The Hidden Challenges of Running AI at Scale in Production
The Data Exchange with Ben Lorica
CoreWeave's SVP of Engineering, Chen Goldberg, discusses the shift from AI experimentation to production across diverse industries. Companies outside Silicon Valley are leveraging their unique data assets to innovate, prompting a need for specialized AI cloud platforms. Goldberg highlights that companies engaged in AI training or inference for production workloads prioritize security, reliability, and scale, and should consider AI-first cloud platforms. She introduces CoreWeave's ARENA, a real infrastructure environment for benchmarking AI workloads, and emphasizes the importance of "goodput," the actual time GPUs spend on useful work. Goldberg also touches on the increasing accessibility of reinforcement learning and the growing adoption of AI agents, while advising companies to experiment with AI to avoid falling behind.
Part 1: Introduction, CoreWeave Overview
Part 2: Industry Use Cases, Training
Part 3: Infrastructure, Scaling, Performance
Part 4: Supply Chain, Hyperscaling
Part 5: Emerging Trends, Agents, Open Source
Part 6: Strategy, Future Outlook
Sign in to continue reading, translating and more.
Open full episode in Podwise
