What does a GPU rich developer actually do all day, besides checking power consumption and inventing increasingly creative justifications for the hardware?

A new class of AI machine now sits somewhere between a powerful workstation and a datacenter in the basement. NVIDIA calls these deskside AI supercomputers. Other vendors use large unified memory pools to fit models locally that once required cloud infrastructure.

In this session, we will spend a day running large models, fine tuning them, unleashing AI agents, and conducting experiments that seemed sensible at the time. We will see what changes when an idea becomes a local command instead of a provisioning exercise, a data upload, and a rapidly spinning cloud meter.

We will also confront cost, heat, software friction, and the awkward amount of time an expensive machine can spend doing absolutely nothing.

Expect hundreds of gigabytes of memory and enough power draw to make the air fryer nervous. You will leave knowing when local compute is liberating, when the cloud still wins, and whether being GPU rich is actually worth it.