AI systems can be classified by their capabilities — from simple reactive machines that respond to immediate input, to hypothetical self-aware systems. Arend Hintze's taxonomy (2016) is widely used: Reactive, Limited Memory, Theory of Mind, and Self-Aware.

Key Points

  • Type 1 — Reactive Machines: no memory, respond to current input only (Deep Blue chess engine)
  • Type 2 — Limited Memory: learn from historical data, most ML models fall here
  • Type 3 — Theory of Mind: can understand emotions and intentions — not yet achieved
  • Type 4 — Self-Aware: conscious AI — theoretical, does not exist
  • Alternative classification: Weak/Narrow AI vs Strong/General AI
  • Current state of the art: we are firmly in Type 2 territory (Limited Memory)
TypeMemoryLearningStatusExample
Reactive MachinesNoneNoneExistsIBM Deep Blue
Limited MemoryShort-termFrom dataExistsChatGPT, Tesla Autopilot
Theory of MindFull contextSocial/emotionalResearchNone yet
Self-AwareFullMeta-learningTheoreticalScience fiction

Real-World Example

Self-driving cars use Limited Memory AI — they learn from vast amounts of driving data and store relevant information about the current road situation, but they do not have a persistent understanding of the world over time.