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1
Intro
2
Neural Programming
3
Applications
4
Hierarchy
5
Rules
6
Expressions
7
Equations
8
Learning hierarchies
9
Examples
10
Frameworks
11
Modularity
12
Differential Equations
13
What else can we learn
14
Why use tensors
15
Examples of tensors
16
Correlations
17
Data Sets
18
Tensor Li Framework
19
Topic Modeling
20
AWS Service
21
Machine Learning for Physics
22
Autonomous Systems and Technology
23
Challenges for Drones
24
Challenges for Ground Effects
25
Demos
26
Nvidia
27
Art and Media
Description:
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.

Opportunities for Infusing Physics into AI - ML Algorithms

APS Physics
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