AI.SEA Co-Labs: How does Fine-Tuning Actually Work (and when should you bother?)

About this event

How does fine-tuning actually work (and when should you bother)?

Most builders have a vague sense that fine-tuning exists. Fewer know what it actually does to a model. Even fewer know when to reach for it versus just prompting better, adding RAG, or switching models entirely.

This session fixes that.

We'll walk the full spectrum — from in-context learning to LoRA to full fine-tuning — with one question at every stop: what are you actually changing, and toward what? By the end you'll have a mental model sharp enough to make the call yourself.

As always, guided discussion. No passive listening.

What we'll cover

— Why the pretrained model already has opinions before you touch it — The fine-tuning spectrum: what changes, what it costs, and when each approach makes sense — LoRA, QLoRA, and why low-rank approximations work better than they should — Loss functions, SFT, and DPO — what you're actually optimising for and how you'd know if it's wrong — Hands-on: fine-tuning a small model + comparing base vs fine-tuned outputs

Who this is for

Builders who've shipped something with LLMs and want to go deeper. Some technical depth assumed — we won't be explaining what a token is.

Format Guided discussion + hands-on practicalVenue: Co-labs Coworking, KL Sentral Organized by AI.SEA