
Explore efficient storage, versioning, and distribution of AI/ML models using OCI Artifacts. Learn to break models into atomic units for optimized updates and reassembly on target devices.

Discover how Databricks Lakehouse Monitoring enhances data pipeline and ML model oversight, ensuring quality and governance for a self-serve data platform through continuous assessment and intelligent issue prevention.

Explore security vulnerabilities in open-source AI models, including live demonstrations of exploits and techniques for embedding malicious code and data poisoning.

Explore federated user representation learning for privacy-preserving collaborative personalization in machine learning, improving model quality while maintaining user privacy.