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Aura Academy

Section 1 · Foundations

AI, machine learning and deep learning

Artificial intelligence is the broad field. Machine learning learns patterns from data; deep learning uses layered neural networks to learn representations. A useful product is a larger system around any model.

Beginner20 minutes

By the end, you can

  • Distinguish AI, machine learning, deep learning, a model and a complete system.
  • Recognize supervised, self-supervised and reinforcement learning.
  • Choose a baseline before reaching for a large model.

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Concept 1 / 5

AI is a field, not one technology

AI includes rules, search, planning, optimization, probabilistic methods, machine learning and hybrids. The simplest adequate method is often the most reliable.

Common confusions

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  • Calling every automation “AI” hides whether the system follows rules, searches, predicts or learns.
  • A benchmark score does not guarantee performance on your users, language, data or failure modes.
  • AGI and ASI are debated capability goals, not proven properties of current general-purpose models.

Keywords to know

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  • AI
  • algorithm
  • model
  • data
  • parameter
  • training
  • loss
  • gradient
  • generalization
  • overfitting

Primary and authoritative sources

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Deep Learning bookOpen reference by Goodfellow, Bengio and Courville on machine learning and deep learning foundations.NIST AI Risk Management FrameworkAuthoritative framework for governing, mapping, measuring and managing AI risks.
Next: How LLMs work