Peter Schuller retweeted
We’ve lost an icon. Margaret Hamilton, a computer science pioneer best known for her work at MIT leading development of the flight software for the Apollo missions to the moon, has died at 90. Read about her legacy via MIT News: news.mit.edu/2026/margaret-h…
Peter Schuller retweeted
I'm now the editor of @stripe's Engineering Blog! stripe.dev/blog/topic/engine… One goal is to keep it interesting and useful for devs who don't even use Stripe but want to see what we're achieving at a company that's AI forward but still has rigor.
Peter Schuller retweeted
I was offered money to scare you of AI. And I'm not the only one.
youtube.com/watch?v=lPdmYMHr…
Peter Schuller retweeted
Blackhat has uploaded the full presentation on the OpenAI Hugging Face incident, about which much ink has been spilled.
youtu.be/87DyyMV0kCY?si=wwYt…
Peter Schuller retweeted
Build a plugin once and use it across compatible agent clients.
Introducing Agent Plugins, an open standard developed with @awsdevelopers, @cursor_ai, @github, @code, and @vercel that packages Agent Skills and supports MCP server configurations in a shared format.
Peter Schuller retweeted
Replying to @AnthropicAI
Just for all the people who won’t actually read the post:
Peter Schuller retweeted
Ghostty is now indisputably the fastest terminal emulator at IO throughput, by a very large margin. On ASCII, Unicode, and CSI tests, Ghostty is more than 2x (double!) faster than any other leading "fast" terminal. These changes are directly in libghostty, too, so everyone wins.
`time cat 150MB_ascii.txt`:
- Ghostty nightly: 575ms
- Ghostty 1.3.2: 1.5sec
- Alacritty: 1.2sec
- Kitty: 1.7sec
- Warp: 3.8sec
- iTerm2, Terminal: stopped after 60s
`time cat 150MB_unicode.txt` (mixed languages):
- Ghostty nightly: 536ms
- Ghostty 1.3.2: 1.22sec
- Alacritty: 1.05s
- Kitty: 1.35s
- Warp: 3.4s
- iTerm2, Terminal: stopped after 60s
`DOOM-Fire-Zig` (an IO test):
- Ghostty nightly: 842fps
- Ghostty 1.3.2: 532fps
- Kitty: 485fps
- Alacritty: 593fps
- Warp: 577fps
- iTerm2, Terminal: 60fps (yes, 60)
To quickly address the "cat speed doesn't matter" naysayers: this is a direct test of how many bytes/second you can push through a terminal. It doesn't cover just "read big file" but also "how much can a TUI do". The tests above test various shapes of inputs (plain ascii, unicode/wide chars, csi-heavy loads, etc.). IO throughput is incredibly important.
Most of these improvements apply to libghostty-vt consumers too, so any libghostty-based terminals will instantly see huge throughput improvements by simply upgrading (ABI compatible).
I'll cover the exact improvements in a blog post in the future. These results are the result of 6 separate optimizations.
Peter Schuller retweeted
We’ve received notice that the Department of Commerce has lifted export controls on Claude Fable 5 and Mythos 5.
We'll begin restoring access tomorrow, and will share an update soon.
We’re grateful to our users for their patience, and to everyone who worked with us on redeploying the models.
Peter Schuller retweeted
Creator of Sqlite on pull requests: "You say, oh, it's free. No. It's not free. What you're doing is asking me ... to maintain it for you, to to document it for you, to test it for you, to maintain it for you for the next 25 years. That's not free." Yep.
Wise words from a wiser man than me. I've told people for the past decade and I have recent posts on here saying the same: the merge button is the easy part. Its the decade+ (Richard says 25 years) that follows where you've accepted the transfer of maintenance thats hard.
Peter Schuller retweeted
Honestly what a bunch of assholes @ABC
Peter Schuller retweeted
James Cameron's ‘TERMINATOR 2: JUDGEMENT DAY’ is returning to theaters on May 22 for the film's 35th anniversary.
Available in 4 formats — original 35mm & 70mm prints + 4K DCP & 3-D DCP digital restorations.
Peter Schuller retweeted
Claude Code 2.1.0 is officially out! claude update to get it
We shipped:
- Shift+enter for newlines, w/ zero setup
- Add hooks directly to agents & skills frontmatter
- Skills: forked context, hot reload, custom agent support, invoke with /
- Agents no longer stop when you deny a tool use
- Configure the model to respond in your language (eg. Japanese, Spanish)
- Wildcard support for tool permissions: eg. Bash(*-h*)
- /teleport your session to claude.ai/code
- Overall: 1096 commits
github.com/anthropics/claude…
If you haven't tried Claude Code yet: code.claude.com/docs/en/setu…
Lmk what you think!
Peter Schuller retweeted
I'm not joking and this isn't funny. We have been trying to build distributed agent orchestrators at Google since last year. There are various options, not everyone is aligned... I gave Claude Code a description of the problem, it generated what we built last year in an hour.
Peter Schuller retweeted
After years of dinners with FAANG friends, you experienced the progression of from being seen as nobody to a tier one AI company.
They always joked, “Are you still working on Full Self-Driving?” Then you sat there quietly eating your own food.
For many, top AI companies means hosting the biggest parties at CVPR, writing lots of papers, and have well known AI “god parents” in the org.
We have none of these. Quietly, we just want to solve singular most difficult problem on Earth.
This year they all have recognized Tesla is doing AI as good, if not better, as any other frontier companies, not because numbers of papers or podcasts being published, but a solid product that delivers the magic.
Peter Schuller retweeted
I took delivery of a beautiful new shiny HW4 Tesla Model X today, so I immediately took it out for an FSD test drive, a bit like I used to do almost daily for 5 years. Basically... I'm amazed - it drives really, really well, smooth, confident, noticeably better than what I'm used to on HW3 (my previous car) and eons ahead of the version I remember driving up highway 280 on my first day at Tesla ~9 years ago, where I had to intervene every time the road mildly curved or sloped. (note this is v13, my car hasn't been offered the latest v14 yet)
On the highway, I felt like a passenger in some super high tech Maglev train pod - the car is locked in the center of the lane while I'm looking out from Model X's higher vantage point and its panoramic front window, listening to the (incredible) sound system, or chatting with Grok. On city streets, the car casually handled a number of tricky scenarios that I remember losing sleep over just a few years ago. It negotiated incoming cars in tight lanes, it gracefully went around construction and temporarily in-lane stationary cars, it correctly timed tricky left turns with incoming traffic from both sides, it gracefully gave way to the car that went out of order in the 4-way stop sign, it found a way to squeeze into a bumper to bumper traffic to make its turn, it overtook the bus that was loading passengers but still stopped for the stop sign that was blocked by the bus, and at the end of the route it circled around a parking lot, found a spot and... parked. Basically a flawless drive.
For context, I'm used to going out for a brief test drive around the neighborhood to return with 20 clips of things that could be improved. It's new for me to do just that and exactly like I used to, but come back with nothing. Perfect drive, no notes. I expect there's still more work for the team in the long march of 9s, but it's just so cool to see that we're beyond finding issues on any individual ~1 hour drive around the neighborhood, you actually have to go to the fleet and mine them. Back then, I processed the incredible promise of vehicle autonomy at scale (in the fully scaleable, vision only, end-to-end Tesla way) only intellectually, but now it is possible to feel it intuitively too if you just go out for a drive. Wait, of course surround video stream at 60Hz processed by a fully dedicated "driving brain" neural net will work, and it will be so much better and safer than a human driver. Did anyone else think otherwise?
I also watched @aelluswamy 's new ICCV25 talk last week (xitter.gq/aelluswamy/status/1981…) that hints at some of the recent under the hood technical components driving this progress. Sensor streams (videos, maps, kinematics, audio, ...) over long contexts (e.g. ~30 seconds) go into a big neural net, steering/acceleration comes out, optionally with visualization auxiliary data. This is the dream of the complete Software 1.0 -> Software 2.0 re-write that scales fully with data streaming from millions of cars in the fleet and the compute capacity of your chip, not some engineer's clever new DoubleParkedCarHandler C++ abstraction with undefined test-time characteristics of memory and runtime. There's a lot more hints in the video on where things are going with the emerging "robotics+AI at scale stack". World reconstructors, world simulators "dreaming" dynamics, RL, all of these components general, foundational, neural net based, how the car is really just one kind of robot... are people getting this yet?
Huge congrats to the team - you're building magic objects of the future, you rock! And I love my car <3.
Peter Schuller retweeted
We are alarmed by reports that Germany is on the verge of a catastrophic about-face, reversing its longstanding and principled opposition to the EU’s Chat Control proposal which, if passed, could spell the end of the right to privacy in Europe.
signal.org/blog/pdfs/germany…
Peter Schuller retweeted
Thread: Tesla’s traction control is next level.
Not talking ESP / yaw control, although they do some interesting things I haven’t seen before, strictly talking wheel speed control
Here’s why Tesla is different (btw BMW claims to now be doing this with their new platform EVs 👌)





























