Guide-linked quiz · Hard Level
Artificial General Intelligence Quiz
Review the guide’s distinctions between narrow systems, disputed AGI definitions, capability claims, and limits of current evidence.
Question 1 of 8
What distinguishes artificial general intelligence from narrow AI?
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- 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
- 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
- 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)
- 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
- 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
- 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
- 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
- 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
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