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Alex Kendall, founder and CEO of Wavye, discusses how their company is using AI to build autonomous vehicle technology. He shares insights into world models, improving decision-making, deploying autonomous delivery vehicles, the challenges of perception-based AI, and expanding AI technology to humanoid robotics.
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Quick takeaways
- World models use simulation to understand the implications of decisions, making them valuable for safety-critical applications like self-driving cars.
- Wave AI's Gaia world model leverages unsupervised learning and large-scale data to generalize across different environments, enabling deployment in autonomous vehicles and potential adaptation for humanoid robotics.
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Understanding the World Model
A world model is a function that predicts the next state of the world based on the current state and action. It acts as a simulator that allows for understanding how the world will evolve in response to different interactions. This model can be used to simulate the future and can even decode the state back into video. The advantages of world models lie in their ability to understand the implications of decisions, making them valuable for safety-critical applications like self-driving cars.
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