8 Matching Annotations
  1. Jun 2025
    1. 能力: - 语音转录支持本地(WhisperCpp/FasterWhisper) 和在线(B接口/J接口??) - 字幕翻译支持传统引擎和LLM - 传统引擎: DeepL/微软/谷歌 - LLM: Ollama、DeepSeek、硅基流动以及【OpenAI兼容接口】 (配套提供LLM API中转站)

      安装部署 - Windows提供一键安装包 - MacOS需要自行基于python搭建,且作者说未验证过 👎 。另外本地 whisper 功能尚不支持macos)

  2. Mar 2025
    1. The analysis uncovered an average of 11 different types of data out of the 35 possible. As mentioned earlier, Google Gemini stands out as the most data-hungry service, collecting 22 of these data types, including highly sensitive data like precise location, user content, the device's contacts list, browsing history, and more.Among the analyzed applications, only Google Gemini, Copilot, and Perplexity were found to collect precise location data. The controversial DeepSeek chatbot stands right in the middle, collecting 11 unique types of data, such as user input like chat history.
  3. Feb 2025
  4. Jan 2025
    1. Take aways: AI will become cheaper and more efficient. - closed source models can cache responses and save computations for repetitive queries - closed source also has possibility of iterative improvements using constant reinforcement learning. - Prioritizing capabilities and deliberate strategy in data selection, carefully designed training objectives.