Cars, aeroplanes, and quantum physics: Why complexity makes life simpler for the vibration engineer

Professor Robin Langley

• 18:00 - 19:00 Bristol-Myers Squibb Lecture Theatre, Cambridge Lent Term G.I. Taylor Lecture Booking Recommended

One of the many outstanding achievements of G I Taylor was the discovery of relatively simple statistical laws that apply to highly complex turbulent flows.  The emergence of simple laws from complexity is well known in other branches of physics, for example the emergence of the laws of heat conduction from molecular dynamics.  Complexity can also arise at large scales, and the structural vibration of an aircraft or a car can be a surprisingly difficult phenomenon to analyse, partly because millions of degrees of freedom may be involved, and partly because the vibration can be extremely sensitive to small changes or imperfections in the system. In this talk it is shown that the prediction of vibration levels can be much simplified by the derivation and exploitation of emergent laws, analogous to some extent to the heat conduction equations, but with an added statistical aspect, as in turbulent flow. The emergent laws are discussed and their application to the design of aerospace, marine, and automotive structures is described.  As an aside it will be shown that the same emergent theory can be applied to a range of problems involving electromagnetic fields. 

Building Embodied Intelligence: Insights from Wayve’s Journey in Autonomous Driving

Alex Kendall

• 18:00 - 19:00 Bristol-Myers Squibb Lecture Theatre, Cambridge Lent Term Honorary Fellows Lecture

Today, the world is captivated by cognitive AI applications such as large language models. But what will it take to bring the benefits of AI into the messy, diverse and safety-critical physical world? Robotics and autonomous systems must deal with open-ended environments, irreversible physical actions, and deployment economics that look very different from pure software.

In this talk, I will outline the frontier challenges and opportunities in embodying AI in the real world, drawing on our journey building Wayve. Originating from research on deep learning for scene understanding at the University of Cambridge, Wayve has spent the last decade developing Embodied Intelligence for autonomous driving. Our technology has been demonstrated across more than 500 cities in Europe, North America and Asia, and will soon be deployed with major automakers such as Nissan and fleet partners like Uber.

I will share the key technical ideas, system-level lessons, and open problems that must be solved to make Embodied AI a safe, scalable and economically viable reality.