Microsoft’s Cognitive Services, powered by machine learning, are an easy way to add artificial intelligence to your apps, offering pay-as-you-go access to a selection of useful algorithms. Unlike many other web services, they’re continuously evolving, improving as they ingest more and more labeled data.
That’s an important difference between machine learning and other, more familiar, algorithms. As Microsoft improves its training and models, the scope of the services continues to get better, along with responsiveness and accuracy. Some can even take advantage of a process called Transfer Learning, where training a model with one set of data improves its performance with another.
Continuous improvement isn’t the only benefit of the research work Microsoft puts into its Cognitive Services. Cognitive Services operationalize that research, delivering new tools and services as research moves from the lab into commercial products. What matters here is the transition between preview and general availability, as Azure and Microsoft Research work together to take what was pure research and turn it into tools you can include in your applications.
Microsoft has been able to containerize some of its Cognitive Services for use on Azure’s Edge servers and on any other platform that supports Docker. Instead of pushing data to the cloud over low-bandwidth links, you can process data locally, as part of an IoT Hub instance, sending only the information that matters to other applications or to administrators.