Rachel Rapp

RBAC from the ground up: Solving for autonomy vs. control There are two things every organization needs from its inference platform, and they pull in opposite directions. The first is individual autonomy: engineers and researchers need to deploy models, iterate on training jobs, and push changes to workloads without waiting on an admin or filing a ticket (in other words: speed matters).

Nemotron 3 Super and the case for open agentic AI As GenAI applications move towards multi-agent systems—retrievers, planners, tool executors, and verifiers working in concert—their infrastructure demands change. Communication overhead, context drift, and inference calls scale with agent count.

The Baseten Inference Stack powers our Dedicated Inference and Model APIs, delivering the lowest latency, highest throughput, and highest uptime for generative AI workloads. We achieve this by combining open-source and in-house tools—runtime engines, scheduling layers, and model-specific optimizations—and using each as best suited to a particular model and use case. One of those tools is NVIDIA Dynamo.