How Autonomous Vehicles Can Improve Generative AI Models
Summary
While AI has made many recent advances in its capabilities, the process of testing and validating model performance remains a problem to be solved for many generative AI products. Fortunately, in safety-critical situations (like autonomous driving) model testing and validation is as important as the end product itself! And there’s a lot the AV space can teach builders of generative AI products. In this session, Hussein Mehanna (SVP Head of AI/ML @ Cruise) shares their robust AI validation process at Cruise, from their principles for AI in AV testing and how to measure performance at the macro/micro & individual levels. You’ll learn how to use these principles as a framework for validating AI models in other industries - so that you can level up your generative AI models' performance and mitigate unexpected bias.
Speakers
Hussein Mehanna is the SVP of Artificial Intelligence at Cruise. He is an expert in AI with a passion for machine learning. He has over 15 years of experience and has successfully built and led AI teams at multiple Fortune 500 companies.
Prior to Cruise, Hussein led the Cloud AI Platform organization at Google. Under his leadership, his team revamped the product line and rebuilt the organization. Cloud AI Platform became Cloud AI's fastest growing product segment. Before Google, Hussein worked at Facebook where he co-founded the Applied Machine Learning group that combined applied research in machine learning and advanced platforms. He helped democratize artificial intelligence with more than 2000 engineers using the technologies, and his team added billions of dollars of revenue.
Hussein has a Masters in Computer Speech, Text and Internet Technology from the University of Cambridge and a Bachelors of Science in Computer Science from Ain Shams University.