Accelerating Multimodal AI // Ethan Rosenthal // #242

Join us at our first in-person conference on June 25, all about AI Quality: https://www.aiqualityconference.com/Accelerating Multimodal AI // MLOps podcast #241 with Ethan Rosenthal, Member of Technical Staff of Runway.Huge thank you to AWS for sponsoring this episode. AWS - https://aws.amazon.com/// AbstractWe’re still trying to figure out systems and processes for training and serving “regular” machine learning models, and now we have multimodal AI to contend with! These new systems present unique challenges across the spectrum, from data management to efficient inference. I’ll talk about the similarities, differences, and challenges that I’ve seen by moving from tabular machine learning to large language models to generative video systems. I’ll also talk about the setups and tools that I have seen work best for supporting and accelerating both the research and productionization process.// BioEthan works at Runway Building Systems for media generation. Ethan's work generally straddles the boundary between research and engineering without falling too hard on either side. Prior to Runway, Ethan spent 4 years at Square. There, he led a small team of AI Engineers training large language models for Conversational AI. Before Square, Ethan freelanced, consulted, and worked at a couple of e-commerce startups. Ethan found his way into tech by way of a Physics PhD.// MLOps Jobs board jobs.mlops.community// MLOps Swag/Merchhttps://mlops-community.myshopify.com/// Related LinksWebsite: https://www.ethanrosenthal.comEthan's mangum opus: https://www.ethanrosenthal.com/2020/08/25/optimal-peanut-butter-and-banana-sandwiches/Real-time Model Inference in a Video Streaming Environment // Brannon Dorsey // Coffee Sessions #98: https://youtu.be/TNO6rYwP3yg Feature Stores for Self-Service Machine Learning: https://www.ethanrosenthal.com/2021/02/03/feature-stores-self-service/Gen-1: The Next Step Forward for Generative AI: https://research.runwayml.com/gen1Machine Learning: The High Interest Credit Card of Technical Debt by D. Sculley et al.: https://research.google/pubs/machine-learning-the-high-interest-credit-card-of-technical-debt/ --------------- ✌️Connect With Us ✌️ -------------Join our Slack community: https://go.mlops.community/slackFollow us on Twitter: @mlopscommunitySign up for the next meetup: https://go.mlops.community/registerCatch all episodes, blogs, newsletters, and more: https://mlops.community/Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/Connect with Ethan on LinkedIn: https://bsky.app/profile/ethanrosenthal.comTimestamps:[00:00] Ethan's preferred coffee[00:11] Takeaways[02:07] Falling into LLMs[03:16] Advanced AI Tech Capabilities[04:40] AI-powered video editing tool[06:56] Transition to AI: Diffusion Models[09:09] Multimodal Feature Store breakdown[15:33] Multimodal Feature Stores Evolution[18:09] Benefits of Multimodal Feature Store[25:09] Centralized Training Data Repository[27:33] Large-scale distributed training[32:37 - 33:39] AWS Ad[33:45] Dealing with researchers on productionizing[43:52] Infrastructure for Researchers and Engineers[47:04] Generative DevOps movement[49:21] Structuring teams[52:06] Multimodal Feature Stores Efficiency[54:02] Wrap up