Focused Language Models: A Hallucination-Free Solution for GenAI

January 28, 2026 Rachel Kim – Technology Editor Technology

Here’s a breakdown of the key steps in training the FLM (presumably a Foundation Language model) as described in the provided text:

  1. seed Data from Experts: Subject matter experts provide initial, high-quality data (“seed data”) to guide the model.
  2. Synthetic Data Generation: The data science team expands this seed data into massive volumes of synthetic language data. A small number of examples (like customer treatment scenarios) can be multiplied into millions of synthetic examples.
  3. Benefits of Synthetic Data:

* Consistent Behavior: Ensures the FLM acts predictably in real-world applications.
* Privacy: Avoids the use of Personally Identifiable Information (PII), addressing a major concern.

  1. Augment with Real-World Data: The FLM is further improved by incorporating real customer data, such as:

* customer History: Past interactions.
* Transaction Records: purchase history.
* Relationship Length: How long the customer has been with the company.
* Data Sources: This data is pulled from systems like CRM (Customer Relationship Management) and other enterprise databases.

In essence, the process combines expert knowledge, artificially generated data for scale and privacy, and real-world data for personalization and accuracy.