Microsoft’s Azure Machine Learning platform faces off against IBM’s Watson

Microsoft's Azure Machine Learning platform faces off against IBM's Watson

IBM’s Watson made headlines when it debuted and later performed on Jeopardy. Now Microsoft is debuting a platform of its own with the Azure Machine Learning (Azure ML) platform. IBM’s Watson is great for those that like programming and dealing with highly technical stuff to get things the way they want, but it’s not ideal if you are an everyday developer. Microsoft’s Azure ML platform promises to be friendlier to the general developer.

Ron Adir, the strategic innovation lead of Microsoft Israel’s enterprise & partners group, explains: “General developers are definitely part of Microsoft’s plans for Azure Machine Learning. Microsoft wants to democratize the idea of machine learning, connecting it to our other services via the cloud and enabling developers to integrate it into their apps as they would with an API.”

Microsoft plans to develop the Azure ML platform to create data models that can be used directly with apps that analyze data and turn it into information that can be readily available to the user. General developers would benefit greatly from most of the information that is created from Microsoft’s Azure ML platform by being able to use that information to create better apps for more devices.

Microsoft's Azure Machine Learning platform faces off against IBM's Watson

For example, a predictive data model would look at information that is collected by sensors, and based on weather conditions, location, time of day, heart rate and many other factors and depending on the app, make suggestions to the user to make their lives more efficient or healthier based on the findings collected by the sensors.  

One particular instance where Azure’s ML platform is working particularly well is with the Microsoft Band. Ron expands on how the Microsoft Band benefits from using the Azure ML platform:

“The [Microsoft] Band includes a prebuilt data model that uses its sensors to provide information to the wearer, not only providing accurate information about heartbeat, physical activity, calorie burn, and sleep quality, but also analyzing the data to provide insights about how to improve health, lose weight, or whatever the goal would be. [It’s about] how to get from point A to point B in an intelligent, personalized manner, understanding all the factors involved and providing answers to real-life questions.”

These are some of the same things that IBM’s Watson can do, but Microsoft’s Azure ML platform “is accessible to everyone, not just experts,” according to Ron, “we have an ambitious platform: we are ready to work with anyone and everyone that wants to add some intelligence to their apps. We really want this to be an intelligence engine that will work with everything, and Microsoft Health is a good place to start.”

Hopefully, Microsoft’s new Azure ML platform will overtake IBM’s Watson sometime soon, but it looks like Azure ML is already well on its way. 

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