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โ† ๐Ÿ’ป Technology ยท usually met in Std 8-12

Artificial intelligence

Programs that learn patterns from data rather than following rules written out by hand. Powerful, useful, and confidently wrong often enough to matter.

Traditional software does what a programmer specified. A machine learning system is instead shown many examples and adjusts internal numbers until its output matches them, after which it can handle cases it has never seen. Large language models work this way on text, predicting what should come next, which is enough to produce writing that reads well.

Two limits are worth knowing before trusting any of it. Such a system learns the patterns in its training data, including the mistakes and the biases, and it has no way of telling the difference. And a model that predicts plausible text can produce a confident, fluent, entirely invented answer โ€” which is exactly the kind of error a student checking homework is least likely to catch. Use it to explain and to check your reasoning, and verify anything that matters.

Worth knowing

  • Machine learning is a part of AI, and neural networks are one method within machine learning.
  • Garbage in, garbage out is not a joke here: data quality decides nearly everything.
  • An AI that scores well on a test may be matching surface patterns rather than understanding the subject.

Want to see it moving? Search YouTube for โ€œArtificial intelligenceโ€ โ†— โ€” we send you to the search rather than to one video, because a link to one video eventually rots.

See also

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Last gone through: 1 October 2026 ยท How these entries are written

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