Have you ever wondered how AI engineers fine-tune and align large language models? Under the hood, they run Supervised Fine-Tuning (SFT), optimize parameters using direct preference gradients (DPO), filter out low-quality pre-training corpuses (Pruning), and mitigate catastrophic drifts.
To help you visualize how LLM alignment and parameter optimization work in a highly strategic way, I built a cyberpunk card battler inspired by Gwent:
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Your mission as an alignment engineer is to play optimizer cards to outscore the adversarial baseline AI across 3 training Epochs:
Here is how the card battle mechanics map to production machine learning pipelines:
