Machine Learning Operations (MLOps) and ML & AI Governance can align innovation and safety to bring utility solutions to production faster. We’ll discuss key components of robust MLOps and ML Governance programs, including security, privacy, legal and compliance, operations, and ethical considerations.
- How to build a flexible and scalable approach that engages AI stakeholders with strategy, process, and tools.
- Importance of a value-driven AI governance board for building ethical AI tools, including model production approval and oversight for tools like ChatGPT.
- Overview of technical practice accelerators that meet AI governance standards and speed up the process.
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