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On episode #152 of Eye on AI, Craig Smith sits down with Alex Kendall, founder and CEO of Wavye, a company building autonomous vehicle technology using AI.

In this episode, Alex provides an inside look at Wavye's approach to autonomous driving, which leverages world models and reinforcement learning to create an AI "driver" that can understand complex urban environments. Alex explains how world models allow an AI system to imagine multiple futures before acting, enabling safer decision-making, and shares Wavye's progress on deploying autonomous delivery vehicles with partners in the UK.

We also dive into the differences between world models and large language models, the unique data challenges of perception-based AI, and Wave's ambitions to expand this AI technology to new applications like humanoid robotics.

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Craig Smith Twitter: https://twitter.com/craigss

Eye on A.I. Twitter: https://twitter.com/EyeOn_AI

(00:00) Preview, Introduction and Netsuite

(03:45) The Advantages of World Models

(10:12) Developing Autonomous Driving Technology

(16:35) Partnership with Microsoft and Training Challenges

(21:10) Decoding the Concept of Generalization in Autonomous Driving

(27:08) Compute Requirements and Infrastructure

(32:45) The Role of Azure in Training

(37:12) What Is Tokenization of Data

(41:47) Addressing Compute Constraints

(46:12) Future Applications of World Models and Open Source