The complexity and scarcity of deploying GPUs can bring AI development to a standstill. What if there was a better way to train, fine-tune, and serve models on accelerated compute infrastructure entirely in Python? See how during this session where we fine-tune 20 Llama models without doing any infrastructure work. Startups and enterprises can finally gain unprecedented speed and agility to build, iterate, and deploy anything that they can imagine, from multi-agent, multi-modal AI applications, to digital twins for real world simulation. What used to take weeks with dozens of best-in-class engineers can now be accomplished in hours from a single notebook.