Deeply honored to have participated in the Institutional Adoption in Crypto panel in the UAE with @LTP_primebroker , @BitcoinSuisseAG , @dYdX , and @traders_guild during Token2049 - Dubai.

“I don’t do politics” well now you're doing 7.5% mortgage rates

JUST IN: Iran's president says "all our money in China has been frozen"

Martin Casado on why the labs missed Jev: they're building beings that speak, and software needed a model that chooses. "LLMs were text in, text out. They generate text, and they came from chat... We've spent the last few years trying to take this thing that spits out text and cram it into a traditional program... It's just been super janky." "Jev basically said, 'Generating text as output is very expensive, but it's also more complicated than you need... If you give us a set of options, we'll choose the best option. We can do that incredibly fast, incredibly cheaply, but also with much more accuracy because we can train just for this.'" "This has probably been the fastest adoption of an AI model since ChatGPT. It's been remarkable because we were all primed for this." "[The labs] are trying to create beings, and beings speak. If you're trying to create God, God speaks in natural languages. This is really about something that's for traditional software." @martin_casado

Foreigners hold dollars because that is what they need to access the great casino.

having a lock on supply when demand is this strong is more likely to increase pricing pressure, and could actually drive up valuation.

This is a very good and clear writeup on datacenter finance. Can someone explain to me in an EMH-compatible way why it’s worth $META paying *more* in interest just in order to nominally remain an “asset-light” business?

Democrats are going to win the House and maybe the Senate, but it’s not because of a popular "blue wave" emerging… Americans are not endorsing the Democratic Party, their policies, or the DSA. It will be a direct result of the Iran War. Low R morale and betrayal by Trump.

This is exactly what they will do. After that, America will become a one-party state.

I have encountered more cracked out schizos in one hour in SF than I have in the last year in Miami

CNN: John Cornyn says he has no plans to help Ken Paxton with fundraising, warning Republicans risk losing when they nominate “flawed candidates” Paxton has a 39% chance to win — an all-time low

The economics of a Neolab. A neolab is loosely defined as a startup of AI researchers who raises a lot of money pre-production to be able to finance GPU compute to take on a large AI problem. To buy 1000 GB300s or ~14 NVL72 racks will set you back $125-150M for 3yrs with 15-30% upfront. That’s about ~2-2.5MW. Thats about enough to do 10^25 flops a quarter and get to a GPT-4 level model which is 1-2 OOMs off frontier for pretraining. If you post-train on a great open source model, you have a better chance of getting to frontier. The risks are a) you need to spend millions on RL environments too and b) being lapped by another model release while being tied to a base model. For this to payback, you need to give your customers a better and ideally cheaper inference service than a base model and serve them for long enough to recoup your large investment. Even at 50% margin on inference, to recoup $10M in training means serving ~10T tokens (!) if you price like Fable / Astra given a standard cache read / input / output split ($2/M blended). And you have to justify being better than a release like Opus 5.5 which is even cheaper. Often, you end up charging your customers a huge premium in terms of platform fees and compute fees on top of pure inference. Meanwhile, every hour you’re not utilizing your GPUs you are burning money so you typically resell this compute back to a broker or run inference for open models / resell spot instances. At below a ~60% utilization on spot, you will still lose money. Add to that insane cost of talent. So what can you do with the compute? - Not play the model game at all. - Play an entirely different model game (Jev, World Labs) that if big labs played, would either a) cannibalize their business or b) be incrementally not significant revenue c) would cause too much distraction from the main main thing - Acquire a proprietary data set (Peridodic Labs) in enough volume in a domain of usefulness to eclipse frontier quality. Often happens in robotics, biology, chemistry. If you do overcome the challenge of building a model that is useful and well priced beyond big labs models, given the huge price of compute, you still need to play in an area where the revenue / compute ratio is signficant and market demand is large enough to payback your compute spend. It is a difficult game.

JUST IN: AOC officially backs Bernie Sanders’ bill banning AI superintelligence, with violators facing penalties similar to unlawfully developing nuclear weapons.

JUST IN: Trump rejects AI integration with China, says US leads "significantly"

🚨 Trump’s DOJ dropped a fraud-and-bribery case after the man offered $10 billion in U.S. investment.

DoorDash spent $1.4M trying to stop Zohran Mamdani from becoming mayor. This week's historic $131.5M enforcement action against DoorDash for underpaying NYC delivery workers shows why. Yet another reminder that the only thing that can beat organized money is organized people. theintercept.com/2026/09/23/…

If weed damages your short term memory, just imagine what weed can do.

A guy wanting to surveil everybody says he “values his privacy” Ironic.