Map the AI · Daily learning
One small lesson. One step forward.
Learn how AI handles text and generates answers through a short experiment and a question. Open the linked tutorial to explore further.
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AI Literacy
Understand what AI is, how it works, and where it fails — without writing a line of code.
The full track uses the existing knowledge graph. Short-lesson mastery currently covers the foundation units below.
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When errors cancel each other
Compare signed error with squared error.
A loss function measures how predictions differ from targets. Positive and negative errors can cancel when averaged. Squaring each error before averaging prevents this cancellation. Mean squared error is one possible loss; the right choice depends on the task.
Both handcrafted examples have target 2. Adjust the predictions and compare two ways to measure error.
Mean signed error: 0.00
Mean squared error: 4.00
Try predictions 0 and 4, then set both to 2. Zero squared error means these two examples are correct; it does not guarantee correct predictions on new data.
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