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cloud.google.com·4h ago
Cloud & Infrastructure
Google Cloud Blog·4h ago·5 min read
Architecting autonomy: A design pattern for high-compute, governed agents in biotech
TL;DR
A new three-layer architecture for high-compute autonomous agents in biotech enhances drug discovery workflows by separating cognitive orchestration from computational execution. This design addresses the limitations of traditional AI models in handling complex, stateful tasks.
✦ Why It Matters
Consider adopting a three-layer architecture to enhance your biotech R&D workflows today.
Key Takeaways
- Separate cognitive orchestration from computational execution for efficiency.
- Utilize NVIDIA Inference Microservices for high-compute tasks.
- Maintain agent identity for robust data governance.
- Implement asymmetric autonomy to balance automation and oversight.
How It Works
The architecture consists of a cognitive orchestrator that manages workflows and a scalable GPU execution layer for heavy computations. By using NVIDIA Inference Microservices, the system ensures low latency and efficient handling of large datasets.
Agents communicate internally without network delays, and complex data is passed by reference to minimize context overload.