Hackathon 🤝 Music Industry. Introducing the Musicathon by @Musixmatch Pro 💻
Built with support from partners including Replit, @ElevenLabs, @SongstatsApp, @ai_lalal, and @Cyanite_ai.
📆 June 15–21
📍 Fully Remote
🌍 Global
🏆 $25k+ of prizes including $5000 cash
Ready to build? Sign up below ⬇️👇
https://t.musixmatch.com/musicathon
Ts & Cs ➡️
http://musixmatch.com/pro/api/musicathon/rules
Registration closes 12 June.

Just installed @garrytan gstack on Claude Code Desktop... works on the first try
No bash script, no npm command, just a natural language prompt you paste into Claude Code
It even instructs Claude to append a gstack section to your CLAUDE.md
Well thought out, going to start applying this to the skills I build

Possibly the thing we will most realize looking back: intelligence was so big that lots of companies were going to succeed. It's not so simply bucketed into chatgpt and claude code.
Logan Kilpatrick: It’s easy to forget just how quickly the size of the pie (AI Market) is expanding in nearly every category

this has to do with how we organize our team.
half the team builds primitives: sandboxes, memory, code execution subagents, security scanning, etc.
the other half owns evals + hillclimbing. they combine those primitives into agents, iterate, a/b test, and push the primitives teams to make them better.
centralizing the hillclimbing effort is important because distributed hillclimbing invariably leads to regression.
conway’s law!
arman: it's crazy how @greptile has had such a noticeable improvement in the last few months. i've never seen an agent at that scale improve drastically so fast

The road to Hell is paved with closed-source citadels disguised as good intentions.
The Pope is right: AI takes on the characteristics of those who build it, finance it, and regulate it. So the question is: who gets to hold the great and wonderful power of AI?
If the answer is a handful of closed source companies, murkily censored, quietly surveilling every step of our lives, every private conversation, enshrined in law as 'safe' and 'open' when they're nothing but the surveillance economy squared, then all we've done is build a few modern East India Companies, digital oligarchies of the few, cloaked in the language of safety.
Open Source and Open Weights are how you spread the fantastic enabling power of AI to everyone, everywhere.
Permissionless innovation.
Everyone gets the hammer and nails to build houses and churches and factories. The more hammers, the more widely spread, the more the decentralized genius of humankind can flourish.
Everyone gets the Printing Press.
The printing press singlehandedly uplifted and spread of intelligence and knowledge around the world. The more we could record all kinds of knowledge, the more we spread the ability to read, the more equal and advanced society became.
Before the press, knowledge was learned by one person and passed into dust with them when they died or passed only to only a small group of students.
When we only had monks in a cave copying religious texts, a closed system, it limited the spread of intelligence and limited the growth of civilization.
The printing press was the single greatest invention in the history of the world because it let anyone print anything and spread knowledge throughout the whole world.
AI can do the same, but only if we build the bazaar, and never let the citadel people convince the world that they're the special people who should control who gets access to intelligence while pretending they're building the bazaar.
What the world needs now is more intelligence, more widely spread and more widely available.
Open is the way.
And it always has been.
And the road to Hell was always built with walls, towers, spiked gates and moats so that only the few could enter.
Pope Leo XIV: In the abstract, technology in and of itself is not a solution to humanity’s problems, just as, in and of itself, it is not inherently evil. In practice, however, technology is never neutral, because it takes on the characteristics of those who devise it, finance it, regulate it

can't wait for this gbrain feature. here's the loop:
agent attempts a task using a skill
↓
gbrain eval or LLM-as-judge scores the result
↓
dream cycle runs the optimizer overnight
↓
proposes small edits to the SKILL.md
↓
if the new version scores higher, accept
↓
commit the improved skill, next run uses it
Garry Tan: These concepts coming soon to GBrain this week

The Telegraph: Macron tore up 65 years of doctrine to defend Europe with French nukes, with or without the US.
Poland, Germany, the Netherlands, Belgium, Greece, Sweden, Denmark, and now the Czech Republic will host French nuclear-armed Rafales. 1/

Musician and human rights activist Peter Gabriel sent a special congratulatory message to Brewster Kahle, founder and digital librarian of the Internet Archive, on being honored as a 2026 Computer History Museum Fellow at the April 25 gala ceremony.
In his message, Gabriel speaks to the importance of preserving and sharing knowledge, work that has defined Kahle’s vision for the Internet Archive.
Watch Gabriel’s message and more on our blog ⤵️
https://blog.archive.org/2026/05/20/brewster-kahle-receives-2026-computer-history-museum-fellow-award/
#BrewsterKahle #InternetArchive #ComputerHistoryMuseum #CHMFellows #DigitalPreservation #WaybackMachine #PeterGabriel @itspetergabriel @Brewster_Kahle

I read all 277 pages of SpaceX's IPO filing so you don't have to.
Losses up 700%. Revenue decelerating. 107x price-to-sales multiple.
It's a trainwreck. Full breakdown below 👇
Ed Elson: http://x.com/i/article/2059144312550760448

Politics isn't abstract. The same decisions that cost businesses billions shape what your family pays at the pharmacy, the grocery store, the gas pump.
Every generation feels the choices we make now. Sitting out an election isn't neutral. It's a choice someone else makes for your family.
Vote No on D.
Check out our first GL Studios production: 一定会

What most people missed in @garrytan 's gstack repo: it's a masterclass in storytelling.
The exact thing YC drills into its startups, sitting in plain sight in a README.
Let's unpack it, move by move. 👇

over the weekend i checked the obvious thing, which is whether mythos is able to solve the erdos unit distance problem, aka erdos problem #90. the answer is: yea

YC CEO Garry Tan: “Moat is not a noun. It’s a verb”
Popular belief says startups win because they have one big, game-changing insight.
But Varun Mohan (Windsurf CEO) argues that’s a myth.
“Every single insight we have is a depreciating insight.”
In other words: the value of your insight declines fast. Competitors catch up. Markets shift. What was once novel becomes table stakes.
He uses Nvidia as the example: Even at a trillion-dollar scale and 70% gross margins, they still have to innovate, or AMD catches up.
The real advantage?
Continuously generating new insights — and executing on them.
“It’s not about the insight you had one year ago. It’s whether you can compound that advantage over and over again.”
That’s why Varun tells his team: being wrong is fine, but being stagnant isn’t. You need to stay sharp, learn from the market, and compound your edge over time.
Or as Garry Tan (YC CEO) puts it aptly:
“Moat is not a noun. It’s a verb.”
Source: @ycombinator (May 2025)

OpenArt now lets you turn a single image into a persistent 3D world creators can direct with precise control.
Wide shots, top-down views, over-the-shoulder framing. All from the same environment, acting like a permanent virtual set.
Powered by the World Labs API. Learn more ↓

Introducing: Our users @superset_sh

new in-depth blog post time: Inside the Transformer: The Life of a Token
a deep dive into a modern dense transformer, i cover YaRN (why does pairwise coordinate rotation induce positional information?), hybrid attention (getting to 160k context length), soft capping, QK normalization, etc. as the token flows through the transformer
bonus transformer math: FLOPs/token formula (and when is 6N formula broken), cluster sizing (how big of a cluster do you need given the model/data size and experiment throughput of interest), and more

My wife (non-technical) built a fully functional iOS/Android app in 6 weeks... and it's made $1.5k on the app store since launch in the first month!
She's a stay at home mom with our 2 young children (3 and 1), and she wanted a way to write letters to our children to keep memories of their childhood (we kept using notes app and was all a mess).
Thank you @amasad and @Replit for making this possible!
Link if you want to try it: https://apps.apple.com/us/app/from-mama/id6760956480

🤳
Matt Shumer: Codex Mobile is making me a better developer in a way I didn’t expect: I step away from my laptop and stop micromanaging.
I give it much more ambitious prompts (the way models work best).
And I get space to think instead of sitting there with burning eyes spamming prompts.

Introducing Screendrop - a screenshot tool for everyone
Opensource
Host your own cloud with R2 + a tiny little hono worker
Native
Screenshot capture and editor
Video recorder, editor and compressor
This is one of the best apps I've built.

First correct benchmark I’ve seen in a while
Serena Ge (Datacurve): Today we’re releasing DeepSWE, a new standard for agentic coding benchmarks.
On public leaderboards, top models often look relatively close in capability. DeepSWE shows where they actually diverge, reflecting the realistic experience of developers in their day-to-day work.

works really well; ended up just turning this into a skill for all frontend work with a script/prompt inside the skill (works better for my flow vs a subagent)
Matt Shumer: Massively useful Codex trick for 10x better frontend:
You can ask Codex to use Claude as a sub-agent to have Claude handle frontend/design work.
Just say “Use claude -p with an excellent, well-scoped, but un-opinionated (UI/UX-wise) prompt anytime you need a design change).”

A post about Pope Leo XIV's encyclical on AI. Why the Pope is right, but perhaps not right enough.
Artificial intelligence is reshaping the world in front of our eyes: how we communicate, how we access information, how we work, how income and status are distributed among us, and soon how we fight and kill each other. Yet the public conversation about AI remains stuck on the minutiae of competition between labs, or on a false dichotomy between AI as a “stochastic parrot” with no real capabilities and AI as an alien superintelligence poised to take command of humanity.
The more important questions are about what we want from AI, and whether our current mindset, institutions, and control mechanisms are equal to the task of steering it toward our welfare.
It is refreshing, then, that a bold and powerful voice has weighed into this debate: Pope Leo XIV. As an economist who has long argued that technology is a matter of choice rather than fate, I find Leo’s intervention welcome and, on most points, on target. But on the most consequential question of what AI should actually be designed to do, Leo stops short.
Secular readers may bristle at the encyclical’s opening invocation of the Tower of Babel. They would be mistaken to stop reading there. Leo goes much further than most pundits, journalists and policymakers in the United States by recognizing that what happens to AI, and hence to humanity, is a under our control. There are multiple possible paths for AI, and which one we take will have sweeping consequences. He is also ahead of many commentators when he writes forcefully and unequivocally that “technology is never neutral, because it takes on the characteristics of those who devise, finance, regulate, and use it.”
These were the central themes of the book I wrote with Simon Johnson, Power and Progress: Our Thousand-Year Struggle over Technology and Prosperity. It is heartening to hear them taken up by a voice with Leo's reach.
The Pope is also right to question the current trajectory of AI in warfare and law enforcement. What was taboo only a few years ago – AI-driven mass surveillance, algorithms selecting targets for killing – has become routine. Many in Silicon Valley are now calling openly for a new military-algorithmic complex centered on AI as an instrument of American hard power. Leo captures something deep and too often ignored: “Any technology that facilitates attacks without seeing the face of human beings lowers the moral threshold of conflict.”
His call for the “disarmament of AI” follows directly from these observations. As he explains, disarming AI means “freeing it from the mentality of ‘armed’ competition, which today is not limited simply to the military context, but is also an economic and cognitive phenomenon.” His moral clarity in stating that “there is no algorithm that can make war morally acceptable” should be a warning to technologists rushing to design new weapons of mass destruction.
Underneath these specific concerns lies a more fundamental claim: that what is technically feasible is not the same as what is good for humanity, and that the difference depends on who controls the technology and what ideology and interests guide them.
Leo edges toward what I take to be the most important point about AI's future when he observes that “while AI promises to boost productivity by taking over mundane tasks, it frequently forces workers to adapt to the speed and demands of machines, rather than designing machines to work with those who work.”
But here he does not go far enough. He stops short of questioning the prevailing design philosophy of AI itself: a philosophy centered on mimicking human capabilities and automating human tasks, with the ultimate goal of artificial general intelligence (AGI) that can do everything a person can.
This philosophy rests on a mistake. It assumes that artificial intelligence and humanintelligence are fundamentally similar, and therefore machines should naturally take over whatever humans currently do. Yet these intelligences are fundamentally different.
Humans are “one-shot” learners. We form hypotheses from a few examples, mentally simulate possibilities, and refine our understanding through a social process of trial and error. This is how children learn language - imitating a few words, generalizing, and adjusting based on how others respond. We are not, however, very good at absorbing massive volumes of information or sifting through unstructured data for relevant patterns.
AI models are almost the opposite. They thrive on enormous training sets and excel at pattern recognition at scale. But they have, as yet, no genuine creativity, no real-world embodiment, and no capacity for trial-and-error learning grounded in interaction with the physical and social world.
When two things are different – you shouldn’t, and typically you couldn’t – use one to mimic the other. If you did, you would end up with suboptimal, disappointing results. It would have been a colossal mistake, and the Chicago Bulls’s legendary coach Phil Jackson would have gone down in the annals of basketball as one of the worst coaches in history, if he decided in the 1990s that because Michael Jordan was the better player, Jordan should mimic everything that Scottie Pippen and Dennis Rodman were doing in the team. The team went from championship to championship because these players worked together and complemented each other.
The same applies to AI and human skills.
The more productive path is complementarity – using AI to do what humans cannot, so that humans can do what they do best. An electrician aided by AI diagnostics, a nurse supported by AI in interpreting symptoms, a teacher using AI to personalize instruction for each student; these are the contours of a different AI future, one that raises rather than displaces human capability.
Optimists and industry insiders will respond that automation-first AI can still benefit everyone, provided redistributive policy keeps pace. But this argument has a poor track record. Forty years of digital automation have already concentrated gains at the top, hollowed out middle-skill work, and produced disappointing aggregate productivity growth. There is little reason to expect that an even more powerful round of automation, deployed by even more concentrated firms, will end differently. We can and must demand a different design.
The global stakes from the future of AI are even larger than those we can see around us in the United States. For the developing world, where billions still depend on the prospect of decent jobs as a path out of poverty, an automation-centric AI agenda is not merely suboptimal. It is simply transferring to foreclose the most important route to broad-based prosperity.
The biggest failing of today's AI industry is its refusal to recognize any of this. It is guided instead by an ideology of control (the industry’s own over humanity) and by a conviction that machines are uniformly better than humans.
As Leo rightly notes, this failure is enabled by the fact that a handful of companies now command the future of AI.
What we need is a combination of moral clarity and a serious, society-wide debate about what AI can do and what we want it to do. That debate must move beyond exhortation toward concrete choices: antitrust action against the dominant platforms, public investment in human-complementary AI, regulation of surveillance and autonomous weapons, and meaningful rights for workers and citizens over the data on which these systems are built.
The Pope's intervention makes such a debate a little more likely today than it was before.
It is now up to the rest of us to carry it further than he was willing to go.

NEW @thevosf ⁦👇🏼
Book review: ‘AMPLIFY! My Fight for Asian America’ by Dion Lim @DionLimTV
A look at the real stories behind the headlines of anti-Asian hate and violence
https://thevoicesf.org/book-review-amplify-my-fight-for-asian-america-by-dion-lim/