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We've shipped an experimental uv-ty integration.
`uv check` will install ty, sync your dependencies, and type check your project, without any additional configuration.
astral.sh/blog/uv-ty-integra…
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A new paper from Apple engineers ends with a line we couldn’t have written better ourselves:
"if idle macOS devices across organizations [...] can be securely federated, they could form a massive, shared GPU resource pool that benefits the broader ecosystem."
That’s what we’re building with Darkbloom.
The paper's Minions is a system that pool idle Apple Silicon Macs into a distributed GPU cloud for on-prem inference. Queue times went from 10+ hours to minutes. Zero new GPU purchases. Zero infrastructure cost.
It runs inside Apple, on coworkers’ Macs, using the company’s own storage and access controls. When a team needs more capacity, they Slack colleagues and ask them to turn on the executor. Even in that setting, the top adoption concern was data confidentiality. People were wary of their jobs running on a colleague’s Mac. Apple’s fix was to keep each team’s work on its own team’s machines.
Which brings it back to that one word in the conclusion: “securely.”
Inside a company, you can shrink the network until you trust everyone in it. On an open network, the machine belongs to a stranger and there’s no one to Slack. Keeping prompts private and outputs honest on hardware you don’t control is the hard problem that we solved at Darkbloom.
Apple built the on-prem version.
Darkbloom is the open one.
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Plants don’t have eyes or brains. How do they know where light is coming from? Seedlings “see” with their whole bodies. quantamagazine.org/plants-fi…
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“The value of a prototype is in the education it gives you, not in the code itself.” — Alan Cooper
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Introducing Anatomy
Describe a machine in one line. Claude brings it to life.
- Interactive isometric wireframes you can rotate, inspect and explore
- WebGL shaders for fire, water, plasma and more
- Real 3D motion, with individual parts that rotate and move
Install it as an agent skill. Fully open source.
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Inference scaling works, but every agent eventually faces the same problem: its context window fills up.
In this essay, we argue the only scalable fix leads straight to swarms.
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Played around with an idea for a wildfire analysis tool
Visualizes wildfire progression over time, tracks hot spots with drones and monitors firefighting efforts
Made with Opus 5.5
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Left: MIT computer scientist Katie Bouman w/stacks of hard drives of black hole image data.
Right: MIT computer scientist Margaret Hamilton w/the code she wrote that helped put a man on the moon.
(image credit @floragraham)
#EHTblackhole #BlackHoleDay #BlackHole
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My hot take from chatting to @poteto is that we should use MORE abstractions in the AI age
You can use them (combined with harsh lint rules) to reduce the design space available to the agent and constrain them only to good decisions.
Combined with the fact that high-leverage abstractions let you do more with less code - so, more token efficient.
Plus, unwinding the damage from a bad abstraction is much cheaper with agents.
This runs counter to a lot of folks thinking that agents just want to read the raw code. They can, but they're not maximally efficient that way.
Be braver! Design abstractions.
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Should YOU do Programming Languages research in era of LLMs? Many would say NO. But I say YES!
PL Research is dead? Nay! the era of PL Exploration is just beginning.
Fuck the users. Fuck the applications. Let's do some fucking PL research!
kirancodes.me/posts/log-end-…
ALT PL research is dead, the age of PL exploration is just beginning! 02 Oct, 2026 programming_languages research perspectives There was a recent thread on the TYPES mailing list with researchers speculating about the future of our field given the disruptive effects of AI tools on programming in general. The opinions in the thread were a mix of thoughtful stances. Some were positive, but the majority opinion was overwhelmingly negative. It wouldn't be too far to say that some researchers feel that they are facing an existential crisis right now: I observe anecdotally that many people in academia are feeling worse about their work in Fall 2026 than a year ago …. Lower morale and motivation, higher stress and anxiety levels, and corresponding risks to mental health. The impact is comparable to what happened during COVID. I wanted to write this thread to present an alternative position. I think many junior researchers at the moment are watching this discussion right now, students re
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ive been leveraging ai to teach me topics in ways i like to learn
built a memory simulator: pick the hardware, OS (Linux, macOS, Windows) and apps, then watch what happens when you run out of RAM
here: an 11 GB game on a 16 GB machine pushing Photoshop and Slack's idle memory out to swap
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You are CPython 3.15, a general-purpose Python interpreter trained on the entire standard library.
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Cool eval. Simply ask an LLM “Land or Water?” and give it a latitude and longitude coordinate as text. Ask 16,200 times, plot as image. The models know. From compressing the internet.
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Ben Affleck (Hollywood star & Artists Equity CEO) talks about how he fine-tunes open video models by unfreezing weights and trained only the last cinematic layer so a film crew can hit real production standards.
for context, Ben Affleck founded InterPositive in 2022, a 16-person AI shop for film post and Netflix bought it in March 2026 for $587 mn in cash.
He needed that model because public video models were trained on his peers' films, and he did not think that was a real business. So InterPositive raised money, shot its own dataset for 8 months on a controlled stage, and used it only as late-stage training.
Each new film then trains a private model on its own dailies, so the production keeps the footage and the learning. That is the product Netflix paid $587 million for.
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From "Bloomberg Live" YouTube channel, (link in comment)
