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Source channel @githubtrending · Post #15314 · Dec 6

#python#brain_inspired_ai#deep_learning#large_language_models#reasoning The Hierarchical Reasoning Model (HRM) is a new type of AI that reasons more like a human brain, using a fast part for quick details and a slow part for big-picture planning. It solves hard logic tasks like Sudoku, mazes, and IQ-style puzzles very well, even though it is tiny (only 27 million parameters) and learns from very little data (just 1,000 examples). Unlike most large language models, it does not need long chains of written reasoning steps or huge amounts of training, which makes it much faster, cheaper, and more efficient. For the user, this means powerful reasoning in a small, fast system that can run on ordinary hardware and still beat much larger models on tough problems. https://github.com/sapientinc/HRM

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djangoproject

@djangoproject · Post #99 · 07/14/2016, 04:57 AM

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https://github.com/daleroberts/tv tv ("#textview") is a small tool to quickly view high-resolution multi-band imagery directly in your terminal. It was designed for working with (very large) #satellite imagery data over a low-bandwidth connection. For example, you can directly visualise a Himawari 8 (11K x 11K pixel) image of the Earth directly from its URL: It is built upon the wonderful #GDAL library so it is able to load a large variety of image formats (GeoTiff, PNG, Jpeg, NetCDF, ...) and subsample the image as it reads from disk so it can handle very large files quickly. It has the ability to read filenames (or URLs) from stdin and load files directly from URLs without writing locally to disk. Command line options are styled after gdal_translate such as: -b to specify the bands (and ordering) to use, -srcwin xoff yoff xsize ysize to view a subset of the image, -r to specify the subsampling algorithm (nearest, bilinear, cubic, cubicspline, lanczos, average, mode).

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