Successfully deploying AI applications into production requires a strategic approach that prioritizes cost efficiency without compromising performance. In this one-hour mini-summit, we'll explore how to optimize costs across the key elements of AI development and deployment. Discover how AWS AI chips, Trainium and Inferentia, offer high-performance, cost-effective compute solutions for training and deploying foundation models. Learn how Outerbounds' platform streamlines AI workflows and makes the most of underlying compute resources, ensuring efficient and cost-effective development. Gain insights into the latest advancements in cost-efficient AI production and learn how to drive innovation while minimizing expenses.

October 2024 MLOps reading group session explores the role and relevance of small language models in an era dominated by large language models (LLMs). The author of a recent survey paper on small models joins to discuss motivations for using smaller models, including resource constraints, efficiency, and unique capabilities they bring to certain tasks. Key discussion points include the advantages of small models in specific contexts (e.g., edge devices and specialized tasks), their role in complementing large models, and emerging techniques for leveraging small models to enhance model efficiency and mitigate issues like out-of-vocabulary words. The group also touches on methods for compressing models and the challenges in balancing model size with generalization and task-specific performance.

Dive into AI risk and compliance. Petar Tsankov, a leader in AI safety, talks about turning complex regulations into clear technical requirements and the importance of benchmarks in AI compliance, especially with the EU AI Act. We explore his work with big AI players and the EU on safer, compliant models, covering topics from multimodal AI to managing AI risks. He also shares insights on COMPL-AI, an open-source tool for checking AI models against EU standards, making compliance simpler for AI developers. A must-listen for those tackling AI regulation and safety.