Event details
Infrastructure Built for Production-Scale AI
Today’s frontier and mixture-of-experts models aren’t small. They span multi-trillion parameters and require precise coordination across thousand-GPU clusters.
Traditional cloud environments simply aren’t built for this scale. To move from experimentation to real-world deployment, teams need infrastructure purpose-built for sustained, large-scale workloads.
In this session, CoreWeave will detail how we’ve optimized every layer of the AI stack—from infrastructure to orchestration to observability—to efficiently run large-scale training and inference workloads. We’ll also examine the architectural breakthroughs that enable rack-scale systems to operate with ultra-low latency and high reliability.
These are the essential cloud components that will power the next generation of agentic AI. The question is: How does your infrastructure stack up?
In this webinar, we’ll cover:
- How infrastructure requirements change when scaling to trillion-parameter and mixture-of-experts models
- How full-stack optimization across infrastructure, orchestration, and observability improves performance and efficiency
- Architectural innovations enabling ultra-low latency, rack-scale AI systems
- Best practices for running production-grade AI workloads, including agentic AI systems
Speakers
