Have you ever dreamt of AI that is truly yours? Not the crude "let me stuff some details into the context of gpt-X and hope it works out", but truly having a model that is specific to problems you want to solve?

Realistically though, you won't be training half-a-trillion parameter models, and smaller ones which you can wrangle locally lack quite the je ne sais quoi of general intelligence.

The solution, of course, is fine-tuning! Which, if you're an application developer, looks scary and smells like Python and years spent on Ph.D in machine learning.

Let's make it more approachable! This session will demystify the world of fine-tuning, transforming it from a scary machine learning discipline into a practical application development tool.
We will cut through the jargon to make you less likely to start daydreaming about Spring Boot when someone mentions pokemon sounding machine learning words like LoRa or Unsloth.

You'll learn how to leverage tools developers use every day to fine-tune small, high-performance models, for example Gemma 3n, for custom tasks. And leave with the courage and concrete knowledge to start adapting LLMs' behavior to your problems at hand.