2026-01-09

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doisinkidney.com
doisinkidney.com / source link only
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Migrating our DOM to Zig
Karl Seguin / Lightpanda
We replaced LibDOM with a custom Zig implementation for better cohesion across events, Custom Elements, and ShadowDOM. Here's how we built it and what we learned along the way.
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www.makingsoftware.com
www.makingsoftware.com / source link only
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Binary and Scalar Embedding Quantization for Significantly Faster & Cheaper Retrieval
Aamir Shakir, Tom Aarsen, SeanLee / Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning
[Submitted on 23 Dec 2025 (v1), last revised 24 Dec 2025 (this version, v2)] / arXiv.org
Large-scale autoregressive models pretrained on next-token prediction and finetuned with reinforcement learning (RL) have achieved unprecedented success on many problem domains. During RL, these models explore by generating new outputs, one token at a time. However, sampling actions token-by-token can result in highly inefficient learning, particularly when rewards are sparse. Here, we show that it is possible to overcome this problem by acting and exploring within the internal representations o
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