See how to use MLRun 1.7 to fine-tune a generative AI banking chatbot, ensuring it answers only relevant banking inquiries. Watch the full tutorial and follow along!

This demo recorded during our MLOps Live Webinar #32 showcases a customer-facing AI agent developed for a jewelry retailer. This can be used as a marketing tool to offer personalized product recommendations and purchasing information and support.

In this MLOps Live session we were joined by Eli Stein, Partner and Modern Marketing Capabilities Leader at McKinsey, to delve into how data scientists can leverage generative AI to support the company’s marketing strategy. We showcased a live demo of a customer-facing AI agent developed for a jewelry retailer, which can be used as a marketing tool to offer personalized product recommendations and purchasing information and support. Following the demo, we held an interactive discussion and Q&A session. Enjoy!

In this session, we explored the unique challenges of implementing gen AI in production environments, when agents are in direct contact with your customers. We shared the Iguazio & MongoDB one-stop-shop solution for building gen AI applications that scale effectively and efficiently, with built-in guardrails and monitoring. We'll show how the end-to-end application lifecycle is addressed – From data management all the way to governance and monitoring in production.

In this webinar we discussed the transformative impact of gen AI on enterprise operations, spotlighting advancements across manufacturing, supply chain and procurement. We covered the main gen AI use cases, challenges to be mindful of during implementation and key learnings from client projects; highlighting three main pillars –people, processes and technology.

Watch session #28 in our MLOps Live Webinar Series featuring Databricks where we discuss improving LLM accuracy & performance. Hear Margaret Amori (Databricks), Vijay Balasubramaniam (Databricks) , and Yaron Haviv (Iguazio) share best practices and pragmatic advice on successfully improving the accuracy and performance of LLMs while mitigating challenges like risks and escalating costs. See real examples including techniques to overcome common challenges using tools such as Databricks Mosaic AI and their new open LLM, DBRX.

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.