Foundation models are AI systems trained on vast amounts of data — often trillions of individual data points — and they are capable of learning new ways of modeling information and performing a range ...
Abstract: Long left ignored by the digital computing industry since its heyday in 1940’s, analog computing is today making a comeback as Moore’s Law slows down. Analog CMOS has power efficiency ...
Comprehensive Training Pipelines: Full support for Diffusion Language Models (DLMs) and Autoregressive LMs, from pre-training and SFT to RL, on both dense and MoE architectures. We strongly recommend ...
Form 13Fs offer a concise snapshot of which stocks Wall Street's smartest money managers bought and sold in the most recent quarter. Billionaires have shied away from buying quantum computing ...
In typical light-based computing, models parse tensors by firing laser arrays multiple times. They function like a machine that scans a barcode on a package to determine its contents, except that in ...
Abstract: Macro models of liquid crystal cells that prioritize input-output responses over physical accuracy are high-speed and valuable for large-scale circuit simulations. However, the simplicity of ...
The model that recently went viral is improved with Gemini 3 Pro. The model that recently went viral is improved with Gemini 3 Pro. is a deputy editor and Verge co-founder with a passion for ...
This is the official repository for our WACV 2025 paper, "A Multi-task Supervised Compression Model for Split Computing". Split computing (/= split learning) is a promising approach to deep learning ...
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