

Evolving MLOps Platforms for Generative AI and Agents with Abhijit Bose - #714
145 snips Jan 13, 2025
Abhijit Bose, Head of Enterprise AI and ML platforms at Capital One, shared insights into the evolution of their generative AI platform. He discussed the transition to a platform-centric approach in finance and the integration challenges faced by MLOps. Bose delved into optimizing Llama models for improved customer service and the role of Kubernetes in enhancing machine learning workflows. He also highlighted the significance of cloud architecture in AI experimentation and the new skill sets required for thriving in the generative AI landscape.
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Platform-Centric Approach
- Capital One prioritizes platform development for AI/ML work.
- This centralized approach improves resource utilization, governance, and user satisfaction (high NPS score).
Flexible Platform
- Build a robust ML platform control plane, allowing flexibility to integrate various tools and services.
- This approach enables faster adaptation to evolving technologies like GenAI.
GenAI Observability
- Generative AI observability requires new monitoring for hallucinations and guardrails, beyond traditional ML monitoring.
- This added complexity necessitates building new infrastructure for comprehensive logging and analysis.