Fireside chat featuring Mo Elshenawy, President and CTO of Cruise Automation, and Mohamed Elgendy, CEO and Co-founder of Kolena. In this discussion, Mo Elshenawy will delve into the comprehensive AI philosophy that drives Cruise Automation. He will share unique insights into how Cruise is developing its quality standards from the ground up, with a particular focus on defining and achieving “perfect” driving. This fireside chat offers valuable perspectives on the rigorous processes involved in teaching autonomous vehicles to navigate with precision and safety.

Natasha will be moderating a panel of leading VCs who have backed the top AI companies and understand the correction within the boom, flight to quality and what happens when OpenAI eats your lunch, how founders should think about giving big tech a spot on their cap tables, & generally how to invest at the speed of innovation right now.

Kolena CPO and CO-Founder, Gordon Hart, will discuss AI Quality Standards, how to establish gold standards, and how to create a framework to evaluate AI systems for performance rigorously.

Retrieval-Augmented-Generations (RAG) is a powerful technique to reduce hallucinations from Large Language Models (LLMs) in GenAI applications. However, large context windows (e.g. 1M tokens for Gemini 1.5 pro) can be a potential alternative to the RAG approach. This talk contrasts both approaches and highlights when Large Context Window is a better option thank RAG, and vice-versa.

Kodiak is on a mission to automate the driving of every commercial vehicle in the world. Today, Kodiak operates a nationwide autonomous trucking network 24x7x365, on the highway, in the dirt, and everywhere in between. We also release and deploy software about 30 times per day across this fleet that is not just mission critical, but also safety critical. Our AI development process must match this criticality and speed, providing fast engineering iteration while guaranteeing a high level of quality that is the requirement of safety. In this talk, we’ll share the details of that process, from how the system is architected, trained, and evaluated, to the validation CICD pipeline, which is the lifeblood of the development flywheel. We’ll talk about how we collect cases, how we iterate models, and how we do quality assurance, data, and release management - all in a way that seamlessly keeps our robots truckin’ across the US.