Solution Study
Monday, September 25
04:00 PM - 04:30 PM
Live in Berlin
Less Details
Machine learning (ML) has permeated almost every stage of the autonomous vehicle design from perception, behavior prediction, motion planning, control, mapping, and routing. However, there are some unique technical challenges and pitfalls to avoid when developing ML models for autonomous driving systems. During this talk, HPE’s VP of AI Portfolio, Joey Zwicker, will discuss key aspects to consider when implementing ML for autonomous vehicles – like how to efficiently work with petabyte-sized datasets of structured data (tabular road, weather, and traffic data) and unstructured data (3D point clouds, 2D videos, radar scans, HD road graphs), how to reduce the time required to run data pipelines and iterate on ML models, and examples of tooling to accelerate computer vision and object detection model training. In this session, you will find out more about
Joey Zwicker is VP of AI Portfolio & Sales Strategy at Hewlett Packard Enterprise, where he leads all GTM and customer-facing functions in HPE’s AI-at-Scale business unit. Prior to this role, Joey was Co-Founder and COO of Pachyderm, which was recently acquired by HPE. Additionally, Joey is one of the creators and on the Board of Directors of the AI Infrastructure Alliance (AIIA). AIIA is a non-profit organization focused on bringing together leaders in the AI, Machine Learning, and MLOps space to help develop standards and interoperability across tools and practitioners that drive AI advancements forward.