nickysielicki

Common misconception, they are a public benefit corporation, which is a shorthand that means they do not serve for the benefit of their public shareholders but instead are ruled exclusively by their founders and Ben Bernanke. It’s tongue in cheek!

Shareholders in PBC have no sway. Look up drakes landing v. tilden park from earlier this year. A PBC was in financial trouble and two specific lenders proposed a solution: financing and debt conversion that would increase their combined ownership from roughly 25% to 85%, heavily diluting all other shareholders. An independent special committee of the PBC approved it.

Shareholders holding more than half the stock had requested a vote against this, but none occurred. They were told that the mission of the PBC came first.

It’s an absolutely crazy financial loophole. Basically, if you found your company under these PBC rules (which have only existed for like a decade), you can avoid any accountability to shareholders and do whatever the fuck you want. It’s a total subversion of property law. You can own a majority of the company and they can still unilaterally vote to dilute your holdings to zero.

When they go public, given their valuation, anyone invested in index funds will be buying. That’s your pension funds, your 401ks, etc.

When they’re unable to meet their… *checks notes*, $895,400,000,000.00 in commitments, what do you think will happen to the people that bought at IPO prices?

Their entire “PBC” governance structure was designed from the beginning so that they could entirely avoid accountability to shareholders. Their board answers to no one.

I suspect when the company eventually falls prey to the intractable economic forces they’re up against (Google, OAI, Deepseek, commercial real estate, power) and the company goes bankrupt and gets stripped for parts because all inputs are commodities and capital becomes the only limiting factor, we’ll see regulation that prevents this PBC scam from ever being pulled again on public markets.

It’s a good thing that companies have a fiduciary duty to their shareholders. It’s such a lesswrong/autistic trope to invent these kinds of complicated tricks to work around realities they don’t like, and when pension funds and everyday Americans start bagholding their junk debt and are forced to bail them out, they’re going to face unimaginable blowback.

Around the same timeframe, proprietary models dominated this same leaderboard. User preferences shifted.

Patently untrue, Anthropic and OpenAI models are both within the top 10. They’re just missing from the top 5.

Unless GCP/Azure/AWS/individual companies publish data themselves, this is the best available public data source we have.

That’s fair, but you also must concede that there isn’t any better source of data available.

> Additionally, open-weight or open-source AI models may capture a portion of the market for certain use cases, which could exert pricing pressure on our offerings or lead certain customers to adopt open-source alternatives for those use cases.

“A portion of the market for certain use cases” meanwhile the top 5 models by token consumption on the day this is posted are all Chinese/open weight models.

https://openrouter.ai/rankings#leaderboard-table

Docker images from Wordpress, joomla, and drupal were all exploitable.

https://www.wiz.io/blog/php2shell-php-rce

FTX Future Fund 2: Electric Boogaloo.

Is that because you were starting from scratch and working alone, though?

Imagine a hypothetical project at the scale of the Linux kernel, with thousands of mathematicians building up organized and well-commented code, standing on each others shoulders.

Suppose lean in its current state existed 15 years ago, and suppose the math community eagerly started contributing en masse to a shared repository of code. How much of the breakthroughs and longstanding questions in mathematics that we’ve seen answered this year do you think we would have solved?

In other words, how much of the developments this year are directly attributable to LLMs using lean, versus lean just being a significantly more productive language for some subset of mathematics compared to English and LaTeX?

Given how much we’ve seen formalized this year it feels hard to believe that this couldn’t have happened earlier.

Follow up question: do you think mathematicians would be as upset about the rapid changes in their field if they were the result of a collective shared effort on github, authored entirely by humans who all share the credit, versus that same outcome but authored by a large language model?

In other words, are the mathematicians upset about large language models, or are they really just upset that formalization and massive collaboration have turned out to be highly effective and has negated the heroic angle that mathematicians previously enjoyed, thinking in a locked room by themselves?

Food for thought.

A coworker recently remarked that lean seems like a new foundational language family that every programmer should be able to read, on par with C and Python, and I think it’s pretty hard to disagree with that. Next generations of models are going to be RL’d on Lean more and more because it pays dividends in winning the math war against their competitors, and this will benefit users of lean not only for mathematics but also as a general programming language and as a vehicle for other DSLs. For example, I think Sparkle (a Lean based HDL) or something like it makes a lot of sense in 2026 and beyond.

https://github.com/Verilean/sparkle

This is the kind of wisdom that caused the great financial crisis. Funds are limited in what they can invest in. Institutional investors don’t see high returns. They’re under a lot of pressure to maximize returns within the bounds of what they’re allowed to invest in. There’s a reason they’re risk restricted: they are responsible for a lot of money and society puts a lot of trust into them to not piss away their pension funds.

We learned this lesson the hard way twenty years ago. If we let them invest in dogshit, and the credit rating agencies allow them to, they will.

When institutional investors lose, they’re not really risking their own money. They’re risking yours, or at least your cousins or your neighbors.

NSA != NIST

They are throwing Claude at questions around cryptography.

So it’s pretty clear that Anthropic is privately trying to break cryptography.

It’s independently verifiable. What do you mean?

It’s perplexing that NIST chose to burn so much trust and goodwill with the independent cryptography community instead of just explaining empirically that they really had nothing up their sleeve.

The point of the headline isn’t to communicate that their debt is currently rated junk, it’s to communicate that it’s impossible for their rating to improve any further without becoming investment grade.

Most pensions and life insurers and so on are mandate constrained to investment grade only.

2008 wasn't fund managers deciding all together in unison to buy bad mortgages. It was AAA ratings on diversified MBS that should have been rated much lower giving them cover to load up.

I don’t like that they’re fleecing the corporate bond market after privatizing the majority of their upside. Yes, I wanted them to issue their junk bonds even earlier.

What I really want above all else is for credit rating agencies to not face pressure to rerate them favorably because they’re deemed too big to fail.

> Bankers for Anthropic and rival OpenAI have lobbied the largest rating agencies to grant the AI labs investment-grade ratings once they go public. Investors expect the initial public offering this year to hit a valuation of more than $2tn.

Let’s be clear about what this means: it gives them access to the corporate bond market. What they’re lobbying for is that pension funds, life insurance, etc., can take exposure to these companies. Suddenly the everyman, your mom and dad, have significant exposure to these companies and their circular financing deals without even knowing it. This is disgusting.

What a lot of people fail to realize is that the rules around IPOs changed since the dot com bubble. Previously, employees counted as shareholders and companies above a certain threshold of shareholders were required to IPO. This is why companies like Microsoft, Amazon, etc., had the majority of their growth while being publicly traded. This allowed the everyman with a brokerage account to participate in these gains.

These rules were essentially removed by Obama in 2012 through the JOBS act. What this means is that companies can stay private for a majority of their growth phase, which is why we’re seeing IPOs being floated with $2T dollar amounts on them. They’ve privatized the gains, and they only IPO once they want to cash out.

So let’s understand clearly what’s about to happen: early VC investors in oai/ant are going to make billions selling dogshit to your parents pension funds, your parents pension funds are run by idiots who will gleefully take the AI exposure and are legally allowed to take that AI exposure because the AI companies lobbied the credit rating agencies to allow it, and when the bills come next year and these companies are completely unable to meet their liabilities, your parents have to postpone their retirements or come back out of retirement to make ends meet.

It’s truly evil. I hope the employees at these companies with dollar signs in their eyes awaiting their multimillion dollar payoff understand the system that they’re participating in and how evil it is.

Point blank: 2008 was about manipulation of the credit rating agencies. This bubble will also be about manipulation of the credit rating agencies. Absolutely deplorable.

And no, just to nip this in the bud, AI isn’t a fad. It’s the most transformative technology of our lifetimes. It’s going to change everything. But that doesn’t have anything to do with chaos in financial markets or malinvestment during the gold rush. It has to do with whether these companies have any kind of moat and whether the billions being poured into current generation chips are going to depreciate over the timeframes that investors think they will.

If they’re not going to open source it, why are they telling us this?

You have a new internal VCS? Kudos! Why should I care? Do you offer it as a service? Can I pay you for it? Does this have any bearing on me whatsoever?

They might as well publicize a redesign of their office space.

My point is that if a proof is wrong or incompletely stated, we can just revise it and fix it. Commit by commit, build out a complete proof. This differs completely from the way that mathematicians have historically operated: check the work endlessly and privately email it to your friends until you’re sure it’s correct and then submit it to a journal.

It’s better to just publish something that you think is correct and if you find out it’s incorrect, try to fix it later.

My point is just that if a handful of these proofs are later revised or retracted, it’s really not a big deal.

I mean git commit by git commit. Which is how it looks when you use the right tool, eg: lean4

You’re right. But to quote Don Draper, “That’s what the money’s for!”

1. why can’t the so called “real mathematicians” (as if mathematics does not belong to all of us) write the lean theorems by hand and then we let the machine fill the rest in? They are very upset that they can no longer contribute to frontier mathematics. This would let them contribute.

2. Why shouldn’t math progress happen in the open, commit by commit? Why is it so horrible if a proof is 95% of the way there but we later find that it needs to be refined? Mathematics previously was optimizing for an antiquated publishing and distribution scheme. There is no need for the first print to be correct. We have the internet now. We can and should publish incomplete results and correct things on the fly. Maybe mathematicians would have solved some of these problems years ago if they didn’t hide incomplete almost solutions in their filing cabinet because it wasn’t yet ready to be published.

You don’t hate the pageantry of mathematics and academics enough.

The important take away here: the leapfrogging we’ve seen this year doesn’t seem to be a temporary thing. The famous theory of Dario Amodei was that AI was this winner-takes-all field where the first team to get a head start would never cede ground back. The term he liked to use was, “concentrating”. This is yet another datapoint that he was wrong about that. AI seems more distributed amongst neoclouds and traditional hyperscalers, FAANG and startups, GPUs and ASICs than it did this time a year ago.

Nobody has a moat.

When the history books are written and all is said and done, the hubris of this moment where all the American labs decided to punk their investors and join hand in hand in agreeing to let the Chinese win forever is going to be the main story.

This also explains why Gemini is lagging, they don’t have an nvidia training cluster.