Supercar Blondie Is Going Into the Auction Business

Social media personality Supercar Blondie, a London-based Australian whose real name is Alex Hirschi, found her niche posting automotive eyecandy for eager viewers rather accidentally.

“I started out as a journalist, and I just fell into cars through my radio show,” says Hirschi.

For someone who “fell into” cars, they’ve certainly been good to her—the Supercar Blondie network of social channels that includes Supercarblondie.com has 110 million subscribers, including 18.4 million on YouTube and 56 million on Facebook. The content has 2 billion views per month, according to the company.

Alex and Nik Hirschi, the Supercar Blondie couple, in Las Vegas.
Jim Motavalli photo

Hirschi, whose first car was a lowly Mitsubishi Lancer, produces the Supercar Blondie content with her husband, Nik Hirschi, who is Swiss. The radio show was on the Arabian Radio Network in Dubai from 2012 to 2017. Dubai is full of supercars, and Hirschi, then known as “Radio Blondie,” said it was a natural fit to drive some of them—Bentleys, McLarens, Ferraris—for on-air features. The independent Supercar Blondie content creation company was launched in Dubai (where Nik Hirschi worked at Bloomberg, Barclays, and Thomson Reuters) in 2017 and has been growing ever since.

“I just loved supercars, and what started out as a hobby after I was loaned a Bentley Flying Spur to drive around Dubai eventually got more serious,” Alex Hirschi says. “We started filming my encounters with cars and uploading the video to our channel.” These days the couple travels 300 days a year; Penta first caught up with them at the Consumer Electronics Show in Las Vegas .

The Tyde Icon electric hydrofoil uses BMW batteries.
SBX Cars Photo

And now SB Media Group, based in London with 65 employees, Nik as CEO and Alex as the co-founder and on-air talent, is going into the auto auction business. SBX Cars, based in California, launched this week. The inaugural inventory goes beyond cars, and includes an electric Tyde hydrofoil yacht designed by BMW. There’s also a no-reserve Tesla Cybertruck, a one-of-nine Lamborghini Veneno Roadster, and a one-of-three Lamborghini Veneno Coupe. Likely attracting attention will be the first public auctions of the Mercedes-AMG One and the Hyperion XP-1 hydrogen-powered prototype. There were three LaFerrari prototypes, and one will be auctioned by SBX Cars.

A collection of John Player Special Lotus F1 racing cars will also be auctioned, as well as Lotus transporters, and founder Colin Chapman’s personal plane and some vehicles from his garage. Other high-dollar items include a Mercedes 300SL “Gullwing,” a Lamborghini Miura, a BMW 507, and an Aston Martin DB5. The estimated valuation of the auction lots consigned is US$100 million.

The Mercedes-AMG One was limited to 275 units.
SBX Cars Photo

The auctions will be online, but there could be some in-person events in the future. “We’re going to be the only digital auction site that focuses on the high end,” Nik Hirschi says. “We will focus on cars that are super-cool, with many that are one-of-a-kind, and we’re going to be attracting collectors from all over the world. Every car will be represented on the site with 200 photographs, taken by our global network.” Video will also be available.

SBX Cars says it will speed up the process for consignors, with just a few weeks until their cars become available on the site. Once up, the vehicles will remain available for one to two weeks. SBX Cars Auction Director Lance Butler, a Bonhams veteran, said in a statement that the auction “introduces our clients to a far easier buying and selling process, all while accessing one of the world’s largest global audiences by way of Supercar Blondie.”

The prototype Hyperion XP-1.
SBX Cars Photo

Mercedes 300SLs, Aston Martin DB5s, and BMW 507s are frequently auctioned around the globe, but SBX features some true exotics.

A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.

The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.

The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.

The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.

This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.

The debt behind the AI build-out

Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.

Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.

JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.

The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.

That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.

A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.

When interest rates rise, those assumptions become less forgiving.

Inflation changes the calculation

September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.

The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.

CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.

Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.

Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.

The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.

China adds another source of pressure

Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.

Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.

The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.

That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.

A reset rather than the end of the boom

The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.

What has changed is the market’s willingness to overlook the price and financing structure of that growth.

The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.

More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.

For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.

Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.

The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.

Fact box

Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026

Philadelphia Semiconductor Index: Down approximately 11.4 per cent

Micron Technology: Down approximately 14.6 per cent

Samsung Electronics: Down approximately 18 per cent

SK Hynix: Down approximately 24 per cent

US September inflation: 3.7 per cent annually

Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion