Bought Bloomberg journal subscription just to read Matt Levine.

AI for quants
The most important modern meta-skill is statistical inference with computers. If you can cause a computer to look at a big pile of data and use it to make predictions, there are many things you can do with that skill. You can, for instance, advance humanity’s understanding of distant galaxies. In some ways that is the paradigmatic use case; people who hire machine learning researchers love to hire astrophysics PhDs.4 In other ways, it is not the paradigmatic use case, because it is extremely difficult to make money by advancing humanity’s understanding of distant galaxies. Neil deGrasse Tyson seems to do well, but otherwise it’s a pretty small market.

There are other, more lucrative use cases. If you can train a computer on a pile of data about soccer or hockey, and then use it to predict which young prospects will become good soccer or hockey players, that is a skill worth many, many millions of dollars, and so we talk from time to time around here about soccer and hockey astrophysicists. But even that is small potatoes compared to the big three, each of which is worth many hundreds of billions of dollars:
Training a computer to predict which advertisements to show to people online.
Training a computer to predict which stocks will go up.
Training a computer to predict the best next word in an essay, or the next pixel in a picture.

These are normally called “big tech,” “quant finance” and “AI labs,” respectively, though all of those labels are somewhat loose. Traditionally big tech and quant finance were lucrative and desirable employers of machine-learning researchers. But, uh, I don’t know if you’ve noticed, but now top researchers at AI labs are regularly in the news for getting nine-figure pay packages. I am sure that many of the astrophysicists who work at quantitative finance firms do it because they love the people that they work with and the problems that they work on; they love the excitement of the markets and the immediate results they can get from applying math to trading strategies. But probably a few of them are in it for the money, and now the money in AI is soooooooooooooooooo good. As I wrote last year (about DeepSeek, an AI lab that grew out of a quant hedge fund):
An important story in the development of modern finance was “if you are good at building computers that can process natural language, you can pivot to building computers that can pick which stocks will go up, and get much richer.” This is essentially the story of Renaissance Technologies, whose central innovation was to hire computational linguists, because there was not much money in building computers that could talk and lots of money in building computers that could pick stocks.
But that is an old story, and now everyone has a computer that can pick stocks, while there is infinity money in building a computer that can talk. So now the people who got good at building computers that can pick stocks are pivoting to processing natural language.

HNTRBRK
Hey good for them:
Hunterbrook Global has been valued at $100mn after a recent fundraising, as the novel US newsroom-cum-hedge fund revealed to investors that it planned to move into litigation. …
Hunterbrook’s fund generated a 31 per cent return in the second quarter of 2025 and a 16 per cent return year to date.
We have talked about Hunterbrook — the hedge fund that’s also a newspaper — a lot, and one thing that I have said is that, if you are in the business of finding problems at public companies, you should really try to monetize that every way you can. The classic approach is “find bad companies and sell their stocks short,” but there are other approaches that are (1) maybe better and (2) certainly additive. “Find bad companies, sell their stocks short, sue them for securities fraud and file a whistleblower complaint with the US Securities and Exchange Commission” is strictly better than only doing one thing. Hunterbrook is using every part of the bad companies; the Financial Times reports:
Hunterbrook also revealed to investors in a letter that it planned to further exploit its news gathering by launching a litigation business that would partner with law firms on cases enabled by the newsroom’s reporting.
Also, if your business model is “find bad companies and sell their stock short,” you will investigate a lot of companies (to see if they are bad), and some of them will turn out to be good. You could … buy them?
Hunterbrook initially envisaged that it would short stocks in instances where its newsroom exposed scandals, but this approach has been sidelined in an “irascible bull market”, according to the investor letter.
The letter also details how Hunterbrook is generating a sizeable portion of its returns by taking long positions in businesses its journalists have investigated and found to be sound.
They should publish those too. “BREAKING NEWS: We looked into this company to see if it’s a fraud, but actually they’re very nice and you should buy their stock.” There’s not enough good news these days; scandals are more newsworthy than “everything’s fine here.” Unless you are long the stock.

this is smart: one of the reasons polymarket bets are misspriced is because of time-interest cost of money, if they can offer Treasuries rates on both sides of the trades, they can basically reduce spreads by a lot

POLYMARKET IS DECIDING WHETHER TO INTRODUCE ITS OWN STABLECOIN OR ACCEPT A REVENUE SHARING DEAL WITH CIRCLE: COINDESK SOURCES

*POLYMARKET CONSIDERS STABLECOIN LAUNCH TO CAPTURE YIELD FROM USD RESERVES

*Polymarket is locking a lot of stablecoin value in their betting pools and so they want some kind of mechanism to get the yield: Source

https://x.com/0xracist/status/1947710249684897989
Real tweet btw

Dream career? Active short-selling like Hindenburg Research but instead of researching fraud we will be the Open-Sourced QA menace — imagine 50k people ordering anvils and returning them every single day while shorting Amazon. Imagine how many more of these practices are possible, no way a poor PM in Amazon will outwit 50k degens probing for weaknesses.

Jeff Bezos in shambles.

https://x.com/shl0ms/status/1948818514069860508

Make All the Characters Awesome   
Eliezer: So to generalize that, let’s talk about the principle of “Make All the Characters Awesome.” This was an explicit process as I was envisioning the story, where I thought, for each character, how can I make this character awesome?
Take Crabbe and Goyle, for instance. I had an explicit process of flipping through various ideas, like, “Okay. Can I have them be like the Secret Masterminds who are running Draco from behind the scenes? No, because then Draco's not awesome.” 
“Can they be Secret Masterminds running all of Slytherin from behind the scenes? No, because that doesn't really fit.”
“Could they be Those Two Bad Guys, as TVTropes named the trope? I think this trope is used in Pulp Fiction and maybe in Neverwhere, if I’m remembering the correct Neil Gaiman novel. Anyway, so I'm like, “How about if there's Those Two Bad Guys?” And I thought, “Eh, it doesn't quite fit. It's been done before. It's a little arbitrary. Why is this trope showing up here?” 
And then I thought, “No, no, see, Crabbe and Goyle saw plays with Those Two Bad Guys as kids, and that's who they think they're supposed to be!” And then I was like, “Alright, this is adequately awesome.” And then I could stop trying to figure out how to make those two characters awesome and move on to the next character.
 
Gretta: Let’s do one more.
 
Eliezer: Sure. How about Luna Lovegood?
A fundamental fact about Harry Potter and the Methods of Rationality is, it's not quite set in the world of canon, it's set in the world of fan fiction. And almost every fan fiction out there makes Luna Lovegood awesome. So this wasn’t just me making every character awesome, this was a required element. 
But HPMOR is set in Harry’s first year at Hogwarts, and Luna is younger than Harry, so she’s not even enrolled at Hogwarts yet.
So I put a lot of effort into figuring out any way that she could be onscreen at all and awesome.
I landed on having her write all the Quibbler headlines. Had we ever made it to the epilogue, she would've been onscreen and even more awesome.

https://www.lesswrong.com/posts/FY697dJJv9Fq3PaTd/hpmor-the-probably-untold-lore

• Memory Retention in Frozen Organisms: Encouragingly, there is evidence that information encoded in the brain can survive cryopreservation. A 2015 study demonstrated that nematode worms (C. elegans) retained learned behaviors after being vitrified and re-warmed. Worms trained to associate a smell with food still responded to that odor after recovery from cryopreservation, indicating that their neural memory traces were not erased by the process . This implies that synaptic changes underlying memory can endure vitrification in a simple animal model, supporting the idea that a human brain’s memories could likewise remain intact if its structure is well-preserved.
• Organ Vitrification and Revival: Outside the brain, progress in organ cryopreservation also bolsters cryonics plausibility. Researchers have vitrified whole organs and then successfully revived them with function, a key step toward “reversible” freezing. Notably, a rabbit kidney vitrified with cryoprotectant was later transplanted into a rabbit, restoring life-sustaining renal function for weeks . More recently (2023), scientists vitrified rat kidneys and used an innovative nanowarming technique – heating the organ rapidly and uniformly via nanoparticles in the tissue – to rewarm without crystallization or cracking, enabling successful transplantation. The reanimated kidneys functioned normally in rats after long-term cryogenic storage . This is the first repeated, peer-reviewed demonstration of a vital organ being cryopreserved and revived to full function, marking a major milestone on the road to reversible cryopreservation .
• Revival of Brain Tissue Samples: Just this year, a team in Germany revived preserved brain tissue, offering a proof-of-concept for restoring neural function after cryopreservation. They optimized a vitrification protocol for mouse hippocampal slices (brain tissue) using a cocktail of cryoprotectants and fast cooling to avoid ice. Critically, after rewarming, the brain slices not only appeared intact but also regained electrophysiological function: they showed normal electrical activity and even long-term potentiation (LTP), a memory-related neural process . This is the first time adult brain tissue has been cryopreserved and then shown to resume functional activity . While these were small slices (hundreds of microns thick) and not a whole brain, it demonstrates reversible cryopreservation on a tissue level – a remarkable technical advance.

Mood

Why do I even care about the long term?

if markets are efficient, who is shorting MOEX on a nuclear war threats?

just arrived. any guesses where?

https://recordcrash.substack.com/p/book-review-avant-garde-autopilot
AGARES review with some great Alexander Wales writers career overview!

I posted nothing about Barca trip because i’m having such a blast that I just have no time to post anything

so I wish yall that, be happy.

Days since the last emotional breakdown: 0.

I will bulldoze through every obstacly standing in my way to happiness.
I will only allow the world to be unfair as long as it is to my advantages.
I will not stop until I stand at the very peak of whatever mountain my gaze lands upon.
I will shape the universe to my will and tear up the stars if it needs to be done.
I will not stop until I am satisfied with what I achieved and reached my potential.
I will not be an NPC in my own story, rest be damned.

This is my mantra and I will repeat it until it becomes the Truth.
Behold.

https://youtu.be/Bm3YWNgpgP0
Someone in the comments said:
"He knows.
They know he knows.
He knows they know he knows.”
This is wrong tho, actual truth is more like:
"He knows.
They are 90% sure he knows.
He knows they’re not 100% sure he knows so he is banking on them hoping he doesn’t know (because what other choice do they have?)."

He makes sure to give them outs however ridiculous they are, he doesn’t want them to get to the 100%, that would make situation harder to control.