Repaying debt is cash cost. But this is convertible debt that could be converted to stock, in which case the holders of those newly converted shares don’t get paid cash from the company, but instead own a chunk of the company worth more than that cash. So the conversion itself would alleviate the cash demands of the company, while also diluting the ownership stakes of any preexisting owner. That’s what that paragraph means.

Companies issue convertible bonds usually because they can get better interest rates on it, in the event that they need to repay it. Or they’re happy to deal with diluting their shares if the company becomes so valuable, because that means they’ve gotten a lot richer and just have to share their newfound riches with the lender.

That’s the tradeoff, of course. If a company liquidates, it pays its debts first, then its preferred stockholders, then its common stockholders. But each step down the line gives a greater upside in exchange for less certainty in getting paid at all. Bondholders get paid at higher priority, but have the exact amount they get paid defined by a specific mathematical formula. So they won’t get any additional benefit from the company becoming super valuable. Or they can get in the back of the line to see what unlimited upside they have from the company’s value going up a lot.

Also, Anthropic’s bonds aren’t exactly low interest. They’re right there at the edge between junk bond and investment grade.

Usually companies will publish an “earnings before interest, taxes, depreciation, and amortization” or EBITDA as a way to show whether their core business is actually profitable (even if shareholders aren’t the ones to get the benefit of that business’s operating profit). But that’s not a standardized metric, and Generally Accepted Accounting Practices (GAAP) won’t define earnings in that way.

The big problem is that the more a company has to deal with high cost of borrowing and huge capital expenditures, the more disconnected EBITDA is from actual GAAP earnings. I can build a hotel for a billion dollars and rent out a bunch of rooms, while each room transaction brings in way more money than it costs for me to have a guy at the front desk give them a key and housekeeping to clean their room, I need to actually make a lot more in order to cover the cost of all the furniture I put in the room, the construction costs on the building, and the interest payments to the bank that financed the whole thing. And if the furniture and the building won’t actually last long enough to where I made all my money back before I have to reinvest a bunch of money into renovations and new furniture, then I don’t have a profitable business. Or if it can be profitable on those numbers but I can’t cover the interest payments to the bank, then the bank will eventually take it over and I’ll lose the business entirely, so owning stock in that company isn’t worth all that much.

So if they’re saying they’re barely profitable when you take out the very expensive costs of training new models, entering big expensive deals with data center companies to build out infrastructure, the stock they keep issuing to employees and partners, etc., that might keep things going a bit longer, but it’s still not actually a path to true GAAP profitability.

This right here is how all of this will come crashing down

No, this is pretty normal, and more importantly, doesn’t actually cost the company cash. They gave lenders bonds that can be converted to stock, so this loss on their books is pure paper loss, the same way wealth in owning stock in this money losing company is pure paper wealth.

These numbers are just illustration for simplicity, but imagine a company borrowing $20 billion and telling the lender that you’ll either pay back the $20 billion plus interest, or they can opt to convert it into stock worth 10% of the company. When the company is worth $100 billion, the bondholders won’t convert to stock. But if the value of the company shoots up on paper to where that same stock would be worth $100 billion, the lenders would rather take the stock than the cash repayment. And because it’s worth $80 billion more, the company will have to record that on the books as replacing $20 billion in bonds for $100 billion in stock, and an $80 billion loss compared to their last statement.

But look at the underlying financial cash flow. When that happens, the company actually takes $20 billion in debt off their books. They don’t have to repay that loan anymore. So it improves their cash flow position at exactly the same time that they’re booking a loss.

The whole thing will come crashing down for totally different reasons, relating to operational cash flow, not the actual accounting shenanigans where one kind of paper number gets converted to another kind of paper number.

“we lose money on every sale but we make it up in volume!”

Does it?

Reuters is reporting that Anthropic’s Investor Day event a few days ago, where they showed their audited Q3 financials to investors, caused institutional investors to shift their sentiment and that they are being pushed to lower their IPO valuation target down from $2 trillion to $1.5 trillion.

Coreweave is down almost 20% this week. Nebius is down more than 15%.

Investor sentiment is shakier than it was a month ago. And for hype-fueled valuations, investor sentiment is a two-way street.

plagiarism

outright theft

It frustrates me to see that people are suddenly protective of some kind of intellectual property right of people to control creations after they’ve been created.

I’m pretty skeptical of AI and have my doubts that it will be a net good, but I’m definitely not gonna suddenly be pro-copyright as part of that fight. Copyright has traditionally been used to entrench corporate interests, and strengthening those protections isn’t going to suddenly win a fight against some kind of AI dystopia.

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.

In the U.S., copyright protections don’t extend to functionality, though. So copying even copyrighted code in a manner to replicate functionality is fair use when there’s no other way to accomplish the same thing.

For example, if you have a piece of equipment that checks the software on a cartridge for a string of text that says “Produced by or under license from Sega Enterprises Ltd.” before running that software, then it’s fair use to copy that exact text so that your software can run on that equipment. And it’s fair use to reverse engineer and decompile licensed cartridges to see what the bare minimum necessary to make it work.

One way to prove that you didn’t copy the software any more than is strictly necessary for functionality is to fully document the functionality, and then have a skilled programmer take the documentation and write new software from scratch, without ever having seen the original software whose function is being copied. That’s a “cleanroom implementation.” Compaq and other IBM clones built their own BIOS software to implement the exact same functionality of copyrighted IBM code, and created an entire industry of IBM compatible PCs that weren’t actually licensed from IBM. Similarly, Google moved Android off of Sun-licensed Java using a cleanroom implementation (when Oracle bought Sun and Google wanted to get away from Larry Ellison’s abusive pricing practices).

Ok, so if it’s permissible to reverse engineer the code to create documentation of how it works, and then have someone else take that documentation and implement the functionality using new code, how do AI/LLMs fit into this? Can it be said that it’s truly a “cleanroom” when the reverse engineering and decompilation functions are done by the same software that converts the decompiled code into documentation in human language, and then is the same software that converts the documentation into newly implemented code? Doesn’t quite hit the same way, and I’m not sure the courts would see it the same way.

All of this is a gray area, and people shouldn’t confidently predict what the courts will decide in specific nuanced examples. A lot will depend on the specific details, so there isn’t going to be much room for sweeping generalizations.

It is believed that pi is “absolutely normal” in the strict mathematical definition: that in any base numbering system, any finite sequence of digits appears as frequently as any other sequence of that length. If that’s true, then yes, a particular binary string, including one that corresponds to a particular digital file (like a particular mp4 file), can be found in pi.

That said, it hasn’t actually been proven that pi is normal. If it’s not normal, then the number can be infinitely non-repeating and still never hit that particular sequence of digits.

Yeah, you’re probably right. Still, if big tech’s ad behavior (ads for stuff you’ve already bought, ads for things you’d never buy but might have looked up information about for non-consumer reasons) is any indication, I’m not actually sure they’re using really sophisticated techniques here that can’t be thrown off by one-off bored sessions.

When I’m bored, I get price quotes from Lyft and Uber to the airport. I’ll click around and look at the different tiers of service. Then I choose not to actually request a fare, and close the app.

I fly enough to where both apps probably have me as a regular airport customer, but that I’m price sensitive enough where I just won’t use their service sometimes.

I do the same with Doordash and other food apps, where I just put together potential orders to get a sense of how much something would cost if I ordered it, and then just never order it, letting that cart expire. I’m hoping this poisons their data or adds something to the price sensitivity metrics.

I also look at airfares, hotel prices, etc., a lot. It’s not for the purpose of manipulating their algorithms, as I just like to get a sense for how prices move over time. But if there’s a side effect that these variable pricing algorithms take into account people who window shop and walk away, maybe I’m helping push prices down.

If they’re gonna create a panopticon, we should fuck with their data.

I’m also waiting to see how Linux support for the A-series chips develops, now that the MacBook Neo has A18 Pros running MacOS. There are people working on tools to allow Asahi’s m1n1 bootloader to work on the Neos. Unclear how much of that effort will ultimately be upstreamed to Asahi itself, but I’m hopeful.

Most CPUs implement a strategy called “race-to-sleep,” where it throws all the resources it has at a computing task, to finish it as fast as possible, so that it can hurry back to a low power sleep mode.

For that reason, optimizing speed often improves battery life.