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Various links I find interesting. Mostly hardcore tech :) // by @oleksandr_now. See @notatky for the personal stuff
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https://github.com/alex193a/Root-My-Pixel local root on Google Pixel phones incl pixel10, incl fairly recent kernel versions. ppl say that includes latest but i don't have a pixel so did not check
πŸ‘Ύ2
great writing, clear & thoughtful
tldr: computers used to be math, and now they're about physics & natural sciences!
https://thomasdullien.github.io/about/slides/An-age-of-experimentation-BlueHat-Asia-2026.pdf
um, ahem, AlphaZero for text.
Training language models without language.
Loosely, natural data mixes contingent information (facts about our world) with universal predictive structure (composition, repetition, recursion, etc…) that are not specific to our world. Our self-play approach only supplies the latter. However, if it produces universal structure efficiently, and if universal structure is the bottleneck, predictable scaling on natural data follows.

https://arxiv.org/abs/2609.30063
https://github.com/acowsik/self_play_pretraining
i started doing exactly this (models editing its own context) as a natural extension of samplers in Nov'25 but couldn't afford going all in full time.
usually i am excited when somebody does what i didn't finish but not today πŸ’” there is still stuff they didn't went into like multipass/viterbi-like sampling still, still

this is kinda similar in terms of empowering the models to giving them access to edit their own harness but more powerful

https://fixupx.com/arankomatsuzaki/status/2105181276714242518?s=46
πŸ‘2