#shell#bash#developers_everyday_life#java#option_parser#python#script#shell#show_busy_java_threads#show_duplicate_java_classes#terminal#useful_scripts
This repository provides useful scripts for Java and Shell that make developer work easier and faster. The Java scripts help you quickly find CPU performance problems in running processes, detect duplicate classes in jar files, and search for specific classes across multiple jar files. The Shell scripts enhance command-line productivity with features like copying output to clipboard, colorizing file displays, deduplicating lines without sorting, and managing Docker containers more easily. The scripts are production-ready, used by major companies like Alibaba, and follow strict Bash standards for safety and reliability. You benefit by getting professional-grade tools that save time on routine tasks and learning best practices for writing quality shell scripts.
https://github.com/oldratlee/useful-scripts
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What’s Really Going On in Machine Learning? Some Minimal Models—Stephen Wolfram Writings
https://writings.stephenwolfram.com/2024/08/whats-really-going-on-in-machine-learning-some-minimal-models/
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Meta's second version of segment anything.
https://github.com/facebookresearch/segment-anything-2
They have a nice demo:
https://sam2.metademolab.com/
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I was searching for a tool to visualize computational graphs and ran into this preprint. The hierarchical visualization idea is quite nice.
https://arxiv.org/abs/2212.10774
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Like a dictionary
Kunc, Vladim’ir, and Jivr’i Kl’ema. 2024. “Three Decades of Activations: A Comprehensive Survey of 400 Activation Functions for Neural Networks.” arXiv [Cs.LG], February. http://arxiv.org/abs/2402.09092.
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I got interested in satellite data last year and played with it a bit. It's fantastic. The spatiotemporal nature of it brings up a lot of interesting questions.
Then I saw this paper today:
Rolf, Esther, Konstantin Klemmer, Caleb Robinson, and Hannah Kerner. 2024. “Mission Critical -- Satellite Data Is a Distinct Modality in Machine Learning.” arXiv [Cs.LG], February. http://arxiv.org/abs/2402.01444.
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Jelassi S, Brandfonbrener D, Kakade SM, Malach E. Repeat after me: Transformers are better than state space models at copying. arXiv [cs.LG]. 2024. Available: http://arxiv.org/abs/2402.01032
Not surprising at all when you have direct access to a long context. But hey, look at this title.