Lessons in accelerating foundation model upgrades
Have you run into problems migrating your products from one model to the next?
Upgrading to the latest AI models is rarely simple. For engineering teams, model updates whether migrating to an entirely new model or updating to a newer checkpoint within the same model family, like moving from an earlier Gemini version to Gemini 3.5 — often require a slow and costly process of testing, proving quality, and manually evaluating new responses. For most engineering teams, upgrading to a new model checkpoint means months of manual toil to verify performance. And the industry is moving at breakneck pace – since 2023, we’ve announced six major model evolutions, bringing us to Gemini 3.5 today.
Our team at Google Cloud, Applied ML, has a goal to deliver transformative infrastructure and services that benefit both Google and our customers globally. As part of that, our team built an agentic workflow that completes...
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