits when they were too low. GSDCost has transformed the way we approach planning, enabling us to quote confidently with accurate, reliable data. We’ve already seen up to 20% reductions in SMVs, a 10% rise in output, and improved customer confidence. It’s a game-changer for our sales and production teams.”
Since adopting GSDCost across 50 sewing lines, VTL Group has been able to establish a reliable baseline for production planning and line efficiency monitoring. This has led to a more streamlined approach to managing load plans and forecasting. Importantly, GSDCost has given the business the flexibility to align pricing more effectively with actual production realities, contributing to greater customer satisfaction and improved profit margins.
Although it’s too early to determine the exact financial impact, VTL Group has already realised improvements in pricing flexibility and competitiveness thanks to shorter product times and better planning. These gains are seen as instrumental in enabling the company to pursue more strategic orders, reduce wasted effort and overtime, and maintain the high expectations of leading global fashion brands.
Hichem Kordoghli, Plant Manager, VTL Group, added: “GSDCost has empowered our teams with reliable data that has translated directly into real operational benefits. We are seeing more consistent line performance, enhanced planning precision, and greater confidence across departments. These improvements are helping us build stronger relationships with our brand partners, while setting the foundation for sustainable productivity gains in the future.”
The company now plans to expand usage across an additional 30 lines in 2025, supported by a second phase of GSD Practitioner Bootcamp training to strengthen in-house expertise and embed best practices throughout the production environment. A further 10 lines are expected to follow in 2026 as part of VTL’s phased rollout strategy.
Liz Bamford, Customer Success Manager, Coats Digital, commented: “We are proud to support VTL Group in their digital transformation journey. The impressive improvements in planning accuracy, quoting precision, and cross-functional alignment are a testament to their commitment to innovation and excellence. GSDCost is helping VTL set a new benchmark for operational transparency and performance in the region, empowering their teams with the tools needed for long-term success.”
GSDCost, Coats Digital’s method analysis and pre-determined times solution, is widely acknowledged as the de-facto international standard across the sewn products industry. It supports a more collaborative, transparent, and sustainable supply chain in which brands and manufacturers establish and optimise ‘International Standard Time Benchmarks’ using standard motion codes and predetermined times. This shared framework supports accurate cost prediction, fact-based negotiation, and a more efficient garment manufacturing process, while concurrently delivering on CSR commitments.
Key Benefits and ROI for VTL Group
15–20% reduction in SMVs across 50 production lines
10% productivity increase across key sewing facilities
More competitive pricing for strategic sales opportunities
Improved cost accuracy and quotation flexibility
Standardised time benchmarks for future factory expansion
Enhanced planning accuracy and load plan management
Greater alignment with lean and sustainable manufacturing goals
Increased brand confidence and satisfaction among premium customers
Note: The headline, insights, and image of this press release may have been refined by the Fibre2Fashion staff; the rest of the content remains unchanged.
No matter how my style may change, I always consider Adidas the ultimate shoes for effortlessly cool people. With celebrity endorsements from pro athletes like David Beckham to music icons like Pharrell and Bad Bunny, Adidas has cemented itself firmly in the current zeitgeist. Although most known for classic sneaker styles like Sambas (beloved by skaters and boys I had crushes on in high school), Adidas also has always-stylish apparel, slides, running shoes, and more. WIRED has Adidas promo codes so you too can be cool—but on a budget.
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Tencia Benavidez, a Supernatural user who lives in New Mexico, started her VR workouts during the Covid pandemic. She has been a regular user in the five years since, calling the ability to workout in VR ideal, given that she lives in a rural area where it’s hard to get to a gym or workout outside during a brutal winter. She stuck with Supernatural because of the community and the eagerness of Supernatural’s coaches.
“They seem like really authentic individuals that were not talking down to you,” Benavidez says. “There’s just something really special about those coaches.”
Meta bought Supernatural in 2022, folding it into its then-heavily invested in metaverse efforts. The purchase was not a smooth process, as it triggered a lengthy legal battle in which the US Federal Trade Commission tried to block Meta from purchasing the service due to antitrust concerns about Meta “trying to buy its way to the top” of the VR market. Meta ultimately prevailed. At the time, some Supernatural users were cautiously optimistic, hoping that big bag of Zuckerbucks could keep its workout juggernaut afloat.
“Meta fought the government to buy this thing,” Benavidez says. “All that just for them to shut it down? What was the point?”
I reached out to Meta and Supernatural, and neither responded to my requests for comment.
Waking Up to Ash and Dust
On Tuesday, Bloomberg reported that Meta has laid off more than 1,000 people across its VR and metaverse efforts. The move comes after years of the company hemorrhaging billions of dollars on its metaverse products. In addition to laying off most of the staff at Supernatural, Meta has shut down three internal VR studios that made games like Resident Evil 4 and Deadpool VR.
“If it was a bottom line thing, I think they could have charged more money,” Goff Johnson says about Supernatural. “I think people would have paid for it. This just seems unnecessarily heartless.”
There is a split in the community about who will stay and continue to pay the subscription fee, and who will leave. Supernatural still has more than 3,000 lessons available in the service, so while new content won’t be added, some feel there is plenty of content left in the library. Other users worry about how Supernatural will continue to license music from big-name bands.
“Supernatural is amazing, but I am canceling it because of this,” Chip told me. “The library is large, so there’s enough to keep you busy, but not for the same price.”
There are other VR workout experiences like FitXR or even the VR staple Beat Saber, which Supernatural cribs a lot of design concepts from. Still, they don’t hit the same bar for many of the Supernatural faithful.
“I’m going to stick it out until they turn the lights out on us,” says Stefanie Wong, a Bay Area accountant who has used Supernatural since shortly after the pandemic and has organized and attended meetup events. “It’s not the app. It’s the community and it’s the coaches that we really, really care about.”
Welcome to the New Age
I tried out Supernatural’s Together feature on Wednesday, the day after the layoffs. It’s where I met Chip and Alisa. When we could stop to catch our breath, we talked about the changes coming to the service. They had played through previous sessions hosted by Jane Fonda or playlists with a mix of music that would change regularly. It seems the final collaboration in Supernatural’s multiplayer mode will be what we played now, an artist series featuring entirely Imagine Dragons songs.
In the session, as we punched blocks while being serenaded by this shirtless dude crooning, recorded narrations from Supernatural coach Dwana Olsen chimed in to hype us up.
“Take advantage of these moments,” Olsen said as we punched away. “Use these movements to remind you of how much awesome life you have yet to live.”
Frankly, it was downright invigorating. And bittersweet. We ended another round, sweaty, huffing and puffing. Chip, Alisa, and I high-fived like crazy and readied for another round.
“Beautiful,” Alisa said. “It’s just beautiful, isn’t it?”
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