Understanding edge to core data pipelines to train future AI/ML models
Red Hat Device Edge Technical Overview, Part 2 - RHEL
RHEL AI and InstructLab for Employee Productivity
Learn how to add your own knowledge and skills to a Large Language Model using the InstructLab Project. This approach uses synthetic data generation to enable anyone to craft a model for specific use cases.
Speakers
Jeremy Eder | Distinguished Engineer
A 20+ year tech industry veteran, Jeremy is a Distinguished Engineer within the Red Hat AI product group, building Red Hat's AI/ML and Open Source strategy. His role involves working with engineering and product leaders across the company to devise a strategy that will deliver a sustainable open source, enterprise software business around artificial intelligence and machine learning. He is a proven technical leader and intrapreneur, having seeded several significant initiatives that have made their way into Red Hat’s products, services and process. Jeremy was the recipient of Red Hat’s Chairman's Award and remains a frequent author and presenter. He previously specialized in software performance analysis (including significant work in CPU and hardware accelerators), managed cloud services, and currently works in the AI/ML space as a corporate strategist, ensuring that Red Hat is positioned appropriately as the AI/ML space consolidates.
Grant Shipley | Sr. Director, Gen AI Model Platforms
Grant Shipley is a Sr. Director at Red Hat focused on Gen AI Platforms. He has had numerous roles throughout his career, including management of software development and infrastructure teams, and brings more than 20 years of experience in software development focusing on Linux, Java, and Node.js. Most recently, he was at VMware and worked on several critical areas related to Tanzu including Tanzu Community Edition, Tanzu Advanced, and Tanzu Application Platform.