Provision An Azure AI Services Resource

By Ashwin Venugopal -

 




About

Azure AI Services is a set of services that you can use into your apps as building blocks of AI capabilities. Cloud-based services that incorporate AI capabilities are called Azure AI services. You should consider AI services as a collection of separate services that you can use as building blocks to create complex, intelligent applications rather than as a single solution.

Azure AI services include:

  • Azure AI Document Intelligence - An Optical Character Recognition (OCR) solution that can extract semantic meaning from forms, such as invoices, receipts, and others.

  • Azure AI Immersive Reader - A reading solution that supports people of all ages and abilities.

  • Azure AI Search - A cloud-scale search solution that uses AI services to extract insights from data and documents.

  • Azure OpenAI - An Azure Cognitive Service that provides access to the capabilities of OpenAI GPT-4.

Provision an Azure AI Services Resource

Azure AI services include a wide range of AI capabilities that you can use in your applications. In order to utilize any of the AI services, you must set up the necessary resources in an Azure subscription to specify an endpoint where the service can be used, supply access keys for verified access, and handle invoicing for the use of the service by your application.

Options For Azure Resources

For many of the available AI services, you can choose between the following provisioning options:

  • Multi-Service Resource- An AI services resource that supports several distinct AI services can be provisioned. With this method, you may use a single point of invoicing for all service usage and manage a single set of access credentials to use numerous services at a single endpoint.

  • Single-Service Resource- It is possible to provide each AI service separately. With this method, you may maintain access credentials for each service separately and utilize different endpoints for each service. Additionally, it allows you to handle each service's billing independently. Single-service resources are an excellent option to test a service before utilizing it in a production application because they typically offer a free tier (with usage constraints).

  • Training and Prediction Resources- Some AI services offer (or require) different resources for model training and prediction, although the majority can be used with just one Azure resource. In most situations, this allows you to use a dedicated service-specific resource to train a model and a generic AI services resource to make the model available to applications for inferencing. It also allows you to manage billing for training custom models independently from model consumption by applications.

Conclusion

We have successfully learnt about provisioning an AI Service resource.

 

 

 

 

 

 



















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