Fine-Tuning

Fine-Tuning is a machine learning technique where an existing, general-purpose foundational model is subjected to an additional round of training using a specialized, niche dataset.

Instead of spending millions of dollars to train an AI from scratch, an organization can take an open-source Large Language Model and fine-tune it on their own internal medical records, legal contracts, or engineering schematics.

This results in a highly specialized, hyper-competent model that intimately understands the organization's unique domain language and business logic, serving as the ultimate asset in a Private AI deployment.