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Gemini 모델, 앱, API 및 클라우드 배포의 역할과 기능 가용성, 다중 모드 평가 및 데이터 제어를 검토합니다.
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Which distinction does the guide make about Gemini?
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- Which distinction does the guide make about Gemini?
- Gemini models, the Gemini application, and developer tools have different roles
- All Gemini services expose identical features
- A model name guarantees every tool is enabled
- The consumer app is the same thing as a cloud deployment
- A feature appears in the Gemini consumer app. What should a developer do before relying on it through an API?
- Assume the same feature is exposed in the API
- Rely on an old product announcement
- Check the relevant API documentation and project availability
- Use the feature name in a prompt
- Why should model and feature availability be checked for the intended project?
- All projects share identical quotas
- Quotas and access can vary by model, endpoint, account, or region
- Availability depends only on how many prompts are written
- A consumer app’s feature list controls every API
- What should a developer review before sending private material to a Google AI service?
- Only whether the project uses the largest model
- Assume a consumer app’s privacy settings apply to every developer project
- Assume no request data is retained whenever training use is disabled
- Review data terms and retention controls for the chosen API service
- A report image contains a small footnote. What should a developer account for when using a multimodal model?
- The model may miss fine text; input quality and resolution can affect what it reads
- The API verifies every number against the original report automatically
- The image-processing step guarantees every visible word becomes a model input
- Repeating the same prompt ensures that all small text will be recognized
- Does retrieval or search support remove the need to verify an answer?
- Yes; retrieval guarantees every claim
- Only if the source is official
- No; check the final claims against the sources
- Yes, if the answer includes links
- What does a model capability establish about a specific app workflow?
- That the feature is automatically enabled everywhere
- Only potential capability; account permissions and enabled features also matter
- That the complete workflow has been tested
- That data controls are identical
- What should be recorded when evaluating a Google AI configuration?
- The company name without its model or endpoint
- Only the final answer produced in one successful run
- The project name without the selected model and settings
- The model, project settings, inputs, and evaluation date