Listen "Episode 009: Optimization Pt. 1"
Episode Synopsis
In this episode, Lloyd and Geoff delve into the nature of optimization problems in mathematics and their role in Artificial Intelligence. They then discuss the concept of reimagining one's life as a convex optimization problem.
Episode Guide:
1:55 - Introduction to Optimization
9:02 - The Role of Optimization in AI Systems
14:21 - Exploring via Gradient Descent
17:53 - Imagining Life as a Convex Optimization Problem
21:58 - The Parameterization of Happiness
24:55 - The Fractal Nature of Entropy
26:32 - Happiness, Utility, and Attention
32:28 - Questioning the Model
36:34 - A Discussion on Decision Fatigue
39:25 - Properly Scoping the Optimization Problem
48:10 - The Utility of the Expected Value Framework
More Info:
Visit us at aiexperience.org
Brought to you by ICED(AI)
Hosts - Lloyd Danzig, Geoff Johnson
Episode Guide:
1:55 - Introduction to Optimization
9:02 - The Role of Optimization in AI Systems
14:21 - Exploring via Gradient Descent
17:53 - Imagining Life as a Convex Optimization Problem
21:58 - The Parameterization of Happiness
24:55 - The Fractal Nature of Entropy
26:32 - Happiness, Utility, and Attention
32:28 - Questioning the Model
36:34 - A Discussion on Decision Fatigue
39:25 - Properly Scoping the Optimization Problem
48:10 - The Utility of the Expected Value Framework
More Info:
Visit us at aiexperience.org
Brought to you by ICED(AI)
Hosts - Lloyd Danzig, Geoff Johnson
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