Gaze Upon the Quirkiest Electric Vehicle You’ve Ever Seen

When I was in college, I worked at a place that bought, sold and consigned classic cars. I was a shop mechanic, and a Subaru 360 passed through. I fell in love with it, and, about a year later, one popped up for sale on Facebook. I paid $US1,200 for it.

The 360 was the first Subaru imported into the U.S., in 1968. A guy named Malcolm Bricklin imported them. He later started his own car company that failed. [According to Subaru’s website, the 360 sold for $US1,297, got 66.3 mpg and was marketed as “cheap and ugly.”] The car did not sell very well. My 360 was not in good shape at all. The motor was disassembled and missing pieces. The cylinders were rusted. The bottom half of the car was mostly rotted out.

At the time, I had just started working as a nurse. Covid was a rough time if you were a hospital worker. I did a lot of ICU work. This car became my Covid project, to get my mind off of work. A lot of it was done when I’d get home, between midnight and 3 a.m. In the summer heat of Mississippi, it’s a good time to work in the garage. It became a “can-I-do-it” project.

I spent about two years just on rust repair. I took the transmission apart. I was able to flush it out and clean it. The brakes were a project. They don’t make parts for this car, so all the parts had to be sourced from different cars and different model years.

For power, I took the electric motor and mounting plate out of a Taylor-Dunn truck. (If you don’t know what this is, you might remember one from the scene in “Austin Powers: International Man of Mystery” when he is riding this little truck and gets stuck in a hallway.) I used the control box out of an E-Z-GO golf cart. So now the 360 runs on electric power.

The goal was never about making an electric car, specifically. I was just trying to get it going with whatever I had lying around and stuff that people gave me. I had to get two sprockets custom made, by a company here in Jackson, Miss., called Motion Industries.

A lot of people in the Subaru community were helpful, through the 360 Facebook page. These cars are so rare these days, and the parts are so hard to find, people are just happy to see them not end up in the crusher. Especially one as bad off as this car was when I started out.

A lot of people also helped me right in my garage. My dad was an electrical engineer for many years, and he helped with the wiring and other stuff. My grandfather, a neighbour, my uncle all helped, too.

Along the way, we took the 360 to car shows, a lot of them locally around Jackson, and one as far off as Ardmore, Tenn. The first time we took it to a show, it had no brakes and we had to roll it up to the judging station with our feet hanging out the doors to make sure we could stop it. Every show we took it to, it had reached another stage, and some people really enjoyed seeing the progress.

I think the car could be street legal, but right now it’s not. Where I live, a lot of the roads are minimum 55 mph. This car has a top speed of about 30 mph. But I have invested so much time in it, and with the help of my friends and family, it means a lot to all of us.

Nowadays, you see Subarus everywhere. But you won’t see many 360s, and you won’t see any other Subaru like this one.

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