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Clemente Henriquez PRO

ClementeH
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https://clemente-h.github.io

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upvoted an article about 6 hours ago
tokenizers v1: encode, decode and scaling, measured
upvoted a paper about 7 hours ago
CodeMidas: Scaling Agentic Coding RL Environments from Code Itself
reacted to SeaWolf-AI's post with 🔥 7 days ago
Instead of making the fly brain play games, we measured what it is for Since the Drosophila connectome was released, people have had the fly brain doomscroll a feed, play Beat Saber, drive in GTA. Those demos show that the brain runs. We wanted to show what it is for. So we gave it a looming object — one of the few things a fly brain is unambiguously built to detect — then deleted a single cell type and repeated the identical stimulus. Remove LC4, 126 cells out of 173,023, and the escape signal falls from 0.840 to 0.091. Eighty-nine percent of the danger signal is gone while the other 172,897 neurons run exactly as before. Deleting neurons does not do this on its own, which is the whole point of the controls. LC11 is the same class and larger than LC4 — 143 cells and 9,940 outgoing connections against 126 and 7,846 — and removing every one of them changes the signal by 0.000000, to six decimal places. It has to be those 126. No server and no GPU: a looming stimulus drives fewer than one percent of neurons above threshold, so the whole thing is 40 KB gzipped and runs in your browser. Try deleting one yourself → https://huggingface.co/spaces/VIDraft/fruitfly-brain The wiring is the measured connectome, but synaptic strength is a uniform count-based value and the dynamics are a firing-rate model of our choosing — a total-effect measurement of a model, not a recording from a fly. Male CNS connectome, FlyEM / HHMI Janelia with Google Research, Columbia and Harvard (2026), CC BY.
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