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Affordable Wheel Based Refreshable Braille Display (Score: 150+ in 8 hours)

Link: https://readhacker.news/s/64dcJ
Comments: https://readhacker.news/c/64dcJ
Libraries struggle to afford e-books, seek new laws in fight with publishers (Score: 151+ in 9 hours)

Link: https://readhacker.news/s/64d7X
Comments: https://readhacker.news/c/64d7X
Hackintosh Is Almost Dead (🔥 Score: 153+ in 1 hour)

Link: https://readhacker.news/s/64erc
Comments: https://readhacker.news/c/64erc
How web bloat impacts users with slow devices (🔥 Score: 152+ in 2 hours)

Link: https://readhacker.news/s/64eHt
Comments: https://readhacker.news/c/64eHt
The return of the frame pointers (🔥 Score: 153+ in 3 hours)

Link: https://readhacker.news/s/64fAS
Comments: https://readhacker.news/c/64fAS
Show HN: Richard – A CNN written in C++ and Vulkan (no ML or math libs) (Score: 151+ in 1 day)

Link: https://readhacker.news/s/64auB
Comments: https://readhacker.news/c/64auB

This started out as a personal effort to learn more about machine learning. It's currently a CLI app where you give it a JSON file specifying your network architecture and hyperparameters and point it to your training data, then invoke it again in 'eval' mode with some data it's not seen before and it will try to classify each sample.
I don't see many other people using Vulkan for GPGPU, and there may be many good reasons for that, but I wanted to try something a bit different.
I've made every attempt to make the code very clean and readable and I've written up the math in documentation/math.pdf, so hopefully this is a useful learning resource for anyone interested in how neural nets work under the hood.
I'll be continuing to add new features over the coming months.
IBM 360 in UK need a home (Score: 150+ in 15 hours)

Link: https://readhacker.news/s/64eGk
Comments: https://readhacker.news/c/64eGk
How Microchips Work (Score: 153+ in 9 hours)

Link: https://readhacker.news/s/64fG6
Comments: https://readhacker.news/c/64fG6