@kejiqu · Post #4116 · 01/31/2026, 01:44 AM
有人将 Apple 最令人恼火的 bug 变成了浪费人类时间的计分板 一个新网站将 Apple 最为持久的软件 bug 转化为一个幽默的计分板,利用夸张的数学计算来估算这些 bug 造成的集体人类时间浪费。该网站旨在以一种轻松的方式呈现 Apple 长期存在的软件问题,并量化其对用户的影响。9to5Mac 🏷#Apple#bugs#scoreboard#wasted#time 📢频道👥群组📝投稿
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Source channel @githubtrending · Post #15385 · Jan 2
#python#deep_learning#inference#openai#quantization#speech_recognition#speech_to_text#transformer#whisper Faster-Whisper is a fast version of OpenAI's Whisper that transcribes audio up to 4x quicker with the same accuracy, using less memory on CPU or GPU—benchmarks show it beats original Whisper (e.g., 1m03s vs 2m23s for 13-min audio on GPU). Install via `pip install faster-whisper`, no FFmpeg needed, and use simple Python code like `WhisperModel("large-v3").transcribe("audio.mp3")` for segments with timestamps. You benefit by getting quick, efficient speech-to-text for real-time apps, saving time and resources on long files or batches. https://github.com/SYSTRAN/faster-whisper
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@kejiqu · Post #4116 · 01/31/2026, 01:44 AM
有人将 Apple 最令人恼火的 bug 变成了浪费人类时间的计分板 一个新网站将 Apple 最为持久的软件 bug 转化为一个幽默的计分板,利用夸张的数学计算来估算这些 bug 造成的集体人类时间浪费。该网站旨在以一种轻松的方式呈现 Apple 长期存在的软件问题,并量化其对用户的影响。9to5Mac 🏷#Apple#bugs#scoreboard#wasted#time 📢频道👥群组📝投稿