Open Ecosystem to Fight Closed Models in Large Language Models

Explore the challenges and opportunities of open-source Large Language Models (LLMs) in this 21-minute talk by Filippo Pedrazzini at MLOps.community. Delve into the growing trend of tech giants restricting OpenAI product usage due to privacy concerns, and discover how self-hosted open-source LLMs offer a privacy-preserving alternative. Learn about model interoperability issues and the complexities of working with a single API without third-party interaction. Gain insights from Pedrazzini's expertise as he shares innovative solutions to overcome obstacles in integrating open-source LLMs into application production. Understand the benefits of open-source AI and explore topics such as quality improvement, hardware constraints, in-house proof of concept, deployment strategies, and the Prem Challenge. Benefit from the speaker's experience as a CTO and Data Engineer with AI expertise and a track record in transforming legacy systems and leading AI innovations.

Intro
Outline
1. Quality: Tips & Tricks
Hardware Constraints
2. HW Constraints: Tips & Tricks
In-House POC & Deployment
The Benefits of Open Source
Prem Challenge