S1, EP10 - AI4Science - Personal Thoughts and Perspectives

The Neil Ashton Podcast

This episode sets the scene for upcoming discussions on AI4Science with world renowned experts on machine learning. The focus is on using machine learning to solve scientific problems, such as computational fluid dynamics, weather modeling, material design, and drug discovery. The episode introduces the concept of machine learning and its potential to accelerate simulations and predictions. The episode also discusses the differences between machine learning for scientific problems and large language models, and the ongoing debate on incorporating physics into machine learning models.
Chapters
00:30 Introduction: AI for Science and Machine Learning
02:29 The Importance of Computational Fluid Dynamics
04:53 The Limitations of Physical Testing and Simulation
05:53 Accelerating Simulations and Predictions with Machine Learning
09:51 Data-Driven vs Physics-Informed Approaches in Machine Learning
13:10 The Future of Machine Learning in Science: Foundational Models