#swift#macos#macos_app#menu_bar#menubar#menubar_app#status_bar#statusbar#swift#swiftui#utility
Ice is a free, easy-to-use tool for macOS 14 and later that helps you hide and organize menu bar items to keep your screen clean and tidy. You can hide icons and reveal them by clicking, hovering, or scrolling, and it automatically hides them again to reduce clutter. It also lets you drag and drop items to arrange them, customize the menu bar’s look with colors and shapes, and use hotkeys to quickly show or hide sections. Ice launches at login and updates automatically, making your Mac’s menu bar simpler and more efficient without much setup time. This improves your workflow by reducing distractions and giving you quick access to the icons you need.
https://github.com/jordanbaird/Ice
#DL
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Zeus New Pytorch Ecosystem Tool
Zeus is an open source toolkit for measuring and optimizing power consumption of deep learning workloads.
🖥Github
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Main channel: @repo_science
Coupons: @freecoupons_reposcience
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#dl
Park, Chanwook, Sourav Saha, Jiachen Guo, Hantao Zhang, Xiaoyu Xie, Miguel A. Bessa, Dong Qian, et al. 2025. “Unifying Machine Learning and Interpolation Theory via Interpolating Neural Networks.” Nature Communications 16 (1): 1–12.
https://www.nature.com/articles/s41467-025-63790-8
#dl
A few cool ideas in this model.
Introducing Gemma 3n: The developer guide - Google Developers Blog
https://developers.googleblog.com/en/introducing-gemma-3n-developer-guide/
#dl
There is this new lib called scale. One could compile CUDA code to use it on AMD GPU.
https://docs.scale-lang.com/manual/how-to-use/
I don't know who is more pissed off, NVidia or AMD.
#dl
This repo is really nice.
yuanchenyang/smalldiffusion: Simple and readable code for training and sampling from diffusion models
https://github.com/yuanchenyang/smalldiffusion
#dl
Google & USC benchmarked a prompt based forecasting method, and the results are amazing.
Cao D, Jia F, Arik SO, Pfister T, Zheng Y, Ye W, et al. TEMPO: Prompt-based Generative Pre-trained Transformer for time series forecasting. arXiv [cs.LG]. 2023. Available: http://arxiv.org/abs/2310.04948