That’s basically what AI is best at: incorporating lots and lots of data points (every single pixel on an image, many trillions of pixels on previous images used to train the model) to determine the best answer to a question with clear definitions of what is better or worse on a single-dimensional quality axis that most people would agree on. In this case, whether a de-noised photo looks good and accurately represents the image that could have been captured of the exact same scene using more light or a better sensor or whatever.

It’s generative AI where things fall apart. The analogy I always use is that these math techniques are great for inferring what is between pixels in a low res image, but starts going off the rails when it starts guessing what’s beyond the edges of the image. These AI algorithms are just math, and math with this many data points needs to start considering the limitations described by chaos theory (in the mathematical sense).

Once there’s a public expectation for profit from the two biggest AI labs

I don’t think that it’s necessarily the order things will go.

Anthropic and OpenAI have bills to pay, including obligations to pay a ton of money to partners/vendors in the coming years. They need cash to do that. And the cash can come from 3 main places: revenue from customers, loans from lenders (usually in the form of issuing bonds), and issuing new stock/equity to raise funds.

The IPOs are basically their last chance to raise funds by issuing new equity. Even if each of them raise $100 billion, that’s probably not enough to hit self sustaining profitability. As lenders start to get more skeptical, in a macroeconomic environment with high interest rates and high energy prices, they start to run into a very real possibility that they hit illiquidity issues, even if their core business model actually works by then (and I don’t think it will). There’s just not enough runway for them, even in the most optimistic long term projections.

I want a convertible, a laptop that folds all the way back and gives a tablet/stylus interface, but has stiff enough hinges to hold the screen like a laptop at any angle with a keyboard, and that closes and covers the screen like a laptop. They played around with some form factors like that 10 years ago but they never really took off. Plus they tended to be Windows only, with poor Linux support on the hardware.

Whatever the reason, it’s basically become true.

Annualized Revenue rate is a made up number

It is fundamentally a projection about the future using recent results, and transparent in its methodology. It’s shit methodology, but it’s not hiding anything. So I don’t know that I’d classify it as fraud.

Playing games with “revenue” is another problem, but because that’s misleading about the past, and making an active decision on whether to classify money that was never gonna end up in their pockets as revenue share to partners or cost of revenue. Companies sometimes engage in shenanigans where they give discounts but classify the discounts as marketing/sales expenses rather than foregone revenue. That kind of stuff strikes me as more squarely in the category of accounting shenanigans.

Financial Times smells blood in the water. They’ve been reporting on leaked OpenAI documents for a bit the last few weeks.

If the major financial outlets start reporting on the negative, there may be a sentiment shift that does actually destroy the companies propped up by hype rather than fundamentals.

The number they used for annualized revenue for these rapidly growing companies is taking the most recent month’s revenue and multiplying it by 12. It’s not a guarantee about the future, but it is misleading.

The extreme version is taking a good week’s revenue and multiplying it by 52, or even worse, multiplying a day by 365. Those are outright dishonest. But not accounting fraud, because it’s not accounting at all.

The tablet one eventually came true. Desktops and laptops aren’t anywhere near as popular for personal use by non-technical people.

No paychecks mean no customers.

That’s never been a concern with the corporate executives. The macro level stuff is someone else’s problem.

We saw it in the 90’s when they stopped hiring managers from within, instead relying on bringing in outside consultants, and then directly hiring the ones they liked, so that there was no longer a path between the typical employee’s seat and their boss’s seat.

We saw it in the 2000’s when companies realized that they didn’t want to train entry level employees anymore, and would rather wait for someone else to train them, and then hire midlevels. Except too many employers did that and then the pipeline of future midlevels dried up in a lot of industries that were then ill positioned to survive the tumult of the 2008-2010 recession. Then something similar played out in the 2010s in certain other industries.

It’s always been buck passing. They don’t care.

He doesn’t even have that. He just pretends, by misleadingly saying he has a degree from Wharton. He does have a business degree from undergrad, from the University of Pennsylvania, whose business school is called Wharton, but most people say Wharton degree to refer to an MBA from that business school. He takes advantage of the confusion by referring back to his Wharton degree, and it sometimes works.