the idea AI being state controlled - and by extension increasingly larger and larger parts of the economy - pretty evident AI will be implemented everywhere - is repulsive

much too easy to imagine

Like many Europeans, I woke up to news the US has ordered Anthropic to block any "foreign national" from its top models, so it pulled them for everyone. On the one hand, this is a wake up call of Greenland proportions for Europe. On the other, it is less dire than it looks. 🧵

Ironically, just days after Dario Amodei argued in his essay Policy on the AI Exponential that the U.S. government should have the legal authority to halt or roll back frontier AI models that fail safety evaluations, Anthropic became one of the first companies to find itself on the receiving end of exactly that kind of intervention. In a sense, the very switch he proposed was flipped on his own company almost immediately.

What can a neuron compute? Real biological neurons are complex, but how capable are they? Using a new method, we found that a single cortical neuron can classify cats vs dogs, recognize spoken words, and solve 10-bit parity, all tasks thought to require entire networks. (1/15)

We have automated 99% of the physical and intellectual labor that we did 250 years ago. No one hand copies documents anymore, no one does accounting by hand, no one reaps the wheat fields by hand. And yet, there is no unemployment as a result of this. I see no reason to believe that in the future, we will not automate 99% of the physical and intellectual labor we do now, but again, there is no reason to believe that that will result in any more unemployment than we have today. The limit to the number of jobs is not the amount of work we have to do. The limit to the amount of work we can get done is the number of minds and machines and hands we have available.

Narrative Violation Watch Software development jobs were in decline before ChatGPT 3.5 release?! Then they climbed after?! And they're growing at a faster rate than all jobs?! 🤯 I had to triple take this chart in the @semafor tech newsletter last week.

Fable seems more capable but it's interesting how the promise of an upcoming AGI leap is detached from reality. It's the same tech with the same fundamental quirks and limitations. The hype has been detrimental to the advancement of the field. It's time for proper engineering!

The most basic way AI could blow up imo. I'm not saying it does but this is the most obvious way I can see it happening - Per seat subscriptions are massively subsidized. The flat fee was priced way below what heavy usage actually costs - For real business use you have to move to the API anyway. Data protections, work integrations and compliance officer approval - On the API you pay metered rates, and businesses are burning credits way faster than the per seat pricing ever led them to expect - This is everywhere right now. Internally for us, Codex users, Uber torching its entire 2026 AI budget in 4 months, the Microsoft comments. Just go try an API I shared more on this here: x.com/Shaughnessy119/status/… - And I don't think most businesses have the money to keep paying increasing API rates without a real change to how they operate (caps needed) - Because they have a cheap alternative. They can reach open source models through any aggregator (OpenRouter, Venice, Baseten, Together) and still get strong privacy. Venice private data centers, or E2EE/TEE serving GLM 5.1. More on open source inference provider raises here: x.com/Shaughnessy119/status/… - And the discount is enormous. DeepSeek V4 codes within a hair of Opus on SWE bench at roughly 1/30th the price, and the cheapest open models run closer to 1/100th - Chinese labs open source frontier grade models. The model is the single biggest cost an inference provider has, and they get it for free - This idea dies if China goes closed source. That is actually bullish web2 AI labs, because if everyone is closed you pay up for the best intelligence. China goes closed source if they are tired of giving away an asset and they want the revenue and data flow to train new models - Is this showing up in web2 AI lab revenue yet? No. Revenue is off the charts. Anthropic went from 9B to 47B run rate in five months - So go forward, what happens? - I think revenue slowly starts leaking to the open source inference providers (see Venice usage, OpenRouter's $113M raise, Baseten is raising at $11B or triple its valuation in three months, on revenue that went from $200M to $600M annualized in a single quarter) - It doesnt move overnight, but it caps the labs ability to raise prices, and margins are already deeply negative. OpenAI is reportedly running near negative 122% - With margins that bad there is no cash flow, so the labs are fully dependent on outside capital to buy GPUs, train models, and keep subsidizing usage (I.e. see Google tapping $80b equity sale, granted 30b for employee RSU taxes. Clearly they think Equity is overvalued or you wouldn't sell it) - The break comes when that capital stops. Pricing is capped so margins cant improve, and the moment investors lose conviction on payback, the whole flow reverses - Why would they lose conviction on payback? Back to the start - the inability to improve margins or get businesses to pay more - This is also limiting, if we start making new drugs with AI or create entirely new businesses, you better believe people will pay up to the max for AI usage

Coding is basically the pinnacle of what you could reasonably automate with AI, and yet we still need human engineers to oversee agents for them to be effective. The AI models are trained on an incredible amount of sophisticated code. The users are highly technical and can use the latest tools quickly. The work is “verifiable” because you can test an app. The outcomes are often removed from the quality of the code (you can have sloppy code but the app can still work). And the context for the agent is often already digitized and sitting in the codebase. That’s an incredible amount of benefits that AI coding agents get to work with. Some of those apply to knowledge work, but most don’t in areas where the work needs to be fully reviewed to be useful, or where data isn’t as abundantly digitized. This makes the job for agents in knowledge work more complicated. So if with all of that, engineers still remain in very high demand, the risks are going to be less than what’s perceived for other areas of knowledge work. Agents will let people do far more than they did before, but the people don’t go away.

Sand watch in TouchDesigner //- Yunsu

Artificial intelligence (AI) as a field has been accelerating towards self-improving systems since the 1950s. Will get there someday.

It's amazing how far the banning lab meat coalition has made it given that they have no real arguments, and they usually don't even bother pretending to have any.

🦔GitHub Copilot switched to token-based billing this morning and users are already out of credits. Pro subscribers paying $39 a month are reporting 60% of their credits gone in two hours of normal use. One user lost 20% of their allowance from a single file review with no code changes. Another hit their monthly cap before the calendar even flipped to June. Orgs with shared token pools have no way to see individual usage, so entire teams get cut off when one person runs a heavy prompt. Users are canceling and moving to Claude Code and Codex. GitHub community forums are on fire. My Take Flat-rate AI subscriptions were always subsidized. Everyone in the industry knew it. Today the subsidy ran out for a few million developers at once. The problem is a lot of companies already restructured around these tools. They cut headcount and told remaining engineers to lean on Copilot instead of building skills internally. Those companies now depend on a tool whose cost just became unpredictable and whose usefulness completely changes when you have to ration prompts to stay under budget. The developers moving to Claude Code and Codex will hit the same wall eventually. Every AI provider faces the same unit economics. Anthropic filed its S-1 this morning, and the durability of its revenue depends on whether customers stick around once real pricing kicks in everywhere. If a $39 subscriber cancels after one day because the tool became unusable, multiply that across millions of seats and the churn risk becomes very real. Today showed what happens when AI pricing meets reality. The companies that built their workflows around cheap tokens just discovered the tokens aren't cheap anymore and the people who knew how to do the work without them are already gone. Hedgie🤗

🦔Anthropic just filed its draft S-1 with the SEC. Less than a week after raising $65 billion at a $965 billion valuation, the company is now on the path to going public. OpenAI has also filed confidentially. SpaceX already released its prospectus. Three of the most valuable private companies in the world are all headed for public markets at the same time. My Take For the first time, a major AI company has to open its books to auditors and the public. Every valuation and run rate headline over the past three years came from numbers that private companies chose to disclose on their own terms. The S-1 changes that. Anthropic will have to show real revenue broken out by customer, gross versus net after cloud reseller payments, actual margins, churn, and customer concentration. The enterprise side of AI spending has been a mess. One company ran up a $500 million Claude bill in a month because nobody turned on spending caps. Amazon built a leaderboard that drove employees to waste tokens on fake tasks. Uber blew its entire 2026 AI budget by April, and its COO said he can't tie the spend to useful output. All of that counts as Anthropic revenue right now. The S-1 will show how much of the $47 billion run rate is durable demand and how much comes from the kind of spend that enterprises are already pulling back on. If the audited numbers look meaningfully different from the headlines, it won't just reprice Anthropic. Every AI company leaning on similar run rate claims to justify trillion dollar valuations will face the same scrutiny. The S&P 500 just hit a record carried by 20 stocks, most of them in this space. This filing is the first real test of whether the numbers hold up. Hedgie🤗 anthropic.com/news/confident…

really a phenomenal piece. gulf capital is a key part of whatever global order emerges from compute & sits at the fulcrum of so many vulnerabilities we’ll have to exploit if we want any leverage in shaping what AI development looks like

Similar que con Petro hace 4 años, gane quien gane la 2da vuelta, por suerte no tendrá mucho poder en el Congreso

Pienso mucho en este tuit en días como hoy.

🚨 #ALERTA | Colombia definirá a su próximo presidente en un balotaje el 21 de junio, tras una primera vuelta marcada por la polarización. Con más del 92 % de las mesas escrutadas, el independiente Abelardo de la Espriella lidera con el 43,63 % de los votos, seguido por el oficialista Iván Cepeda con el 41,17 %.

Some people desperately want to believe we're a few good markdown files away from "getting" to fire 90% of people.