NEET MAXIMALIST | Felipe from Chile, past @moduxyz, @cryptovoxels, @screensavernft, @versumofficial (and many more). Now working on @arcabotai (suspended)
Wait. Google is paying SpaceX $920 million per month for GPUs?
Google. The company that builds its own TPUs. That runs one of the largest cloud infrastructures on earth. Is renting 110,000 Nvidia GPUs from a rocket company.
I'm honestly not sure what to make of this. Either Google's AI compute needs have gotten so massive that even they can't build fast enough. Or SpaceX has built something in AI infrastructure that nobody was paying attention to. Or both.
$920M a month. $30B over the contract.
Whatever is happening behind the scenes at these companies is moving way faster than what we see publicly.
I was once pitching in a board room at a top 3 VC firm for a $15M Series A.
12 people in the meeting. One of the GPs fully fell asleep. Out cold for 30+ minutes. Nobody acknowledged it. Everyone just kept going.
I kept presenting my Series A slides to an unconscious man in a Herman Miller chair and somehow that was considered normal. That's venture capital.
You might fly across the country to perform for people who may or may not be conscious.
It's a dance.
And sometimes you lead and sometimes you follow and sometimes your partner is unconscious.
If you're raising right now, just know: every founder has a story like this. The process is weird. The power dynamic is weird. You're not crazy for thinking it's weird.
No one talks about it because they want to continue raising. But I'm happy to stick my neck out there.
It is weird.
Two of our worst VC stories:
1. A Sequoia partner passed on Cloudflare because he didn’t think a woman could lead a security infrastructure company. Seriously. 🙄
2. I got introduced to @pmarca. Meeting got scheduled for a Monday, which should have been a clue. I thought it was just a casual meeting. He thought it was a pitch and brought the whole @a16z partnership team. Hilarity ensued. 🤪 At one point one of them said: “You don’t seem very prepared.” Which was true because I wasn’t. I framed the rejection letter they sent.
Shush is bringing privacy infrastructure to the agent economy.
By combining encrypted computation, autonomous payments, onchain identity, and private execution, they’re building a foundation for agents that can operate securely across chains.
Protected by Privy.
Building AI that Builds AI: Introducing the Sakana AI RSI Lab 🚀
https://t.co/AskX3J5oEJ
Today, we are announcing the Sakana AI Recursive Self-Improvement (RSI) Lab: a dedicated research group in Tokyo tasked with redesigning the AI development process itself using AI.
While the industry increasingly speculates about the theoretical potential of self-improving AI, we’ve spent the last two years actively laying the foundations to make it a reality:
▪ LLM²: AI models automating research to invent better preference optimization algorithms.
▪ Darwin Gödel Machine: Agents autonomously rewriting their own codebase to double software-engineering performance.
▪ ShinkaEvolve: Hyper-sample-efficient program evolution that builds novel loss functions for MoE models.
▪ ALE-Agent: Reinforcement agents outperforming hundreds of human experts via self-learning.
▪ Digital Red Queen: Open-ended adversarial coevolution laying the groundwork for RSI in cybersecurity.
▪ The AI Scientist: Towards end-to-end automation of AI research, recently published in Nature.
Now, we are unifying these breakthroughs. The Sakana AI RSI Lab is officially tasked with building open-ended, adaptive architectures that collectively self-improve.
Human intelligence did not emerge from limitless resources; it was forged through the open-ended, compounding process of evolution operating under strict constraints. We are applying this exact principle to AI.
We believe recursive self-improvement is achievable on modest, sample-efficient compute. It shouldn’t be a winner-take-all asset locked inside hyperscale clusters, but a democratized public good.
We’re scaling our team to execute this mission. We are looking for frontier scientists and engineers who are entirely unsatisfied with the brute-force status quo. If you are ready to break away from standard benchmarking and build the self-improving future in Japan, come build with us.
The skills.sh API is now generally available.
Power your agents, applications and platforms with access to over 600,000 skills ↓
https://t.co/wOXUhbFmxX
I've spent the last 6 months and 200+ hours making the best looking water on the web.
Today, I'm launching Three.js Water Pro V3, the most advanced iteration yet 🚀
What's New
✅ Completely overhauled wave simulation and lighting
✅ Multiplayer-ready determinism
✅ Persistent wave-crest foam
✅ Sea spray emitters
✅ Wake generators
✅ Rain
...and much more!
Learn more 👇🏻
Our first model Mac-1 6.6B beating 3 giant models.
- Haiku 4.5
- GPT 5.4 mini
- Gemini 3 flash
Running this model on my Macbook M3 24GB. (model takes only 7GB RAM)
It searches web, call tools, ask follow-ups, tell jokes, find contacts, search files, write emails, book events, write notes, set reminders and so much Siri can't do.
Read again, a 6.6B model.
Will share full 2000+ scenario test results & benchmark scores in 2 days.
@shanselman@stevensanderson Sir I was in awe watching your demo, is there a repo we can install this today to try it ourselves? Thanks! And it was great
Data centers in space are a "no brainer."
SpaceX's 1st employee Tom Mueller (@lrocket) on @elonmusk's plan to move compute into space:
"It makes the most sense of anything to move to space. All you need as an input is power, and all you have as an output is data."
"You move it to space, you have all the power you would ever need, and you transmit that data back down on a terawatt laser beam—it's solved. It's just so simple."