#javascript#distributed_companies#hacktoberfest#jobs_search#jobsearch#jobseeker#remote#remote_companies#remote_job#remote_work
This list shows hundreds of companies, mostly in tech, that let people work from home either part-time or full-time, with many offering jobs to people all over the world. The list includes big names like Microsoft, Amazon, and Shopify, as well as smaller companies, and covers many different types of work, from software and design to education and health. For anyone looking for a remote job, this is a helpful starting point because it saves time—instead of searching one by one, you can quickly see which companies are open to remote work and find links to their websites for more details or to apply. This makes it much easier to find a job that fits your skills and lets you work from anywhere.
https://github.com/remoteintech/remote-jobs
#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