professional code monkey @aws

brooklyn
Joined April 2023
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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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one day you wrote console.log("here") for the last time and didn't even know it
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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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behold, an evolutionary LISP kernel which uses llms to self-modify/hot-reload running application without downtime once all properties pass. just insert tokens, dreams and ambitions.
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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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Trainspotting (1996), dir. Danny Boyle
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I'm still here. I use Vim on my full time job for programming in C++ and Go... And use it at home for developing PS1 and Dreamcast games. :')
We really don't see those vim/nvim/emacs aestheticists anymore, mfs disappeared like they never existed.
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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-…
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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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Insane UX to manage a fleet of warehouse bots
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You are CPython 3.15, a general-purpose Python interpreter trained on the entire standard library.
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