Why do we learn?
A Summary of Wozniak's Concept of the Learn Drive.
Learntropy
- Underlies the Learn Drive
- Based on an analogy with Shannon Entropy
- Not to be confused with entropy in Physics.
- Can't help but include fact about Johnny Von Neumann telling Shannon to use entropy
- If the information coming from some source is perfectly predictable
- You are not surprised when you are told that
- If the information coming from some source is perfectly unpredictable
- Surprise based on
- 1950s with the cognitive revolution this was applied to the brain.
- Surprisal underlies the reward of the learn drive.
Nature
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Toddlers scan the environment for low probability components like colorful toys.
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Animals
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BIG link to the difference between information and meaning
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Complexity Melanie Mitchell
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Information processing
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Art of the Problem has an AMAZING series on information theory
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What should the unit of information be? Bits? Chunks (H.A. Simon)?
Importance of Learntropy
- Information is attractive to the brain based on its learntropy
- The measure of meaning must involve the brain itself in addition to the information channel metric. Prior knowledge is essential in learning.
Neural Processing
- Hippocampus
- New information compared with old knowledge.
- Compared for relevance, coherence and value.
- We immediately
- If the new infomation is low probability, it generates reward.
Wow Factor
- "Wow is how the brain responds to a sudden discovery"
- The entire purpose of the learn drive is to search for wow factors.
Information Processing
- Sensory information enters
- Processed.
- Scanned for surprisal.