quiz bu lëkkale ak tegtal · Diggante Niveau

Quiz de réglage de jouer sa bopp

Saytu fowokaayu sa bopp ci Go ak tàggat modelu làkk, méngale AlphaGo Zero ak AlphaZero, ba noppi xoolaat siñaal done yu fiks ak risku done synthetik.

Yooni njiit yu jëm ciAccordage bu baax ci jouer sa bopp
Laaj 1 de 8

Ban sistem bu siiw moo yegg ba yegg ci Go play bu ëpp nit, di jëfandikoo self-play rek te amul benn dokimaa ci jeu nit?

Xoolaatal laaj bu nekk8 laaj

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

  1. Ban sistem bu siiw moo yegg ba yegg ci Go play bu ëpp nit, di jëfandikoo self-play rek te amul benn dokimaa ci jeu nit?
    • AlfaGo Zero
    • Baxa bu xóot
    • Watson
    • GPT-2
  2. Ci SPIN, lan mooy liggéeyu 'konno' bi model bi wara daan?
    • Benn xeetu neexal buñ tàggat ci nit
    • checkpoint bi njëkk ci model bi ak tontu yi mu defar
    • Generatëru mbind ci anam wu bari
    • Tokenisatër bi
  3. Lan mooy njariñu self-play ci wàllu njariñu done?
    • Dafay laaj ab done nit bu bees ci rond bu nekk
    • Dafay dox ludul ci done yu amul àpp
    • Mën na génne benefiis yu bari ci benn done bu takku te du am etiketu nit bu bees
    • Soxlawul benn model
  4. Ci mébetu tàggat yaram bu SPIN, lan lañuy puus model bi mu def?
    • Dafa taamu tontu yu boppam defar moo gën royuwaayi nit
    • Bàyyi bépp done bu nit
    • Memoriser ensemble test bi
    • Jox tontub royuwaayu nit ñi gëna am wërsëg moo gën ay génnam yu njëkk
  5. Which pair of games did the AlphaZero paper demonstrate beyond its Go experiments?
    • Chess and shogi
    • Poker and bridge
    • Checkers and Othello
    • Atari and StarCraft
  6. What risk did researchers report when language models are recursively trained on generated data?
    • Model collapse, with loss of diversity and representation of the original distribution
    • Guaranteed monotonic improvement at every iteration
    • Automatic prevention of distribution shift
    • A higher count of verified human labels
  7. What search component does AlphaGo Zero use alongside self-play?
    • A nearest-neighbor lookup over human game records
    • A language-model tokenizer
    • Monte Carlo tree search guided by a policy and value network
    • A fixed list of opening moves
  8. Why can automatic checkers be useful in self-play for math or code tasks?
    • They guarantee that a model never learns incorrect strategies
    • They replace the need for a task specification
    • They make all generated examples independent of the model
    • They can verify generated solutions without requiring a new human label for each attempt