ABOUT THIS EPISODE
Guest: Campbell Watson, Senior Research Scientist at IBM Research
As artificial intelligence, or AI, continues to become more pervasive in our technology, it’s only natural to wonder what it means for meteorology and climatology. Believe it or not, AI is already revolutionizing how we develop models in the Earth and Space sciences. Joining us today is Campbell Watson, a Senior Research Scientist at IBM Research, to discuss how we are creating these AI models, and the opportunities and advancements we hope to learn from using them.
Chapters
- 00:00 Introduction to AI in Meteorology and Climatology
- 01:35 Campbell Watson's Background and Interest in Weather
- 04:18 The Use of AI in Weather Forecasting
- 05:24 The Evolution of AI in Weather Forecasting
- 06:26 Understanding AI at its Core
- 08:09 Difference Between AI and Conventional Weather Model Forecasting
- 10:44 The Difference Between AI and Conventional Weather Model Forecasting
- 13:31 AI Models Learning from Weather Models
- 20:30 Foundation Models and Unsupervised Learning
- 25:12 Verification of AI in Weather Forecasting
- 27:57 The Robustness of AI Models
- 28:24 Learning from Observations
- 29:23 AI Models Learning from Observations
- 30:09 The Importance of Observations
- 30:38 Comparing Deep Learning and AI with Traditional Weather Forecasting Models
- 35:38 Trustworthiness in AI Forecasting
- 36:12 Adopting AI in Weather Forecasting
- 41:46 Nowcasting with AI
- 44:03 AI in Climate Forecasting
- 47:38 The Future of AI in Weather Forecasting
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English
United States
IN THIS EPISODE
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