▶ Watch ↗AI Engineer World's Fair 202423:14
Accelerate your AI journey with Azure AI model catalog
Read the full talk →Key ideas
Scroll to read ↓Follow model discovery, deployment, grounded chat, function calling, and flow evaluation to see how a shared inference interface supports application-specific model choices.
- Can AI solve the use case—and can it scale?1:29 ↗
- Choose capabilities, not just model size3:14 ↗
- Inspect a model, deploy it, and compare benchmarks4:25 ↗
- Give the same question a better source7:12 ↗
- Separate infrastructure choice from the inference interface9:36 ↗
- Use a function for the shop’s actual bill11:08 ↗
- Build retrieval as a flow, then vary the models13:42 ↗
- Control data handling, model integrity, and access16:25 ↗
- From internal assistance to customer-care automation18:34 ↗
- Forecasting broadens the catalog beyond chat21:16 ↗