combined_Fundamentals of Azure AI Services_study guide Flashcards
What are the two main types of Azure AI service resources, and how do they differ?
The two main types of Azure AI service resources are multi-service and single-service. Multi-service resources provide access to multiple AI services with a single key and endpoint, whereas single-service resources provide access to only one AI service with its own unique key and endpoint.
Explain the purpose of an API in the context of Azure AI services.
An API (Application Programming Interface) defines the information that is passed between two software components, such as an Azure AI service and the application using it. APIs enable these components to communicate so that one can be updated without disrupting the other.
What are the three key principles that make Azure AI services readily usable for businesses?
Azure AI services are prebuilt and ready to use, accessed through APIs, and available and secure on Azure. This allows businesses of all sizes to integrate AI without significant development challenges or infrastructure investment.
Describe how Azure AI services can be customized to better fit specific requirements.
Some Azure AI services, like Vision, Speech, and OpenAI, can be customized by adding data to existing models to better fit specific requirements. This customization allows users to enhance the performance and accuracy of AI models for specialized use cases.
What is the role of the endpoint and key in accessing an Azure AI service?
The endpoint is the location or URL used to reach the AI service resource, and the key is a private string used to authenticate a request to access that resource and protect its privacy. Both are essential for API authentication.
How does the authentication process work when accessing an Azure AI service?
Authentication for Azure AI services involves verifying that the user or service has authorization to use the resource through an endpoint and resource key. The authentication header sends an authorization key to confirm the application’s permission.
What are some examples of the AI capabilities provided by Azure AI services?
Azure AI services offer capabilities such as generative AI (Azure OpenAI), image recognition (Azure AI Vision), natural language processing (Azure AI Language), and speech to text and text to speech (Azure AI Speech), among others.
How does the use of pre-trained models benefit users of Azure AI services?
The use of pre-trained models in Azure AI services allows users to quickly implement AI functionalities without the need for extensive data and training, saving time and resources while lowering the barrier to entry for utilizing AI in their applications.
Describe the process of associating an AI service resource with an Azure AI studio interface.
To associate an AI service resource with an Azure AI studio, navigate to the studio’s settings page, select the resource you want to use, and click “Use Resource”. This action connects the studio to the selected AI service resource.
How do Azure AI services contribute to accessibility and inclusivity in applications?
Azure AI services enhance accessibility through tools like Immersive Reader, which helps users read at their own pace, translate text, or view images for understanding. By offering these kinds of features, Azure AI is making technology more inclusive to diverse users.
