📢

Why Neural Networks Generalise, and Why They Are (Kind of) Bayesian

📅 2020
public awareness
⚪ Common
#ai #lottery ticket hypothesis

📖 Description

Currently, we do not have a good theoretical understanding of how or why neural networks actually work. For example, we know that large neural networks are sufficiently expressive to compute almost any kind of function. Moreover, most functions that fit a given set of training data will not generalise well to new data. And yet, if we train a neural network we will usually obtain a function that gives good generalisation. What is the mechanism behind this phenomenon?

📊 Game Impacts

Variable Change Condition
Research +5 Always
Vibey Doom +2 Always
Ethics Risk -5 Always

💭 Reactions

🔬 Safety Researcher Reaction: ⚠️ Placeholder - Needs Real Quote
"Adds to our knowledge base"
📰 Media Reaction: ⚠️ Placeholder - Needs Real Quote
"Discussed in AI safety community"
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🔗 Sources

🏷️ Event Metadata

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⭐ Rarity ⚪ Common → Suggest different rarity
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