Nvidia dynamo

AI Tokenomics Explained

AI Tokenomics Explained

A product and go-to-market lead at NVIDIA examines the economics of AI inference as agentic AI multiplies token demand. The talk covers matching premium versus efficient models to use cases, model routing, open models, sizing token demand, and extreme co-design across mixture-of-experts models, NVLink systems, KV caching, software stacks, and CPUs to maximize tokens per watt and minimize cost per token.

Dedicated Inference

Dedicated Inference

A walkthrough of CoreWeave's three inference paths (Serverless, Dedicated, and Inference on CKS), covering when each fits, how a multi-agent research assistant uses OpenAI-compatible endpoints across model types, and live demos of gateways, deployments, and Kubernetes-based vLLM, Dynamo, and LLM-D serving.