Guide-yakabatana mibvunzo · Zviri nyore Nhanho
Amazon AI Quiz
Inosiyanisa Amazon's AI masevhisi uye mabasa ekugadzirisa, anosanganisira kuwana modhi, matunhu, kuyerera kwedata, uye mutengo wekushandisa.
Mubvunzo 1 ye 8
Amazon Bedrock inosiyana sei neAmazon SageMaker AI padanho repamusoro?
Tarisa mubvunzo wese8 mibvunzo
Mhinduro uye tsananguro zvinoonekwa paunenge uchitora bvunzo.
- Amazon Bedrock inosiyana sei neAmazon SageMaker AI padanho repamusoro?
- Bedrock offers managed access to foundation models, while SageMaker AI supports building, training and deploying models
- They are identical products with different names
- Bedrock is a physical GPU and SageMaker is a database
- SageMaker AI is Amazon’s home voice assistant
- Chii chinofanira kuwonekwa nemugadziri asati avimba neBedrock modhi chimiro?
- That every foundation model is available in every region
- That the model and feature are available for the account, region and chosen configuration
- That the feature works without permissions
- That model access guarantees a particular output quality
- Ndechipi chirevo pamusoro pekubata data paAWS AI masevhisi anotsigirwa negwara?
- A managed service removes every data responsibility
- All AWS services use one identical data policy
- Storage, logging, retrieval and model calls can have separate controls to review
- Permission settings never affect model requests
- Ko kushandisa yakachengetedzwa AI sevhisi inoshandura chii kune muridzi weapp?
- It guarantees legal compliance for every workflow
- It removes the need to validate model outputs
- It means no application configuration is needed
- It reduces some infrastructure work but does not remove responsibility for authorized access and data use
- Ndeipi rekodhi rekodhi inobatsira kuburitsazve AWS AI ongororo?
- The endpoint, model version and configuration used
- Only the service’s marketing name
- The user’s browser theme
- A copy of unrelated training logs
- What should a team include when comparing the cost of an AWS AI workflow?
- Only the model’s parameter count
- Storage, data transfer, failures, throughput and operational behavior
- Only the first successful request
- The number of tabs open in the console
- Why can a model offered through Bedrock differ operationally from using its provider’s direct API?
- The underlying model name makes all terms identical
- Bedrock guarantees the provider’s exact interface
- The managed platform can have different integration details, access conditions and configuration
- Using a managed endpoint removes model versioning
- Before production rollout, which test best follows the guide’s service-selection advice?
- Assume the public feature list applies to every account
- Test only a model’s training accuracy
- Skip tests if the service is managed
- Evaluate representative tasks and failure handling in the intended account and region