Explore strategies for managing AI costs and maximizing ROI in this informative webinar designed for data scientists, platform engineers, and finance operations managers responsible for AI-based applications. Delve into the challenges of tracking AI cloud expenses and learn how to transition from cost management to planning and forecasting for profitable AI-based products and services. Gain insights from industry leaders Raja Iqbal of Data Science Dojo and Asim Razzaq of Yotascale as they discuss future-proofing AI initiatives, addressing cost implications of ML inference paths, exploring the convergence of organizational roles in cost management, implementing FinOps for LLMs, and examining latency considerations. Discover essential techniques for building a cost-effective modern data stack AI project and ensure the long-term viability of your AI products in an increasingly competitive market.
Overview
Syllabus
– Introduction
– Cost implications of multiple paths to ML inference
– Who manages costs as an organization and roles Converge
– FinOps for LLMs
– Strategies for managing AI costs
– Latency
– Where do we go from here?
Taught by
Data Science Dojo
