Comparison
Fine-tuning vs Machine Learning
Fine-tuning and Machine Learning are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Fine-tuning
After you've exhausted prompting and retrieval, and you have a few hundred to thousands of clean labeled examples.
Fine-tuning Llama 3 on medical Q&A for a clinical assistant.
When you would reach for Machine Learning
Machine Learning comes up when the question is fundamentally about foundations.
A spam classifier learning what spam looks like from labeled examples (supervised).
Frequently asked
What is the difference between Fine-tuning and Machine Learning?
Fine-tuning: Fine-tuning continues training a pretrained model on a smaller, task-specific dataset, adjusting its weights to specialize behavior or knowledge. Machine Learning: Machine learning is the branch of AI in which models learn patterns from data instead of being explicitly programmed. The training process adjusts model parameters to reduce error on examples.
When should I use Fine-tuning vs Machine Learning?
After you've exhausted prompting and retrieval, and you have a few hundred to thousands of clean labeled examples. Machine Learning applies when you are focused on foundations.
Are Fine-tuning and Machine Learning the same thing?
No. Fine-tuning is training; Machine Learning is foundations. They are related but address different parts of the AI stack.