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@testflightynoti · Post #38175 · 05/12/2026, 07:04 PM
#VoicePad#AI#Dictation Join the VoicePad AI Dictation beta on ✈️#TestFlight 🔗 Link: https://testflight.apple.com/join/bbmnyyS4 Shared by Dimitri
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Source channel @githubtrending · Post #15539 · Mar 5
#python#agent#llm#llm_agent#llm_reasoning#machine_learning_systems#mlsys#reinforcement_learning#rl AReaL is a free, open-source system for fast asynchronous reinforcement learning to train large AI models in math, coding, search, and agents. It decouples generation and training for up to 2.77x speedup, stable performance, and easy setup on single or 1000+ GPUs with algorithms like GRPO/PPO. Install via git/pip, run examples like GSM8K math instantly. You benefit by building top AI agents affordably and quickly, reproducing results with shared data/models, saving time/money vs. slow synchronous tools. https://github.com/inclusionAI/AReaL
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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