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Source channel @githubtrending · Post #15535 · Mar 3

#shell ESP-CSI uses Wi-Fi Channel State Information (CSI) on all ESP32 chips to sense breathing, chewing, walking, or other movements without contact or extra hardware. You get rich data like signal phase and amplitude for smart monitoring, activity detection, positioning, and AI apps, with easy OTA upgrades, BLE help, and examples for quick starts like radar or cloud uploads—saving costs while boosting your IoT projects' accuracy and reliability. https://github.com/espressif/esp-csi

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Machinelearning

@ai_machinelearning_big_data · Post #8615 · 09/23/2025, 05:34 PM

⚡️Новая модель LFM2-2.6B - лидер в классе до 3B параметров. Ключевые особенности: - лёгкая и быстрая, всего 2.6B параметров - построена на архитектуре v2 (short convs + group query attention) - обучена на 10 трлн токенов, поддерживает контекст до 32k LFM2-2.6B - компактная, но мощная моделька для широкого спектра задач. 🟠Blog post: https://liquid.ai/blog/introducing-lfm2-2-6b-redefining-efficiency-in-language-models 🟠HF: https://huggingface.co/LiquidAI/LFM2-2.6B 🟠Model Bundle on LEAP: https://leap.liquid.ai/models?model=lfm2-2.6b @ai_machinelearning_big_data #AI#LLM#LFM2#OpenSourceAI#Multilingual