The Neil Ashton Podcast
AI for Science — Personal thoughts and perspectives
Episode overview
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
Transcript
A public transcript is not currently available for this episode.