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Prueba de pensamiento sobre sistemas de IA

Asigne entradas de servicios de IA, dependencias, comentarios, cuellos de botella, fallas de límites, resultados de un extremo a otro y registros de versiones en todo el flujo de trabajo.

Rutas de guía relacionadasPensamiento de sistemas de IA
Pregunta 1 de 8

In an AI service, what makes a feedback loop?

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Las respuestas y explicaciones aparecen a medida que realiza el cuestionario.

  1. In an AI service, what makes a feedback loop?
    • A system output changes data or behavior that later returns as input
    • A model is saved to a backup drive
    • Two developers review the same code
    • A user closes a browser tab
  2. Which sequence best maps the complete path described in the guide?
    • Model, then interface only
    • Input collection, preprocessing, retrieval, model, tools or review, storage, and feedback
    • Training data, then model weights only
    • User account, billing, and logout
  3. Why should a team record the owner and failure behavior of each dependency?
    • To increase the model’s parameter count
    • To remove the need for monitoring
    • To know who is responsible and what happens when a component or boundary fails
    • To ensure every component uses the same programming language
  4. A workflow spends 40 seconds in review while retrieval and generation take 3 seconds combined. Where should a systems team investigate first?
    • The model’s training date
    • The logo shown in the interface
    • The number of model layers
    • The review bottleneck and how source presentation could improve it
  5. Why can recommendation exposure affect later system behavior?
    • User reactions to shown items can become future data
    • The interface changes the model’s source code automatically
    • A recommendation always reveals a user’s identity
    • Exposure prevents future model updates
  6. Which issue can create a wrong outcome without a model crash?
    • A clear ownership record
    • A missing field or outdated cache at a component boundary
    • A version number in a log
    • A reviewed source document
  7. What should an end-to-end check verify?
    • Only that a model endpoint returns a response
    • Only that the final screen loads
    • The user-visible result across the complete workflow
    • Only the number of retrieval documents
  8. What information helps trace a regression after a system change?
    • Only a screenshot of the home page
    • Una lista de todos los usuarios.
    • A model’s marketing name
    • Version information for the components involved