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Source channel @githubtrending · Post #15037 · Aug 8

#other The FFmpeg School of Assembly Language teaches you how assembly code is written in FFmpeg, helping you understand what happens inside your computer. To join, you should know C programming (especially pointers) and basic high school math. The lessons include assignments and a Discord server for questions. By completing them, you can contribute to FFmpeg, a powerful video processing tool that uses assembly to speed up tasks dramatically—sometimes up to 94 times faster with special instructions like AVX-512. Learning this helps you write highly efficient code for video and multimedia processing, improving performance in real-world applications. https://github.com/FFmpeg/asm-lessons

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Machinelearning

@ai_machinelearning_big_data · Post #8680 · 10/02/2025, 05:01 PM

✔️IBM представила Granite 4.0 — новое семейство open-weights языковых моделей от 3B до 32B параметров. Четыре новые модели: - Granite 4.0 H Small - 32B/9B активных параметров - Granite 4.0 H Tiny - 7B/1B - Granite 4.0 H Micro - 3B/3B - Granite 4.0 Micro - 3B/3B Benchmarking (Artificial Analysis Index): - Granite 4.0 H Small: 23 балла (на 8 выше Granite 3.3 8B), обходит Gemma 3 27B (22), но уступает Mistral Small 3.2 (29) и Qwen3 30B A3B (37). - Granite 4.0 Micro: 16 баллов, выше Gemma 3 4B (15) и LFM 2 2.6B (12). ⚡ Token efficiency: - Granite 4.0 Small — 5.2M токенов - Granite 4.0 Micro — 6.7M токенов Обе модели заметно эффективнее Granite 3.3 8B и большинства non-reasoning моделей <40B. Детали: - Контекст: до 128K токенов - Лицензия: Apache 2.0 - Granite 4.0 H Small доступна на Replicate по $0.06 / $0.25 за 1M input/output токенов - Все модели доступны на Hugging Face - Модель Micro (3.4B) можно запускать полностью локально. 🔗 Hugging Face: https://huggingface.co/collections/unsloth/granite-40-68ddf64b4a8717dc22a9322d 🔗Unsloth: https://docs.unsloth.ai/new/ibm-granite-4.0 @ai_machinelearning_big_data #AI#IBM#Granite4#LLM#OpenWeights

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@githubtrending · Post #15348 · 12/20/2025, 12:00 PM

#go#gemma3#go#gpt_oss#granite4#llama#llama3#llm#on_device_ai#phi3#qwen3#qwen3vl#sdk#stable_diffusion#vlm NexaSDK runs AI models locally on CPUs, GPUs, and NPUs with a single command, supports GGUF/MLX/.nexa formats, and offers NPU-first Android and macOS support for fast, multimodal (text, image, audio) inference, plus an OpenAI‑compatible API for easy integration. This gives you low-latency, private on-device AI across laptops, phones, and embedded systems, reduces cloud costs and data exposure, and lets you deploy and test new models immediately on target hardware for faster development and better user experience. https://github.com/NexaAI/nexa-sdk