⿻ patcon (is in Toronto) 🦋 @patcon.bsky.social
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⿻ patcon (is in Toronto) 🦋 @patcon.bsky.social
@patcon_
& this is the wonder that keeps the stars apart. #plurality @CivicTechTO @g0vtw fan @UsePolis contrbtr. past: biochmst @enviroDGI @HyphaCoop @nwspk @gc_talent




Why doesn’t anyone know what decimate means?


What's the deeper meaning of Open Source? I searched for it in 🇺🇸 Los Angeles, 🇩🇰 Denmark, 🇮🇳 India ... and 🇺🇦 Ukraine. I met legends like Mitchell Hashimoto, Poul-Henning Kamp, and Kailash Nadh. Along the way, I slept in an air-raid shelter, flew in a private jet, and ventured out into Bangalore traffic. The experience changed me forever. Join me to discover the GIFT COMMUNITY of Open Source for yourself.

Domestic horse meeting a Przewalski’s horse, the last truly wild horse species on Earth.








🚨 BREAKING : Did Trump just mock Japan in front of Japan's PM? Journalist : Why didn’t you inform allies before attacking Iran? Trump : We wanted surprise. Who knows better about surprise than Japan? Why didn’t you tell me about Pearl Harbor? 🤯

The paper I’ve been most obsessed with lately is finally out: nbcnews.com/tech/tech-news…! Check out this beautiful plot: it shows how much LLMs distort human writing when making edits, compared to how humans would revise the same content. We take a dataset of human-written essays from 2021, before the release of ChatGPT. We compare how people revise draft v1 -> v2 given expert feedback, with how an LLM revises the same v1 given the same feedback. This enables a counterfactual comparison: how much does the LLM alter the essay compared to what the human was originally intending to write? We find LLMs consistently induce massive distortions, even changing the actual meaning and conclusions argued for.


New Article - Prayer is Radar - link below
