<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Vertex AI on 梦兽编程</title><link>https://rexai.top/en/tags/vertex-ai/</link><description>Recent content in Vertex AI on 梦兽编程</description><generator>Hugo -- 0.163.3</generator><language>en</language><copyright>梦兽编程</copyright><lastBuildDate>Tue, 21 Jul 2026 10:00:00 +0800</lastBuildDate><atom:link href="https://rexai.top/en/tags/vertex-ai/index.xml" rel="self" type="application/rss+xml"/><item><title>BigQuery AI.AGG: When GROUP BY Starts Calling Gemini</title><link>https://rexai.top/en/ai/llm/bigquery-ai-agg/</link><pubDate>Tue, 21 Jul 2026 10:00:00 +0800</pubDate><guid>https://rexai.top/en/ai/llm/bigquery-ai-agg/</guid><description>Google wired Gemini into a BigQuery aggregate. Each group now returns one natural-language answer. We walk through SQL semantics, hidden batching, cost pitfalls, and four engineering guardrails.</description></item></channel></rss>