Kedis ku xidhan hagaha · Dhexdhexaad Heerka

Kediska Jiilka Code Poolside AI

Dib u eeg moodooyinka koodka Poolside, jawaab celinta fulinta, hawlgelinta ganacsiga, baaxadda moodeelka, iyo sheegashooyinka gaarka ah ee bartilmaameedka. Hubi waraaqaha iyo baaxadda

Wadooyinka haga ee la xidhiidhaAbuurista koodhka AI ee barkadda
Su'aal 1 ee 8

Waa maxay farsamada tababarka aasaasiga ah ee Poolside loo yaqaan?

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  1. Waa maxay farsamada tababarka aasaasiga ah ee Poolside loo yaqaan?
    • Xoojinta Barashada Jawaab-celinta Fulinta Xeerka (RLCEF)
    • Tababarka kahor ee aan la ilaalin ee saafiga ah GitHub kaliya
    • Xoojinta bini'aadamka oo laga baranayo qiimeynta sheekada
    • Barnaamijyada hidaha oo aan lahayn shabakado neerfaha
  2. What do Poolside’s Laguna models target?
    • Image segmentation only
    • Agentic software development and code-generation tasks
    • Consumer finance scoring
    • Audio transcription only
  3. Maxay Poolside ku nuuxnuuxsatay macaamiisha ganacsiga?
    • Helitaanka API dadweynaha ee bilaashka ah ee qof kasta
    • Kaliya barnaamijyada mobilada ee macaamiisha
    • Gelin gaar ah iyo goob-guri ah si kood uu guriga u joogo
    • U iibinta xogta isticmaalaha xayaysiiyayaasha
  4. What should a reader use to assess Poolside’s reported benchmark scores?
    • A general claim that one model is best
    • Parameter count alone
    • A social-media post without methodology
    • The model/version, benchmark setup, and evaluation source stated with the result
  5. Waa maxay sababta jawaab-celinta fulinta kood ay aad ugu qiimo badan tahay tababbarka qaabka kood?
    • Saxnimada si toos ah ayaa loo eegi karaa, iyada oo dhalinaysa calaamado abaal-marin ah oo la qiyaasi karo iyada oo aan lahayn calaamadeeyayaal bini'aadam ah
    • Waxay ka dhigaysa moodelku inuu si degdeg ah u socdo marka la eego
    • Waxay meesha ka saaraysaa baahida GPU-da kasta
    • Waxay dammaanad qaadaysaa in moodelku aanu waligii khalad samayn
  6. What context lengths does the Laguna M.1/XS.2 technical report describe for continued pre-training?
    • 2K and 4K tokens only
    • 32K and 128K token sequence lengths
    • 1M and 2M tokens in every released model
    • 30 and 60 seconds of generated code
  7. Which framework does Poolside cite for the Laguna M.1/XS.2 agentic benchmark evaluations?
    • Xabbad
    • ImageNet
    • The Laude Institute’s Harbor Framework
    • Gurguurashada caadiga ah
  8. What should an enterprise review before deploying a code model?
    • Kaliya magaca modelka
    • Whether the UI uses a dark theme
    • A benchmark score alone
    • Data handling, access controls, model terms, and evaluation on its own repositories