Why Azure Cognitive Services?

The Azure Cognitive Services suite of tools will help your organization quickly implement artificial intelligence (AI) solutions to do the following:

• Improve operational efficiencies by reducing the touchpoints within workflows that require human intervention with the use of robotic process automation and related activities.
• Provide predictive capabilities, helping to drive supply chain efficiencies in either reducing unneeded stock overages or avoiding stock outages that would drive customers to a competitor.
• Augment human capabilities in the way of quality standards and transactional interactions where large volumes of information are being handled, oftentimes too quickly for a human to monitor all the details efficiently.
• Improve the customer experience by automating services that would traditionally require human intervention, using chatbots embedded into applications customers interface with, and monitoring call center activities...

Exploring the history of Azure Cognitive Services

There are countless cases of AI being implemented within organizations or broader society at large, and the overall topic of AI is really nothing new. Since the mid-1950s, scientists have been working on various ways to replicate the inner workings of the human brain to teach computers how to "think" on their own and perform tasks with the same efficiency as humans. Through many starts and stops of funding and support, progress has been made with various methodologies. With the introduction of cloud computing in the late 2000s with virtually limitless amounts of processing power, memory, optical networks, and solid-state disk drives, applications of AI have exploded for both corporate and personal use within software, smartphones, and many other uses.

Today, the three major public cloud vendors are Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). They are listed in order of market share in terms...

Exploring Azure Cognitive Services

In this section, we will outline each of the services and the categories they fall into. Each of the services is built with the intent of helping to alleviate the requirement to build such a feature into an existing application and all the cost and time implications as a result. Many of the services help to enhance the solution they are being tied to, and some can add revenue to the top line of your organization.

So, without further ado, let's jump in!

Decision

The first category we will explore when discussing Azure Cognitive Services is the Decision category. When we think about the Decision category, we should focus on how Microsoft describes the category function as "Build apps that surface recommendations for informed and efficient decision-making."

The Decision category is the most recent category added by Microsoft as they continue to invest in the Cognitive Services suite of tools. This category was developed to...

Reviewing past and future investments

With the explosion of AI among enterprises, Microsoft's investment in their Cognitive Services suite started back in 2015 with Project Oxford. At the Microsoft Build conference (typically targeted at developers) that year, it was announced that this new set of ML-based REpresentational State Transfer (REST) API and SDK tools were being built. There have been many directional changes and iterations of deployments, but the majority of the services released back then are still being used today. The only major difference is the approach to Face APIs, as discussed briefly in the last section.

Updates

Microsoft maintains a blog for notable changes to Azure and tags articles based on technology. Cognitive Services-specific articles are tagged and can be found here in their complete form: https://azure.microsoft.com/en-us/blog/topics/cognitive-services.

Later on, the Azure updates blog was announced and articles about new services and features...

Summary

In this chapter, we discussed the current offerings of Cognitive Services from Azure, with an explanation of how each of the services can be used. We explored many examples from various industries and practical applications of the services that hopefully set a foundation for ways the services can be used. Although not all services are covered, later chapters in this book will give a deep dive into actual implementation steps for deploying the services and building use cases. The complete examples will help provide context for the use case that you want to build and help provide the best possible value for your organization.

These services change frequently. Many will have features added and dropped or enhanced and deprecated. This is the nature of technology and, largely, those decisions are made based on the value of the offering. Commonly, the services will be looked at based on the adoption rate compared to other services and how expensive it is to maintain. Be mindful...