<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Google on AI 早报</title><link>https://ai-news.example.com/tags/google/</link><description>Recent content in Google on AI 早报</description><generator>Hugo</generator><language>zh-CN</language><lastBuildDate>Tue, 07 Jul 2026 23:13:10 +0800</lastBuildDate><atom:link href="https://ai-news.example.com/tags/google/feed.xml" rel="self" type="application/rss+xml"/><item><title>[EN] Google ScreenAI：5B参数视觉语言模型，在UI与信息图理解任务上达到最先进水平</title><link>https://ai-news.example.com/articles/en-google-screenai5bui/</link><pubDate>Tue, 07 Jul 2026 23:13:10 +0800</pubDate><guid>https://ai-news.example.com/articles/en-google-screenai5bui/</guid><description>Google Research推出的ScreenAI是一种基于PaLI架构与pix2struct灵活分块策略的视觉语言模型，能以5B参数在UI与信息图理解任务中取得领先效果，同时自动生成大规模训练数据。</description></item><item><title>[EN] AutoBNN：谷歌开源概率时间序列预测工具，结合贝叶斯神经网络与可解释性</title><link>https://ai-news.example.com/articles/en-autobnn/</link><pubDate>Sun, 05 Jul 2026 01:52:03 +0800</pubDate><guid>https://ai-news.example.com/articles/en-autobnn/</guid><description>谷歌推出开源工具AutoBNN，基于组合贝叶斯神经网络，自动发现可解释的时间序列预测模型，提供高质量的不确定性估计，并在大规模数据集上高效扩展。</description></item></channel></rss>