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관련 가이드 경로AI 미래
질문 1 의 8

유용한 AI 예측에는 무엇을 명시해야 합니까?

모든 질문 미리보기8 질문

퀴즈를 풀면 정답과 설명이 나타납니다.

  1. 유용한 AI 예측에는 무엇을 명시해야 합니까?
    • 가정, 기간 및 증거
    • 확신에 찬 결론만
    • 글을 쓰는데 사용된 모델
    • 불확실성에 관계없이 정확한 출시일
  2. A controlled benchmark improves. What does that establish about widespread product adoption?
    • That all organizations can deploy it now
    • That infrastructure and maintenance are solved
    • Not when or how widely adoption will happen by itself
    • That future reliability is guaranteed
  3. Why use faster, slower, and uneven-progress scenarios?
    • They identify which forecast is guaranteed
    • They make planning robust when progress is uncertain across tasks
    • They eliminate the need for indicators
    • They convert a scenario into a probability
  4. Which indicator better updates a capability assessment than a launch announcement?
    • A company product announcement alone
    • A funding round
    • A marketing forecast
    • Independently reproduced task performance and sustained reliability
  5. Why record a forecast and what would count as a miss?
    • To ensure the forecast becomes correct
    • To keep the prediction secret
    • To assess it against the stated outcome without changing the definition afterward
    • To avoid updating assumptions
  6. What does uneven capability growth imply?
    • Progress on one benchmark does not prove the same progress in other domains
    • Every task improves at the same rate
    • One benchmark predicts physical interaction reliability
    • A capability cannot be measured
  7. What is a robust decision under multiple plausible futures?
    • One that depends on the fastest forecast being correct
    • A decision made only after certainty arrives
    • One that has no current evidence
    • One that remains useful across several scenarios
  8. Why review forecasts over time?
    • Forecasts become facts after publication
    • New evidence can update an assessment and reveal whether prior predictions were calibrated
    • Predictions should never change
    • A later review hides the original assumptions