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generative ai

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2020-Q1 2026-Q1

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Generative AI has incredible potential, but turning that potential into real-world impact requires more than just a proof of concept. Join Matheus Guimaraes for a journey into what it takes to bring generative AI into production — from adoption and development to testing, deployment, and observability. Along the way, you’ll see how new patterns like agentic AI, open-source frameworks like Strands, and AWS services like AgentCore are reshaping the way we build with AI.

Curious how to apply resource-intensive generative AI models across massive datasets without breaking the bank? Join this session to discover efficient batch inference strategies for foundation models on Databricks. Learn how to build scalable, cost-effective pipelines that power LLMs and other generative AI systems—optimized for performance, quality, and throughput. We’ll also dive into ai_query, a powerful new capability that lets you run generative AI directly on your data using SQL-like syntax. See how it simplifies development, unlocks new use cases, and accelerates insights with live demos and real-world examples.

Traces the evolution of data use in clinical practice from real-time patient data collection and interpretation to precision medicine and real-time clinical decision support. Discusses the development of biostatistics, randomized controlled trials, meta-analyses, and the impact of big data and generative AI on the future patient–doctor relationship and healthcare.

In this talk we’ll explore how we maximize the potential of the FiftyOne open source SDK and App to efficiently store and annotate training data critical to Finegrain’s Generative AI workflows. We will provide an overview of our cloud-based storage and hosting architecture, showcase how we leverage FiftyOne for training and applying models for semi-automatic data annotation, and demonstrate how we extend the CVAT integration to enable pixel-perfect side-by-side evaluation of our Generative AI models.