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Cloud & Infrastructure
Google Cloud Blog·19d ago·5 min read
Three lessons in accelerating foundation model upgrades
TL;DR
Upgrading AI models is often a lengthy process, but Google Cloud's Applied ML team has developed a new agentic workflow that reduces migration time from months to hours. By leveraging the Gemini Enterprise Agent Platform and Google Antigravity, they have streamlined the model upgrade process.
✦ Why It Matters
Engineers can implement the Gemini Enterprise Agent Platform to streamline their AI model upgrade processes today.
Key Takeaways
- Engage in hands-on discovery to identify migration challenges.
- Avoid rigid automation; adapt processes to unique project needs.
- Utilize the Agent Development Kit for creating custom agents.
- Leverage Antigravity for automating coding and orchestration tasks.
How It Works
The agentic workflow uses a flexible agent architecture that adapts to specific project requirements, allowing for dynamic analysis and testing of prompts. This flexibility enables teams to efficiently evaluate new model checkpoints and optimize performance without being constrained by traditional automation limitations.