Manga / Sci-fi / Functional Programming & Deep Learning

Was not expecting this. 'Ghosts of Departed Proofs' is my all-time favorite typed FP paper. Highly recommend going through it if you haven't. If gdp-ts is as good as the tweet says, I'm moving most compile-time invariants to this.
Introducing gdp-ts: Ghosts of Departed Proofs for TypeScript. gdp-ts is a library, linter and AI skill for safer API design. Under this contract, sensitive functions require 'proofs' that the caller performed an authorization check. The typechecker verifies these proofs at compile time, preventing your team and agents from shipping catastrophic security (and other kinds of) bugs. While these patterns have existed for quite some time, especially in ecosystems like Haskell, ① human code review and ② cognitive and syntactic overhead made these solutions niche. The situation is now inverted. Agents are writing more code than we can review, and they *thrive* in tight loops with hard constraints that would frustrate us. We see this with the rise of Rust, borrow checker, code aesthetics debate and all. The README and examples model a real-world Vercel API product constraint: changing the password on a Project requires a proof of a certain role + a certain entitlement. Thanks to Matt Noonan and Ollie Charles for their research in this space. github.com/rauchg/gdp-ts
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Was not expecting this. 'Ghosts of Departed Proofs' is my all-time favorite typed FP paper. Highly recommend going through it if you haven't. If gdp-ts is as good as the tweet says, I'm instantly adopting it with Effect-v4.
Introducing gdp-ts: Ghosts of Departed Proofs for TypeScript. gdp-ts is a library, linter and AI skill for safer API design. Under this contract, sensitive functions require 'proofs' that the caller performed an authorization check. The typechecker verifies these proofs at compile time, preventing your team and agents from shipping catastrophic security (and other kinds of) bugs. While these patterns have existed for quite some time, especially in ecosystems like Haskell, ① human code review and ② cognitive and syntactic overhead made these solutions niche. The situation is now inverted. Agents are writing more code than we can review, and they *thrive* in tight loops with hard constraints that would frustrate us. We see this with the rise of Rust, borrow checker, code aesthetics debate and all. The README and examples model a real-world Vercel API product constraint: changing the password on a Project requires a proof of a certain role + a certain entitlement. Thanks to Matt Noonan and Ollie Charles for their research in this space. github.com/rauchg/gdp-ts
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Agents are can now write ~100% of most code. And yet, knowing the implementation details in-depth *is* important. Apps where devs don't care about code have a "smell". Your users can feel it. I've felt it myself while looking to switch text editors. [1/n]
"No one on my teams writes code anymore" is no longer a useful differentiator. The real question is: does anyone on your team _read_ code anymore?
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Everything I want is technically "available", but not within reach. And theres no common "language" between me and the editor. Ironically, the best editor I found—and then ditched for other reasons—was one where the author rejects all use of AI. It's called Gram. [3/n]
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There's likely a balance that the industry (I hope) will converge on, or the agents get better with long term memory. But until then, I strongly encourage being acutely aware of your code. As for editors: I'm currently using Zed, and still looking out. Nearly quit nvim.
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This is really simple and clever. Makes you wonder why culling didn't occur to competitive FPS/Mobas in all these years!
Few things ruin a great match faster than wondering whether an opponent earned the win or saw you through a wall. Wallhacks give cheaters information they were never meant to have. With Modern Warfare 4, we’re introducing a new way to fight back: Server Culling. Here’s how it works:
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you know what else Jev helps classify? people who actually understand ML, and people who don't.
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The "whiteboard defense:" I should be able to pull you aside at any moment and ask you to explain any customer-facing system you've shipped. You should be able to clearly explain how it works and defend the decisions you made. This is my benchmark for responsible AI usage. I don't expect line-level familiarity with the code. I don't care if you remember the exact function name or implementation detail. You may not even know it. I don't care. But if I ask "why did you do X instead of Y?", "what happens if this actor behaves maliciously?", "what data structure did you use here and why?", or "where does this fail?" you should be able to answer confidently. For PoCs, demos, experiments, whatever: I don't care. Generate 100% of it and understand none of it. Speed over quality every time in those specific scenarios. But if you're shipping customer-facing work, you can't be shipping things you don't understand at a high level.
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DeepSource has been acquired by Harness. Sanket and I started DeepSource on one bet: every line of code shipped should meet a high bar for quality and security, without a human having to review it. Over the last eight years, we built DeepSource from the ground up: static analysis across 20+ languages, Autofix in 2020, before automated remediation was a category, code formatting, coverage, SCA and security, and eventually AI-powered code review and remediation. The idea never changed much. Find problems before code ships, and fix as many of them automatically as we can. With agents producing code faster than humans can review it, there is a lot more of that problem to solve now. I’m proud that everyone from open-source maintainers to enterprises relied on DeepSource to ship better code. More than anything, I’m proud of the team that built it. Harness is building the Autonomous SDLC Platform to catch risks in software before it ships, and our vision aligns perfectly with theirs. I'm excited that DeepSource is joining forces with them and continuing our work. deepsource.com/blog/deepsour…
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injuly retweeted
DeepSource has been acquired by Harness. Sanket and I started DeepSource on one bet: every line of code shipped should meet a high bar for quality and security, without a human having to review it. Over the last eight years, we built DeepSource from the ground up: static analysis across 20+ languages, Autofix in 2020, before automated remediation was a category, code formatting, coverage, SCA and security, and eventually AI-powered code review and remediation. The idea never changed much. Find problems before code ships, and fix as many of them automatically as we can. With agents producing code faster than humans can review it, there is a lot more of that problem to solve now. I’m proud that everyone from open-source maintainers to enterprises relied on DeepSource to ship better code. More than anything, I’m proud of the team that built it. Harness is building the Autonomous SDLC Platform to catch risks in software before it ships, and our vision aligns perfectly with theirs. I'm excited that DeepSource is joining forces with them and continuing our work. deepsource.com/blog/deepsour…
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We're looking for a CFD/Scientific Compute Engineer @pre6ai Work involves high-performance physical process simulations, computational geometry, ML, and working on production software built for CAD/CAM. More details in reply. If you know someone, please reach out!
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I love Ed Zitron. He's like a comic book character. SHOCKING: "OpenAI will run out of cash in 20XX" – Ed Zitron, 20(XX-1).
🚨SHOCKING: "OpenAI will run out of cash in 2027, and then we enter a tech depression." Tech critic Ed Zitron just laid out the exact sequence of how it happens.
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Another fun fact: two randomly sampled vectors are almost certainly near orthogonal in high dimensional spaces. Meaning if you need properties that fall out of orthogonality for two independent vectors, higher d_model helps.
Local minima are extremely rare in high dimensional spaces, so if you ever feel stuck in a rut it’s probably just because you aren’t considering a wide enough set of orthogonal options
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IDK how I ran into @hey_kivi but it's a *fantanstic* product for STT. Beats wisprflow any day.
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"Let us go for a run" – said Mr. Walker.
Let us go for a run someday , I want to see your fitness level. Time and place you decide , distance I decide
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Every once in a while people will tell you spiderman 2 is only good because of nostalgia. And you will go rewatch to learn once again why they're wrong.
People talk about Spider-Man 2 on this app like it saved their life or something
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Superman! Please save my cat, he's stuck in that car over there.
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Sachin Tendulkar has finally spoken on the student protests, and I had to read his note twice: once as a fan and once as an editor. The fan was disappointed, but the editor realised that this was a textbook specimen of the kind of writing that George Orwell warned about in his essay “Politics and the English Language”. The essay was written in 1946, but it might well have been written yesterday about this very statement. Orwell’s point was that when people want to hide something, they stop using plain words and reach instead for the passive voice, for fog, for phrases that sound like they mean something while meaning nothing at all. Consider the line, where students are disappointed that “their hard work hasn’t been rewarded”. Rewarded by whom, and denied by whom? There was a paper leak, which means somebody leaked it, some institution failed to prevent it, and an official presides over that institution. Yet none of them appears in the statement, and neither does the leak itself. A crime with identifiable custodians has been turned into something that simply happened to lakhs of children through nobody's fault. Then comes the list of those who must set things right: parents, teachers, friends, relatives, schools and administrators. If you read that list again slowly, you will notice it covers everyone in India except the people the students are actually protesting against, which is to say the NTA, the education ministry and the government. When everyone is responsible, nobody is, and that is not an accident of drafting. It was engineered to deflect blame. There is also a quiet sentence buried in the middle. “A society which prioritises outcomes over effort will seek shortcuts over meritocracy” is a line about those who take shortcuts, meaning the cheat. So a note on protests around paper leaks ends up gently lecturing the leaked-upon about honesty. His father’s lovely lesson—that failure is okay but cheating is not—is again aimed squarely at individuals, while the scandal and protests right now are about institutions that failed them. The rest of the statement is what Orwell called ready-made strips of words, glued together. Full of dreams and energy, fuel to our success, safeguard their aspirations. Nobody can disagree with any of it, which is precisely the point, for this is prose engineered so that no one in power will find a single sentence to object to. What an actual position would have looked like is a single sentence in the active voice: The government must find and punish those who leaked the paper, and fix the system that allowed it. He wrote 160+ words to avoid writing that one. Here’s Orwell’s full essay for those interested: bioinfo.uib.es/~joemiro/RecE…
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