Reduce Your AI Cloud Costs Management: Learn from Experts of Data Science Dojo & Yotascale

Learn the challenges of tracking AI cloud costs and how to improve your AI cloud costs for profitable AI-based products and services.

This talk is intended for data scientists, platform engineers, and finance operations managers who are responsible for AI-based applications and need to manage their public cloud infrastructure costs closely.

Artificial Intelligence and Machine Learning are the new frontiers of software development. Massive market demand for AI is pushing up cloud infrastructure costs. Profitable AI products require collaborative management between data science, platform engineering, and increasingly FinOps teams. An 80% public cloud cost contribution to the cost of goods sold is no longer viable when launching new digital products.

Join industry leaders, Raja Iqbal of Data Science Dojo and Asim Razzaq of  @yotascale  as they discuss how to future-proof your AI initiatives. Cloud cost management is an essential element of any modern data stack AI project.

Table of Contents:
0:00 – Introduction - How to future proof your AI initiatives
12:59 – Cost implications of multiple paths to ML inference
26:26 – Who manages costs as an organization and roles Converge
42:15 – FinOps for LLMs
47:14 – Strategies for managing AI costs
21:12 – Latency Considerations
54:36 – Future of AI cost management?

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Dive deeper into Generative AI and Large Language Models with this playlist:    • Getting Started with Large Language M...  

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