In this session, Yaron Haviv, CTO Iguazio was joined by Ehud Barnea, PHD, Head of AI at Tasq.ai and Guy Lecker ML Engineering Team Lead, Iguazio to discuss how to validate, evaluate and fine tune an LLM effectively. They shared firsthand tips of how to solve the production hurdle of LLM evaluation, improving LLM performance, eliminating risks, along with a live demo of a fashion chatbot that leverages fine-tuning to significantly improve the model responses.

Efficiency means doing things right. The multi-environment feature introduced in the insightsoftware Platform underlines this. It enables you to assign licenses per environment to a specific user, ensuring the most efficient distribution your licenses that suits your unique requirements.

Automated free text feature engineering uses sophisticated algorithms under the hood to allows far better prediction from free text fields. This complements the date feature engineering capability we released last year, which automatically parses dates into usable features. Organizations now have role-based access control for AutoML users. We’ve added two new user roles to support AutoML – experiment contributors and deployment contributors, which can be assigned to specific users or groups. With this, you can now control and limit access to AutoML to the right types of users.