将AI提供的答案和摘要带到网络文件预览中

Dropbox offers a handful of features that use machine learning to understand content much like a human would. For example, Dropbox can generate summaries and answer questions about files when those files are previewed on the web. Instead of asking a coworker for the gist of last week’s all-hands meetings, Dropbox can provide a summary of the video and a user can ask questions about its contents—all from the file preview. We recently expanded AI-powered summarization and Q&A to handle multiple files simultaneously, too. 

Dropbox提供了使用机器学习来理解内容的一些功能，就像人类一样。例如，当在Web上预览文件时，Dropbox可以生成摘要并回答关于文件的问题。不再需要向同事询问上周全体会议的要点，Dropbox可以提供视频摘要，用户可以就其内容提问-所有这些都可以在文件预览中完成。我们最近还扩展了AI驱动的摘要和问答功能，可以同时处理多个文件。

(As part of our commitment to responsibly using AI, Dropbox abides by a set of AI principles; you can visit our Help Center to learn more. These features are still in early access, and not yet available to all users. These features are also optional, and can be turned on or off for you or your team.)

（作为我们负责任地使用人工智能的承诺的一部分，Dropbox遵守一套AI原则；您可以访问我们的帮助中心了解更多信息。这些功能仍处于早期访问阶段，尚未对所有用户开放。这些功能也是可选的，您可以为您或您的团队打开或关闭。）

Both our summarization and Q&A features leverage large language models (LLMs) to find, compare, and consolidate the content of the file. An LLM works by ingesting content as text, transforming the ideas contained within it into a numerical representation, and comparing those numerical representations against both the input query and an internal corpus of knowledge to answer the question. This effectively enables a computer to consume and compare information semantically, rather than lexically.

我们的摘要和问答功能都利用了大型语言模型（LLM）来查找、比较和整合文件的内容。LLM通过将内容作为文本输入，将其中包含的思想转化为数值表示，并将这些数值表示与输入查询和内部知识库进行比较，以回答问题。这有效地使计算机能够以语义方式消化和比较信息，而不是词汇方式。

For knowledge workers suffering from information overload, we can use machine learning to get them the answers they need—without them having to remember exactly how a piece of information was worded, or where it might be contained within a file. This is what we’ve done with file previews on the web.

对于遭受信息过载的知...