Opportunities for Infusing Physics into AI - ML Algorithms

Explore the intersection of physics and artificial intelligence in this 36-minute conference talk by Animashree Anandkumar from the California Institute of Technology. Delve into neural programming, hierarchical learning, and the application of physics principles to AI algorithms. Discover how tensor frameworks and differential equations can enhance machine learning models. Examine real-world applications in autonomous systems, drones, and ground effect challenges. Learn about topic modeling, AWS services, and the role of machine learning in physics research. Gain insights into the latest developments in AI/ML algorithms and their potential impact on various fields, including art and media.

Intro
Neural Programming
Applications
Hierarchy
Rules
Expressions
Equations
Learning hierarchies
Examples
Frameworks
Modularity
Differential Equations
What else can we learn
Why use tensors
Examples of tensors
Correlations
Data Sets
Tensor Li Framework
Topic Modeling
AWS Service
Machine Learning for Physics
Autonomous Systems and Technology
Challenges for Drones
Challenges for Ground Effects
Demos
Nvidia
Art and Media