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- **Title**: Logits: The Unbounded Voice of Neural Networks - **Reference**: Chat with Assistant, July 24, 2023 - **Main Idea**: Logits represent the unregulated, initial outputs of a neural network, capturing the raw sentiment of the network regarding its input before it's molded into more interpretable forms like probabilities. - **Body**: - At the core of a neural network's decision-making process are its neurons. When these neurons make preliminary decisions, they do so without the confines of boundaries. This unfettered expression is termed as logits. But why is such a free-ranging expression important? - 1. **Expansive Expressiveness**: Neural networks, by their nature, process vast amounts of information, seeking patterns and drawing connections. Logits provide these networks a space to initially articulate their findings without any constraints. Imagine a painter first sketching with charcoal on a canvas, free from the constraints of colors — that's the freedom logits offer. - 2. **Transition to Probabilities**: After articulating their raw thoughts as logits, neural networks then use activation functions to transform these values into forms that external entities can understand, like probabilities. This is similar to our painter filling in colors and refining the initial sketch, making it presentable. - 3. **Dynamic Range**: Because logits can span from negative to positive infinity, they inherently carry more information about the intensity and confidence of the decision. This dynamic range is crucial when determining the strength of patterns detected. - **Keywords**: Logits, Raw Output, Neural Decision-making, Dynamic Range, Transformation to Probabilities - **Linking to Other Notes**: Role of Activation Functions, Interpreting Neural Outputs, Confidence in Neural Decision-making