From the course: Leveraging Cloud-Based Machine Learning on Azure: Real-World Applications

AI processing on Azure - Azure Tutorial

From the course: Leveraging Cloud-Based Machine Learning on Azure: Real-World Applications

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AI processing on Azure

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- [Narrator] So why is it that machines need to think? So they provide us with certain capabilities that traditional programming isn't able to approach. For example, the ability to leverage your ride share program that'll tell you not only when the ride's going to show up but the optimal route to get you to your destination quickest. Entertainment becomes a machine learning capability as well such as the ability for your favorite streaming service like Netflix to recommend movies you may enjoy. Or more importantly, the ability for a healthcare provider to spot and diagnose some sort of a disease from a symptom that human beings may have missed. Because they're able to go back amongst thousands of outcomes and figure out what's the likely issue. So how do things relate? Well, ultimately we have the core notion of artificially intelligent systems, which have been around for decades. Building on that, we have an instance of artificial intelligence, which we call machine learning. It's more pragmatic and it's more tactical in how we're leveraging AI based systems, but in unto itself is an AI based system. And then finally, we have deep learning systems, which are really the ultimate. They're able to consider massive amounts of information into certain patterns within that information. Perhaps, deeper and more strategically focused than machine learning. And then we have what's next, people are building new innovations all the time on this existing AI and machine learning base infrastructure, and the sky is the limit. Ultimately if we have machines that think, we'll have machines that are able to teach other machines, and the ability to abstract and aggregate the knowledge into massive brains that are able to, in essence, do what we can't do with single human beings or even a committee. So how did Microsoft get into this game? Here's a brief history. Ultimately, Microsoft research was formed in 1991 to figure out where the next generation technologies are going to be. They launched Hotmail in 1997 as the internet started to rise and the AI systems within Hotmail were able to find spam based systems and redirect the email. They were able to bring artificially intelligent systems to Bing Maps, then later the Bing search engine. And then in support of gaming, they add the Kinect system launch, where you're able to spot motions based on an object standing in front of a video camera. They brought AI technology to Skype to translate different languages and to bring artificially intelligent systems to telephony. Then here we are today, ultimately, back in 2014 Azure machine learning was launched and it's been out there ever since. In essence, providing artificially intelligent systems, the machine learning based systems, as a service, and we're going to learn all about that.

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