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Source channel @githubtrending · Post #15225 · Oct 15

#mdx#bilateral_teleoperation#force_feedback#genesis#gravity_compensation#humanoid_robot#imitation_learning#machine_learning#moveit2#mujoco#open_source#openarm#python#reinforcement_learning#robot#robot_arm#robotics#ros2#teleoperation OpenArm is a special robot arm that helps with physical AI research. It has 7 degrees of freedom, which means it can move like a human arm. This makes it good for tasks that involve touching or moving things safely around people. The robot is open-source, meaning anyone can build, modify, and use it. This is helpful because it makes advanced robotics available to more people, like researchers and students, without costing too much. A complete system with two arms costs about $6,500, which is much cheaper than similar robots. https://github.com/enactic/openarm

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Посольство России в Индии

@RusEmbIndia_Ru · Post #14913 · 04/14/2026, 08:01 AM

Дорогие друзья! 📚 Русский дом в Нью-Дели приглашает вас принять участие в международной исторической акции «Диктант Победы». 📆 Ждем Вас 24 апреля в 12:00. 🔗 Язык диктанта - русский и английский. 🏢 Место проведения: Русский дом в Нью-Дели. 📍Адрес: 24, Фироз Шах Роуд, г. Нью-Дели. ✅ Вход для посетителей мероприятия - свободный. 🔗При себе необходимо обязательно иметь ID-карту (на бумажном носителе). 💎 Не упустите возможность стать частью важного события! Ждем Вас! #РусскийДом#Диктант#Индия Dear friends! 📚 The Russian House in New Delhi invites you to participate in the international historical campaign "Victory Dictation." 📆 We look forward to seeing you on April 24 at 12:00 p.m. 🔗 The language of the dictation is Russian and English. 🏢 Venue: Russian House in New Delhi. 📍Address: 24, Firoz Shah Road, New Delhi. ✅ Entrance for visitors to the dictation is free. 💎 Don't miss the opportunity to become part of an important event! We are waiting for you! #RussianHouse#Dictation#India

Libreware

@libreware · Post #1477 · 08/07/2025, 03:49 AM

WhisperTux Simple #voice#dictation application for #Linux. Uses whisper.cpp for offline speech-to-text transcription. No fancy GPUs are required although whisper.cpp is capable of using them if available. Once your speech is transcribed, it is sent to a ydotool daemon that will write the text into the focused application. Features Local speech-to-text processing via whisper.cpp (no cloud dependencies) No expensive hardware required (works well on a plain x86 laptop with AVX instructions) Global keyboard shortcuts for system-wide operation Automatic text injection into focused applications Configurable whisper models and shortcuts https://github.com/cjams/whispertux #assistant#speech#stt