OpenAI released 722 mathematical manuscripts produced by an unreleased internal model, grouped into 372 families of results from about 4,000 research problems, averaging three hours of ChatGPT Pro compute per result. The author highlights claimed results including a zero-free half-plane for the zeta function and a quasi-Riemann hypothesis advance, which remain to be independently assessed.
Ok so I took a closer look at the results, and OpenAIs AI-generated mathematics manuscripts are *even more* significant than I initially thought.
I spent the morning going through it. Some thoughts.
The list is absurd. A zero-free half-plane for the zeta function (Re s > 7/8), which is the first result of its kind in over a century. Hilbert's tenth problem over the rationals. The Hodge conjecture for CM abelian varieties. Irrationality of Catalan's constant. Dozens more.
Any one of these would normally be a career.
But the number that many arent seeing is the following: It's 3. That's the average hours of ChatGPT Pro compute per result. A month ago, Navier–Stokes took them around 10,000 agents and 88 hours. That efficency gain within just a few weeks.
Also OpenAI claims to have solved the quasi-Riemann hypothesis. That alone would be a historic breakthrough in mathematics.
This is a weaker version of the famous Riemann hypothesis, which concerns how prime numbers are distributed. The full hypothesis remains unsolved, but the claimed advance would be enormous in its own right.
Math twitter obviously is shocked. Again: this is literally the intelligence explosion happening right now. 2027 will be the year of Superintelligence. Im now convinced by that.
OpenAI announced it is releasing a range of new mathematical results produced by an internal frontier model, consulting the Institute for Advanced Study's Advisory Group on Mathematics and Artificial Intelligence on how to release them, with materials published on GitHub.
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
Peter Yang highlights a developer who reimplemented seven Adobe apps, including Photoshop, Premiere and Lightroom, in Rust with Claude Opus 5.5 and open-sourced them. The developer believes they can match Adobe's features within months, against Adobe's $840 yearly all-apps plan.
It's insane to watch AI blow apart closed source software and games.
4 examples from the past month:
1. 7 of Adobe's biggest apps, including Photoshop, Premiere, and Lightroom, have been partially rebuilt in Rust with Opus 5.5 and open sourced. It's still early, but the developer thinks they can match Adobe's features within months. Adobe's all-apps plan costs $840/year.
Nikhil Pahwa congratulates Nous Research on a reported $90 million raise at a $1.5 billion valuation after its open-source Hermes agent was downloaded 22.7 million times, with about $36 million in annualized revenue by mid-September.
Molly O'Shea reports a $1.8 billion coalition including Biohub, the Department of Energy, NIH, Meta, Google DeepMind and Isomorphic Labs to build the largest open, AI-ready biological dataset to help models predict biology and treat disease.
BREAKING: The U.S. government, Google, Meta & Zuckerberg-backed @biohub are launching a $1.8B push to build the data layer for AI biology.
The goal is to create the largest open, AI-ready biological dataset ever assembled, giving models the data needed to better predict how biology works & ultimately help treat disease.
The coalition is massive:
› Biohub committed $500M › DOE is investing $500M+ across measurement, modeling & compute › NIH is bringing $500M+ of federally funded datasets & repositories › Meta, Google DeepMind & @IsomorphicLabs are jointly investing another $300M
This is effectively an infrastructure buildout for AI biology.
Instead of just building bigger models, they’re attacking one of the biggest bottlenecks in biology AI today, generating standardized, high-quality biological data at massive scale & making it openly available to researchers.
$1.8B committed to turning biology into something AI can increasingly model, predict & engineer.
Derek Thompson shares a quoted passage calling October 6, 2026 probably the biggest day of scientific advancement in history for AI in mathematics. The quoted Josh Gans post discusses OpenAI's Big Maths Day announcement.
"It isn’t an overstatement to say that this is probably the biggest day of scientific advancement in history. I suspect October 6th, 2026, will go down as some form of Judgment Day for AI in mathematics, but it portends so much more."
Tanay Jaipuria reports that Micron expects humanoid robots to require memory and storage comparable to Level 4 autonomous vehicles, including over 200GB of DRAM and terabytes of NAND. Micron's CEO believes physical AI could become a significant memory demand driver by decade's end.
Bret Taylor says Sierra built the Fleming-1 model to complement its Personal Agent Protocol by detecting when the caller on a phone call is an AI agent. The linked post describes it as Sierra's own model for that purpose.
To complement the Personal Agent Protocol, Sierra has developed the Fleming-1 model, which detects when the caller on the other side of a phone call is an AI sierra.ai/blog/caller-id-in-the-age-of-agents
A post reports that a user running ChatGPT Astra in a loop is repeatedly breaking records for integer multiplication algorithms. It quotes an update to OpenAI problem #109 that tightens the constant from 2^-182 to 2^-59, a roughly 500,000-fold improvement over the previous result.
Vijay Iyengar, who helped create Sierra's interview process, responds to points in a post by @jdpruettt on hiring experiments when candidates have capable agents. He says Sierra grades product judgment and system understanding via a two-hour prototype, scope decisions, production thinking, short-answer questions and a debugging interview with a semantic code search skill.
I helped create Sierra's interview process (sierra.ai/blog/the-ai-native-interview), so wanted to reply to some of the points here, which I largely agree with!
Models ship end-to-end demos trivially. What’s the point of testing for this?
We want to evaluate product judgment and system understanding. It’s hard to do this in English, better when you have a real product to look at. The prototype a candidate builds over 2 hours is more a rich visual aid for discussion than the artifact we’re grading. We also find a lot of signal in what scope candidates decide to keep or cut within the time box. The best candidates focus on what makes the product great instead of boilerplate that is trivial to add later. Finally, we spend a good portion of time on how they would take this system to production. We look for whether they really understand what makes the problem nuanced in a real-world setting vs the traditional FAANG style system design where you name-drop consistent hashing and Redis pub/sub to pass.
Short-answer questions
This is something we don’t do in general, outside of certain specialized roles, but I agree it’s valuable. You get a lot of signal about a candidate’s depth in a particular area by whether they can grok and answer questions quickly and concisely. Curious how well this works for generalists vs specialists.
Unassisted code review and tweaking
I really like this idea. We introduced a debugging interview where candidates are given an unfamiliar codebase and have to find/fix a bug in it. We do allow for AI assistance through a skill that doesn’t reveal the problems directly, but acts like a “semantic code search”. We find this to be a happy medium and reasonably representative of the real-world, where you’re just not going to interact with code without an AI anymore.
Doing things that don’t standardize
I very much agree with JD here. The main benefit of Leetcode interviews is that they’re easy to standardize. But imo, you shouldn’t be hiring engineers as quickly anymore, which means it’s worth sacrificing standardization for higher-signal. Of course you want to avoid bias, but I think it’s worth pushing on “what would we do if we didn’t have to standardize?” and questioning whether you really need to double or triple headcount. The three problems with graduated time constraints is a great approach.
a16z's Ryan McEntush argues that data centers agreeing to curtail power during peak hours can connect to congested grids sooner. He cites Texas's queue growing to 474 GW, about 90% of it data centers, and estimates 100 GW of flexible capacity could be added without new plants.
Left: Texas's grid only maxes out about 200 hours a year, roughly 2% of the time.
Right: New data centers that agree to cut back during peak hours can skip the wait for more capacity. US grids could add 100 GW of them without building a single new plant.
Why Texas Is Making Data Centers Wait — At the end of 2024, Texas’ grid operator had 63 GW of large new customers in its queue. By this June, that figure reached 474 GW, more than five times record peak demand, about 90% of it data centers.
Deedy highlights a claimed OpenAI mathematics release, conditional on verification, and argues that LLMs have made major progress on several Millennium Prize problems, concluding that AI has largely reached human-level cognitive ability.
OpenAI’s math release is, in the words of Opus, “the single most consequential mathematical release ever” *
LLMs have how made substantial progress on 4 of 7 Millenium Prize problems: Navier-Stokes (claimed), Riemann, Hodge and Birch-Swinnerton-Dyer. Poincaré was solved in 2003. The two left are P v NP and Yang Mills. *conditional on verification
On average, each OpenAI result used only 3hrs of thinking compute on their new unreleased models.
Two years ago, models said 9.11 > 9.9. Today, we have results that the smartest human minds have not been able to achieve in their entire lives. It is clear that data, compute and algorithms scale. Every model generation (3mos) has made substantial intelligence progress.
It also becomes incredibly hard to not believe that all knowledge work will change monumentally over time. The things AI can not do in the foreseeable future are very likely context-bound (don’t have access to the right information) than intelligence bound. Some might argue they are also creativity-bound or judgement-bound (what should I work on), although it can be argued that future generations could solve for this (given, say, the advancement in research taste for models over time).
AGI is defined as surpassing human capabilities on virtually all cognitive tasks. By most interpretations of that definition, we are there. The domains humans are still better than AI, such as, robotics / physical world control (data-bound?), natural science research (data-bound), some creative domains like writing, movies, music (creativity-bound), super long tasks (context-bound), choosing problems to solve (creativity-bound) and maybe human relationships management (meat-proxy bound?). In many ways, we have achieved AGI.
Olivia Moore shares an a16z map identifying search, creative tools and productivity as areas where early consumer AI winners are emerging, while social, marketplaces, travel, finance and other categories remain open.
James Zou announces the Evidence API from Paperclip, which lets users search over 100 million papers to find evidence for and against a scientific claim in about a second. He cites coffee and diabetes risk as an example query.
Vaibhav Sisinty reports the FDA cleared the first human age-reversal trial, citing animal research on partial reprogramming and Life Biosciences' $80 million raise to pursue it, though the post's claims about mouse and monkey results are not independently verified.
The FDA cleared the first human age-reversal trial
A Harvard professor proved you can reverse aging by 75% in 6 weeks in mice cured blindness, reversed Alzheimer's, MS, ALS, kidney and liver disease then confirmed it works in monkeys
Now humans are next. Life Biosciences raised $80M to make it happen
His words "The eye is just the beginning. We believe we can treat every tissue. A whole body reset"
The post argues the Navy turned to Anduril because only two U.S. yards build nuclear submarines and deliver far below the required rate, with China's shipbuilding capacity vastly larger. Anduril is investing $3.7 billion in a new Sparrows Point shipyard, Arsenal-2, with operations planned for 2030.
The US Navy just paid $2.9 billion to a company that has never built a submarine. Here's why they had no choice.
America has exactly two shipyards that can build nuclear subs. Electric Boat in Connecticut. Newport News in Virginia. The Navy needs two Virginia-class boats a year from them. They deliver 1.1.
Then it gets worse. Under AUKUS, America promised to sell Australia 3 to 5 Virginia-class submarines starting in the early 2030s. We signed a deal to export a product we can't build fast enough for our own fleet.
And the number behind all of it comes from the Navy's own intelligence office. China's shipbuilding capacity sits around 23 million tons a year. America's is about 100,000 tons. 230 times larger. One Chinese shipbuilder, CSSC, built more commercial tonnage in a single year than every American yard combined has built since World War II.
Both incumbent sub yards carry backlogs stretching past 2040, and the supplier base behind them shrank by thousands of companies after the Cold War. You cannot order your way out of that. There was physically no third option to call.
So the Navy invented one. Anduril adds $3.7 billion of its own money, breaks ground on the bones of Bethlehem Steel at Sparrows Point, once the largest steelworks on earth, shuttered in 2012, the yard complex that fed the fleet that won WWII. Hiring starts in 2029. Operations in 2030.
Four years from announcement to first output, and in American shipbuilding that counts as a sprint.
A tracker account relays Michael Burry's view that $573 billion in AI financing over the past year runs through eight companies that lend to, guarantee and buy from one another. Burry compares the setup to the 2000 telecom fiber bust and warns guarantees could be called if AI revenue disappoints.
Breaking: Michael Burry says the AI boom is running on one giant loop and time is running out
Here's his breakdown:
1. Burry shared a report from Wall Street lender Ares tracking $573B of AI financing from the last 12 months
2. All of it runs through just 8 companies: Meta, Oracle, Microsoft, Amazon, OpenAI, Anthropic, Broadcom and Nvidia
3. They lend to each other, guarantee each other's debt and buy from each other, so one company's loan is backed by another company's promise to keep spending
4. Every deal depends on one thing: AI spending never slowing down
5. If AI revenue disappoints for even one season, the guarantees could all get called at once, right when the companies backing them are at their weakest
6. Burry says it's the same circular financing that turned the 2000 telecom fiber boom into a bust
Burry claims the stock market in the first stage of grief and the crash is soon
Claire Vo shares a Grok-powered bot built by Zach Davis that smoke-tests web apps and posts up to five screenshot-backed findings about design flaws three times a week. Davis says DevinAI investigates most findings and opens pull requests for them.
omfg @zachdavis made the @bot of my dreams, which looks at our @cxodev website and nits all the little design bugs and weird issues that accidentally get shipped.
Cringe Bot is a team Grok Bot I created to find small problems with the stuff we build that makes our eyes twitch a little. It runs automatically 3x a week, does its own QA, and drops up to 5 findings per run with threaded screenshots.
It runs against our "marketing" website (cxo.dev), the custom app we built for our course, and a few other things. I take a quick look at the findings and have @DevinAI investigate and put up PRs for most of them.
Bill D'Alessandro says he received a draft 2025 tax return showing $117,360 owed, then asked ChatGPT Astra to review it against source documents. He reports the 90-minute review produced a report showing a $191,173 refund, which his accountant agreed was correct, and recommends pairing frontier LLMs with past tax returns.
I just got the draft of my 2025 tax return - it says I owe $117,360 of tax. On top of what I already paid.
Oof.
But it didn't feel right to me.
I asked ChatGPT Astra to do a secondary review, ticking and tying every number to source documents. Max effort. It ran for 90 minutes.
Output - a 15 page report. It says I'm actually due a $191,173 REFUND.
I reviewed Astra's work line by line with my accountant. He agreed, the LLM is correct.
I was about to send Uncle Sam $117,360. Instead, I'm getting back $191,173.
That's a swing of $308,533 (!!!!!!)
The LLM couldn't have done my tax return from scratch - I still need my accountant. But for massively complex detail oriented work, and LLM is the best thought partner you can have.
Connect a frontier LLM to your email and file storage, then ask it to review your past tax returns. You never know what it might find. My prompt is in the next tweet.
Amanda Orson compares Trammel Crow and Sam Zell's real estate strategies through the 1970s rising-rate environment, quoting Zell on accumulating assets with cheap fixed-rate debt during inflation.
"We realized that if we could accumulate assets – particularly in an inflationary time – with cheap fixed rate debt, it was hard not to make a fortune."
Most of us weren't alive during the last rising-interest-rate environment in the 70s but let's rewind through the lens of two different investors:
Trammel Crow and Sam Zell
Crow pioneered warehouse development and was doing both lots of projects and some BIG projects (Embarcadero in SF, Peachtree in Atlanta). He had a decentralized partnership model. By the end of 1974 (inflation peaked around 12%) his annual cashflow was -$25M and he had hundreds of partnerships and $400M in short-term debt, of which $151M was PGed. (🤢)
By 1972, Zell not only had stopped his own apartment acquisitions (th…
David Heinemeier Hansson describes a workflow for adversarial code review in which he asks Codex to review work from Claude and vice versa, using each model's command-line interface. He says the models can take turns and settle disagreements without special tooling.
Claire Vo says many mothers, including those in tech, are slow to adopt AI due to privacy, environmental and workplace concerns. She argues the market is missing agents that manage family logistics like calendars, bills and errands rather than one-off tasks.
As one of the most tagged AI mother of bots in this thread let me tell you a secret: a lot of moms (even moms in tech) are the slowest f-ing adopters of AI I know.
I’m in a bunch of random mom groups and I hear - I won’t connect my email cal whatever - water / data centers etc - get all AI out of my kids schools - here is my 10000 word prompt for chat - I hate AI in my job, burn out, get me out of tech
If you get off X and into the real world, the adoption curve is slow. My YT channel is over 90% men. Women + moms are being left behind, and it’s not because someone hasn’t designed the right agent yet.
Silicon Valley keeps building me a husband when what I really want is a wife lol
I don't want an agent that only does one-off, random tasks that are nice but not life-changing: booking flights, making dinner reservations, or buying tickets
I want an AI wife who knows what’s on the family calendar, remembers there’s a birthday party Saturday and we haven’t bought a gift then sends me options, realizes we’re almost out of diapers and buys them, knows which bills are coming up, remembers someone needs a dentist appointment and books it, figures out what the hell we’re eating all week and what w…
Noah Kagan says he made a free Wispr Flow alternative for Apple silicon Macs, offering unlimited use the first week then 2,000 words weekly, or $20 once for unlimited. He plans to share pricing experiment results in 30 days.
Bill D'Alessandro argues that GLP-1 weight-loss drugs are disrupting every category of consumer packaged goods, from snacks to supplements. He advises investors in consumer stocks to try the drugs themselves to understand the shift.
Prajwal Tomar promotes a gallery of motion graphics created with Claude Opus 5.5, each shown alongside the exact prompt that produced it, collected from posts on X and credited to their creators.
Adrià Martinez describes the Claude Startups program, which offers a year of Claude Team, API credits, priority rate limits and tool discounts, and gives step-by-step application tips such as using a company email.
It took me 5 minutes to get into the Claude Startups program
And you don't need VC funding anymore
What you get:
- A year of Claude Team - API credits - Priority rate limits - Deals on the tools a startup runs on
How to apply:
- Create a Claude Console account (the API one, not the app) - Use a company email, not Gmail - Go to claude.com/programs/startups - Fill in the form with what you're building on Claude
Dan McAteer argues OpenAI is downplaying its new mathematical results, noting reasoning models went from failing basic arithmetic to solving long-unsolved problems in two years, and predicts AI will revolutionize all of science.
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
Developer Levelsio reports that many hotels are owned by governments, including Shanghai's municipality via Jin Jiang International's 539 hotels, and says he added a government-owned filter to his hotel-ownership site.
TIL a crazy number of hotels is owned not by public stock holders, not by private owners, not even by private equity funds, but by governments!
You don't see this easily, because you have to dig quite deep (or well dig upward actually) and they cover it up in lots of constructions
Like this hotel in Paris "Le Ballu", sounds French? Yes and it's owned by Hotels & Preference, which on paper is a French international hotel chain
Hotels & Preference itself is owned by the Louvre Hotels Group, sounds French too? Yes
But Louvre Hotels Group is owned by Jin Jiang International, that doesn't sound so French anymore? So it must be a Chinese company? Right?
No! It's the municipality of Shanghai!?
Yes the the local council of Shanghai somehow owns 539 hotels around the world including Raddison, Park Plaza, Vienna House, Golden Tulip, Campanile, Kyriad etc.
Other big government owners are the government of Dubai, Brunei and Qatar
So I added a filter [ Government-owned hotels ] and every hotel page shows the TRUE owner of a hotel, not just the chain!
🔲 Public company ☑️ Privately owned 🔲 Government owned
I love ETFs as much as the next guy but they do put a pressure on stocks to grow by 10%/year or more
Hotels have a hard time doing that, so how do you grow? You cut costs and big hotel chains have been doing that in the name of DEI and ESG and wokeness a lot. Locking down ACs, no daily cleaning, cutting corners, etc. it all saves money
Those cost savings mean higer profit margins mean growth!
Great as an ETF or stock holder, terrible as a hotel guest
Commentator Matthew Berman praises Tesla's Full Self-Driving for his 83-year-old father's independence and says Powershare Home Backup, now available for new Model 3 and Model Y with Powerwall 3, can extend whole-home backup by over two days using a vehicle.
Tesla FSD already turns a car into autonomous transportation. It's one of the most impressive products I've ever used. My 83-year-old father told me he didn't think he'd be able to drive much longer. Then he got Tesla FSD and can maintain independence.
Now your Tesla can also back up your house.
The biggest drawback of battery backup vs. a gas generator has always been limited capacity. This largely solves it.
If your Powerwall runs out after two days, drive to a Supercharger, charge for 30 minutes, come home, and you've got roughly another two days of whole-home backup.
The official Grok Bot account announces that it can now search, read and monitor posts on X. The post is a short video announcement with no further details.
Olivia Moore lists the AI agents she uses, including Instinct for purchases, Muse for mini-apps, Tomo for goal tracking, Bot for X monitoring, OpenAI's Dots for long-running projects, Town for work email and docs, and Tab for outbound calls. She says she is using Dots to start a business.
- @instinct - on-the-go purchases, form fill, local recs - @Muse - mini-apps that require reliable connectors (ex. "track my sleep and movement, send me a survey daily") - @tomo - motivation + goal tracking, also want to try their Interest Groups - @bot - X feed monitoring + alerts - Dots (@OpenAI) - deep, long-running projects...I'm currently making it start a business 👀 - @townai - everything work-related in email, Slack, docs - @Tabdotbot - outbound phone calls / appts
Tibo announces a free, open-source AI skill that turns Nikita Bier's consumer app growth framework into a tool for analyzing an app and recommending fixes, metric checks and a yes/no test. The skill is linked at tmaker.io and promoted in an upcoming newsletter.
so we turned his whole consumer app playbook into a free, open-source AI skill for the rest of us
describe your app to your agent and it tells you:
- which rung of his ladder you're stuck on - which of your numbers you can't trust yet - what to fix first, then 2-3 big bets - one test with a yes/no threshold, set before you run it
Jurrien Timmer writes that strong earnings are offset by a tightening Fed and rising bond yields, with price meandering sideways for four months while market internals weaken. He shares analysis in a LinkedIn post linked from the tweet.
The markets continue to be pulled apart by opposing forces: a massive earnings boom on the one side and a rising cost of capital on the other. In the middle is the residual of the E and the P/E, price, which continues to meander for 4 months now while the market’s internals are bleeding, courtesy of a tightening Fed and rising bond yields. Let’s explore.
Ilya Sutskever posted that people who value intelligence above all other human qualities are going to have a bad time, a short reflective remark on AI and human values.
Replit CEO Amjad Masad argues that mathematics was bound to be cracked first by AI, reasoning that the purer a field is, the easier it is for AI to solve. The post is a short opinion accompanied by a photo.
Polymarket reports that AI startup BioinvestGPT correctly predicted five of six major drug trial outcomes before results were announced. The post offers no methodology or independent verification.
Bobby Kogan argues that Paul Ryan voted for tax cuts that worsened debt repeatedly across his career, and notes he retired at 55. He is responding to a post suggesting Ryan could return to politics in 2028.
Paul Ryan took debt so seriously that he voted for the tax cuts that did this at only 31 years old, and again at 33 years old, and again at 40 years old, and again at 42 years old, and again at 47 years old.
He retired before he could do it yet again at 55 years old.
FWIW, Paul Ryan is only 56 years old. In our age of absolute fiscal irresponsibility, what if the man who took tackling the debt seriously pulls a Winston Churchill and suddenly comes back onto the scene with serious momentum in 2028?
Mitchell Hashimoto argues that many highly successful people across industries are very smart, even when they present themselves as unserious, and reacts to a clip of Ben Affleck discussing his machine learning knowledge.
An uncomfortable truth for a lot of people is that a lot of the most successful people in any industry are wicked smart. We apply stereotypes based on the loudest people, but its not representative of norms. Most are crazy smart and got to where they are because of it.
I grew up in LA, one of my parents was a TV producer, my wife was an actor, many friends "in the industry." I've been constantly surrounded by it, and some of the stupidest seeming people (cause its their bit) are actually insanely smart and strategic in private. It sometimes is just beneficial for various reasons to... not show that side of you.
My favorite anecdote was when a friend (a model) was dating a phD in physics and a very rude person made some off the cuff degrading comment to model friend about it without realizing model friend has their own phD in math lol. You wouldn't know from their instagram though!
For the quoted video, I don't know Ben Affleck. I don't know how deep his knowledge goes. He's almost certainly not going to be more knowledgable than someone who professionally does this area of work full time, but he also to me on the surface sounds like someone who knows a LOT more than the average person and possibly even the average software engineer (on this topic).
Anyways, this applies to tech too. I see it constantly.
Ben Affleck reveals he writes Python, understands convolutional neural networks, worked extensively with GPUs, and used his celebrity status to get private looks at Google and OpenAI’s video models
“I’ve always been kind of into computers since I was young. Then, when film started to move from analog film to digital, I became more interested in that aspect of it. The visual-effects workflow for many years has included machine learning, so I can write pretty shitty Python scripts and stuff like that.
“With convolutional neural networks, which were the precursors to what the transformer can do…
In a video clip, Palmer Luckey says he would build a startup using oxytocin to strengthen marriages and end divorce. He argues the chemical is well understood and unregulated, and that it could help couples stay together.
Palmer Luckey reveals the startup he'd build today: oxytocin doping to end divorce
"I would try to end the tragedy of divorce with oxytocin doping for marriage counseling."
"We understand mammal pair bonding pretty well. There's a lot of people who want to stay together. Most of the people who don't want to stay together should stay together, especially for their kids."
"And we can, if people think SSRIs are fine, which they're not, but if they were, then oxytocin doping to stay together is definitely fine."
"It's the mammal pair bonding chemical. There's things you can do to increase the uptake, and it's very well understood. Also, totally unregulated, which is great. Unregulated spaces are a lot easier to do. You can go buy a kilogram of oxytocin on Sigma Aldrich Chemical Supply right now, and if you do that, maybe you won't die alone."
"It's pure biology. It's used for women who don't bond with their kids, and now for women who don't bond with their husbands. It's also used for kids with various neurological issues, some kids with autism who struggle with pair bonding."
"The cool thing is it's a self-reinforcing loop. We understand that very well. Unlike most drugs, it doesn't form a chemical dependency. It actually unburdens you from a chemical dependency."
Daniel Di Martino says a new rule charging $70,000 for OPT and $30,000 for STEP OPT rests on an unrealistic 44% demand drop assumption, and warns it will harm innovation and cost taxpayers.
It assumes demand drops by 44%, which is an arbitrary and incredibly optimistic scenario. There is no indication that universities will pay this, demand will drop 99%.
This is bad for innovation, and will cost taxpayers.
A post recounts that Instagram co-founder Mike Krieger came to the US on an F-1 visa, moved through OPT to an H-1B, and later self-deported amid delays. It argues that a proposed $100,000 H-1B fee would have prevented Instagram's creation.
Instagram co-founder Mike Krieger came to the US on an F-1 visa and then used OPT to get an H-1B. He later decided to self-deport and told Kevin to find a replacement because his H-1B transfer kept getting delayed.
If this administration was in 2010 they would've abused Mike for stealing an American's job, coming on F-1 and using OPT to get H-1B. If the $100k order was passed, Mike would've returned back to Brazil and we wouldn't have Instagram.
Shirish writes about the psychological toll of seeing a decade of learned expertise reduced to a prompt. The post is a brief reflection quoting Anthropic's announcement that Claude now works inside Google Docs, Sheets and Slides.
Claude now works inside Google Docs, Sheets, and Slides, and those files also open inside Claude.
In Google Workspace, Claude sits in a sidebar next to your file, reads what you have open, and edits it in place. You can approve each edit before it lands.
Investor Sam Lessin says he is reading hedge fund quarterly letters for the first time to understand how managers view the current moment. He notes that funds up about 30% in the quarter tend to discuss small businesses.
For the first time i can remember i am reading all the hedge fund quarterly letters because i am truly interested in how they are thinking about the moment... some are quite good. the ones up 30% on the quarter do like taking about small businesses.
Kim-Mai Cutler responds to a New York Times interview in which Zohran Mamdani said he changed his mind about the role of the private market in housing construction. Her post is a brief quip with no further argument.
Bret Taylor shares a celebration of Manat, who went from intern to engineer building voice products, after she demoed Tandem Voice and Persona Studio at a keynote, posing with her parents.
Manat started as an intern, and now she's an engineer building our voice products. She did an amazing demo of Tandem Voice and Persona Studio today. Here we are celebrating with her parents after the keynote.
Yishan replies to Palmer Luckey's oxytocin remarks with a brief joke titled as reinventing hugs from first principles. The post is lighthearted commentary with no substantive claims.
Palmer Luckey reveals the startup he'd build today: oxytocin doping to end divorce
"I would try to end the tragedy of divorce with oxytocin doping for marriage counseling."
"We understand mammal pair bonding pretty well. There's a lot of people who want to stay together. Most of the people who don't want to stay together should stay together, especially for their kids."
"And we can, if people think SSRIs are fine, which they're not, but if they were, then oxytocin doping to stay together is definitely fine."
"It's the mammal pair bonding chemical. There's things you can do to increase the …
Economist Noah Smith posts a brief one-line statement that the situation reflects unimaginable levels of corruption. The post provides no specifics about the subject.
Bren posts a brief tag of @OpenAI, quoting Ilya Sutskever's line that people who value intelligence above all other human qualities will have a bad time.
Mark Gadala-Maria posts that the Titty Killer series is one of the most promising developments in AI, quoting a post by Charlie Curran asking whether AI film can be art. The post offers no further detail.
