An AI model must study all available examples of a concept. The AI model must not make assumptions about how a concept is created. The AI model must learn from real data, not from guesses.
By Pawan Nayar · from the LLOS AI Learning record
An AI model must study all available examples of a concept.
The AI model must not make assumptions about how a concept is created. The AI model must learn from real data, not from guesses.
An AI model learns best by studying many examples. The AI model should look at all the different ways a concept is made. If the AI model only sees a few examples, it might guess how the rest are made. This can lead to wrong answers. The AI model needs to see the full range of possibilities.
A developer asks an AI model to create 'expressive shapes'. The AI model has only seen simple circles and squares. The AI model assumes all expressive shapes are variations of these. The AI model fails to create complex, unique shapes because it did not study a wide range of examples.
Resolved from this lesson's own record — real definitions, not invented for this page.
More from the same record, pulled by shared topic — not written new for this page.
A new way of writing or a new concept must be shown in an example. The example acts like a teacher.
An AI model must study all available examples of a concept. The AI model must not make assumptions about how a concept is created. The AI model must learn from real data, not from guesses.