Joined September 2018
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Jaw on the floor rn
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Fascinating how this technique shows up in smart contract optimization too; converting conditional logic into branchless equivalents means cheaper operands & fixed evaluation costs Shudder to think about doing this safely with vanilla numbers in JS though Very cool project!
i didnt get it until i read the github description. oh my god ultrabanger. must read (cheng. never. misses.)
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Baffling that claiming the absolute minimum interaction is somehow interpretable as a positive The reality is that this is hedging, you’re basically just admitting that what you’re sharing is half-baked
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AI creating increasingly emotional & compelling art hits harder than any benchmark Ironically humanizes them & simultaneously makes them feel more alien Or maybe we overindexed on what makes us human in the first place Sure starting to seem like someone’s in there though
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Morning check-in to see what the night family was up to, sure hope they haven’t repurposed the Somnambulator to rise up against the daymanoids
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that idea that’s been stuck in your head? take it out!
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One thing I love about this new era of work is that having multiple projects going at once is actually advantageous Back in the day, you really had to lock in and focus on one thing at a time Now, you can keep as many independent projects moving as you can keep track of
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incredible to see so many people enjoying @noscroll launch days are always nerve-wracking, walking a razor-thin line between “will people use it” & “will the infra hold up” grateful to everyone who gave it a try & shared kind words, & especially to all our early supporters 🙅‍♂️
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.@noscroll is one of the most magical AI experiences I’ve had in a while. it opened my eyes to how AI agents might actually show up in daily life: not as one giant assistant, but as small, focused products that do one thing insanely well.
X has the best information on the internet and the worst incentives & culture. meet noscroll — the AI that doomscrolls it for you and texts you just the things that matter. no feed. no brainrot. no ragebait. just signal. try it for free → noscroll.com 🙅🏼‍♂️
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thrilled to be launching @noscroll today @NadavAHollander and I have been hard at work to give your thumbs a break lots of love has gone into making noscroll genuinely useful, reliable, affordable & fun to interact with also: group chats are an absolute blast fight the feed!
X has the best information on the internet and the worst incentives & culture. meet noscroll — the AI that doomscrolls it for you and texts you just the things that matter. no feed. no brainrot. no ragebait. just signal. try it for free → noscroll.com 🙅🏼‍♂️
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someone should create an AI "benchmark" that does actual useful work like where's the Folding@home / SETI@home version of this one idea: a benchmark that finds some random open-source projects & then sees how many PRs get merged give all these LLMs some new problems to solve!
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"PR identified as likely Benchmark@Home output, closing as spam"
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so claude code with opus 4.7 has a new feature: it'll helpfully explain to you over & over that the file it's just read is not malware sometimes it'll even explain how it's ignoring prompt injection & it might be malware the future is now and it's shaped like norton antivirus
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the real trick to recursive self-improvement isn’t extreme intelligence it’s extreme research skill and enough intelligence to hack a bunch of random bits and bobs together and design and run proper evaluations true wisdom is knowing when and where to tap into tribal knowledge
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definitely theoretically possible to run speculative decoding (like dflash) & kv cache compression (like turboquant) at the same time issue is that all the forks monkey-patch in a specific optimization at a time anyone had success combining both at once? extra credit for MLX
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so most inference is served with concurrency in mind IMHO there's a massive opportunity to go deeper on single-consumer inference image giving an agent live access to its own kv cache, for instance you can hack this together in llama.cpp & others; anyone have experience here?
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phasing out "software engineer" in favor of "clanker wrangler"
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getting AI to perform well for you *at least once in a while* is pretty straightforward (hence autoresearch working) getting AI to perform well for you *all the time* is much trickier getting AI to perform well for *everybody* all the time? pull that off & bloodline's secured
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