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Learn the essential considerations for productionizing generative AI models in this introductory conference talk that covers the complete journey from model development to deployment. Explore the fundamental decisions data scientists and developers must make when building GenAI services, including model serving architectures, concurrency management, and real-time streaming implementations. Discover how to handle multiple concurrent requests and implement batch processing while maintaining optimal performance through techniques like quantization. Master the implementation of authentication and authorization layers to secure your services, and understand how to protect against model jailbreaking attacks using guardrails. Gain insights into testing probabilistic GenAI models using the Checklist framework with Minimum Functionality Tests, Invariance testing, and Expectation testing methodologies. Understand various deployment patterns specifically designed for generative AI services, along with containerization strategies for scalable production environments. The session provides a high-level overview using visual diagrams to explain complex concepts, making it accessible for those with basic technical knowledge while covering the core challenges and proven approaches for building robust generative AI services.
