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What distinguishes artificial general intelligence from narrow AI?

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  1. What distinguishes artificial general intelligence from narrow AI?
    • Running on more expensive and powerful hardware
    • Broad ability to learn and perform across many domains
    • Having a physical robot body that moves in the world
    • Being trained exclusively on large image datasets
  2. What does Moravec's paradox observe?
    • AI progress stops once it matches average human intelligence
    • Larger models always become less accurate over time
    • Perception and motor skills, easy for us, are hard for AI
    • Computers can never beat humans at strategy games
  3. Which benchmark did François Chollet propose as a concrete way to measure skill-acquisition efficiency on abstract puzzles?
    • ARC (Abstraction and Reasoning Corpus)
    • MMLU (Massive Multitask Language Understanding)
    • GLUE (General Language Understanding Evaluation)
    • SQuAD (Stanford Question Answering Dataset)
  4. What is the 'intelligence explosion' hypothesis associated with I. J. Good?
    • Standard intelligence tests will soon become obsolete
    • AI hardware will physically overheat and fail at scale
    • The number of AI startups will keep growing exponentially every year
    • A self-improving machine could trigger runaway capability gains
  5. Rich Sutton's essay 'The Bitter Lesson' argues what about AI progress?
    • Symbolic rules crafted by experts will always outperform learning
    • General methods that scale with compute beat hand-built knowledge
    • Small curated datasets are always better than large ones
    • AI research should stop relying on GPUs and big clusters
  6. Why is the Turing test considered an incomplete criterion for AGI?
    • No machine has ever actually attempted to pass it
    • It only tests a machine's mathematical ability
    • It tests conversational imitation, not broad competence
    • It requires a physical robot body in order to pass
  7. Why does the guide say AGI discussions need an explicit definition?
    • Different proposed thresholds produce different claims about timing and capability
    • There is a single legal definition used worldwide
    • AGI means any system that generates text
    • A definition proves a system is safe
  8. A model performs well on several benchmarks. What conclusion does the guide support?
    • It proves the system can perform every cognitive task
    • It settles the AGI definition debate
    • It shows the model has human experience
    • Benchmark results are evidence about tested tasks, not proof of universally agreed AGI