Learning to Inflate Tom Rudelius IAS Based on 1810.05159/hep-th - PowerPoint PPT Presentation

Jun 27, 2023 •363 likes •709 views

Learning to Inflate Tom Rudelius IAS Based on 1810.05159/hep-th Outline Machine Learning and hep-th Introduction to Inflation Learning to Inflate Algorithm Results Possible Next Steps Machine Learning and hep-th Machine

Learning to Inflate Tom Rudelius IAS Based on 1810.05159/hep-th
Outline • Machine Learning and hep-th • Introduction to Inflation • Learning to Inflate • Algorithm • Results • Possible Next Steps
Machine Learning and hep-th
Machine Learning ?
Machine Learning Works Best When… • Have clear measure of success
Example: Chess
Example: Self-Driving Cars
Machine Learning Works Best When… • Have clear measure of success • Have large, representative dataset on which to train
Example: Deciphering Digits
Example: Deciphering Digits
Advantages and Limitations of AI • When it comes to string theory, we don’t understand the large datasets very well • Known string vacua are likely small, biased sample • Don’t have a clear measure of “success” • Need to find problems suitable for machine learning: train a computer to do something we can already do and then do it “better” than we can • Inflation is nice in this regard because we have some experimental data, but more will come in. Best human models can explain data, but lack predictive power
Introduction to Inflation

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