When comes to machine learning and artificial intelligence, it’s no longer a question of how to deliver it. The question now is how to get developers and enterprises to use AI and machine learning.It’s not been long since machine learning was the province of research labs. In fact, the first time I talked to Microsoft about its deep-learning machine learning work was a conversation about that basic research back in 2014 with Peter Lee, now Microsoft Research’s leader for AI.[ Go deep into machine learning at InfoWorld: 11 must-have machine learning tools. • 13 frameworks for mastering machine learning • Machine learning pipelines demystified • Review: 6 machine learning clouds • Which Spark machine learning API should you use? ]
Back then, Skype Translator and Cortana were Microsoft’s first machine learning-powered applications. Now, machine learning tools are everywhere, with Azure’s machine learning platform the flagship service and the Cognitive Services Toolkit a quick on-ramp to machine learning, with prebuilt models for common scenarios like image recognition. Those same services also power Microsoft’s conversational user experiences, through its Bot Framework. It’s even in your databases, with new analytics and machine learning tools in SQL Server 2017.To read this article in full, please click here

Leave a Reply