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Source channel @githubtrending · Post #14796 · Jun 6

#typescript#assistant#chatbot#knowledge_base#llm#markdown#nextjs#note_taking#notes_app#openai#rag#tauri#webdav NoteGen is a helpful tool for taking notes. It works on many devices like Mac, Windows, and Linux, and will soon work on iOS and Android. It uses AI to help you organize your recordings into readable notes. You can record audio, take screenshots, and add text or images to your notes. NoteGen also supports Markdown, which makes it easy to format your notes. It helps you save time by automatically organizing your recordings and allows you to use AI models like ChatGPT for assistance. This makes it easier to write and manage your notes efficiently. https://github.com/codexu/note-gen

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@tgchinanews · Post #585 · 08/27/2020, 04:54 AM

Raspberry Pi Zero 型态的 ZYNQ 7010 FPGA SoC SBC https://www.cnx-software.com/2020/08/25/zynqberryzero-brings-xilinx-zynq-7010-fpga-soc-to-raspberry-pi-zero-form-factor/ #这不消费电子#FPGA#RPi

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@githubtrending · Post #15271 · 11/05/2025, 12:30 PM

#cplusplus#arm#baidu#deep_learning#embedded#fpga#mali#mdl#mobile#mobile_deep_learning#neural_network Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance. https://github.com/PaddlePaddle/Paddle-Lite

GitHub Trends

@githubtrending · Post #15220 · 10/14/2025, 01:00 PM

#verilog#cocotb#embedded#fpga#iss#risc_v#rtl#verilator#verilog#vpn#vproc#wireguard This project creates an open-source, hardware-based WireGuard VPN using an affordable FPGA board, making fast and secure VPNs more accessible. Unlike slow software VPNs or costly proprietary hardware, this FPGA design runs WireGuard encryption and packet processing at near wire speed without needing a PC host. It uses common tools and languages (SystemVerilog, open-source FPGA tools) and includes a soft CPU for control tasks and hardware logic for data encryption and routing. This means you get a faster, more efficient, and customizable VPN solution that is open and affordable, ideal for learning, development, or deployment in cost-sensitive environments. https://github.com/chili-chips-ba/wireguard-fpga