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10908_AI_BusiScho_Lance_Olson_FINAL_V2

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[AI Business School] [Introduction to AI technology for business leaders Examine the Microsoft approach to pre-trained AI cognitive services] >>Lance: Azure Cognitive Services give you a way to add AI capabilities into your application without needing to be a data scientist. There are a number of different aspects to Cognitive Services that I want to talk about with you today. One is vision. We have vision capabilities which lets you write applications that can actually see things. For example, you can see a document, and it can read the words off of a page. You can use that to be able to take forms. If you have customers filling out documents, or if you have forms that you're processing, you can use those services to be able to understand the forms, and then be able to process the text that's in the forms. It can also look at images, and recognize what's in an image, or find faces or find people in the image, and understand who's there, and use that connected to a camera, for example, in order to recognize your customers. You can also use speech. Cognitive Services let you take speech and translate it, or convert it to text, or takes text, and convert that to speech. We also support translation, so you can understand different languages. Next, we have language understanding. Language understanding is beyond speech. It's actually looking at text of many different types of languages, and do things, like understand the intent somebody has. If they say something like, "I want to order a pizza," they might say that in different ways, like, "Let's have a pizza," or, "Give me a pizza." But the intent there all maps to order a pizza. There, our language services can understand the intent when someone speaks, and map that to an action that you can program into the service. We also do things, like text analytics, so we can look at sentences or paragraphs, and tell you what are the key things that they're talking about in this sentence, or in this paragraph, And is it positive or negative? We also do knowledge understanding. [What are Cognitive Services?] With knowledge, what we do is we can process whole documents, and then make sense of them, and provide action on top of them. For example, imagine you wanted to build a conversational experience for one of your products. You could take a FAQ, and feed that into our knowledge service. Our Q&A Maker service is the name of the service. And Q&A Maker would read that document. It would look at the questions and the answers, and it would map them. So then if a person asks a question, and it doesn't have to map exactly, but asks a question that means basically the same thing as one of the questions that is in your FAQ, the service would then recognize that, and give back the answer. Finally, we expose search, that's Bing search. What that lets you do is harness the knowledge that Bing has of the world around us, and take advantage of that knowledge in your own solutions and in your applications. For example, if you were building an application that had to deal with topics that were coming in, and you wanted to understand about related images or related news stories, you could call the Bing search API, and get back related web information for that topic. You could also even pass in lat/long value, location information, and get back related businesses that might be nearby. Find out all about the world around you, and use that to augment the understanding that your system has of the world around it, and the entities that it works with. I'd like to also point out that there are lots of different kinds of use cases that we see with Cognitive Services. They span a very broad range. For example, in retail, you could use those services to understand what people say about your products. You could have the language understanding service looking at the feedback that's coming in for your products. It would break that down and find the keywords that people mention. It would look at the sentiment and see if it's positive or negative. You could do the same thing using speech to analyze data that's coming into a call center. It might be a help desk or an external-facing product support line that you have. And you could see what customers are saying about your products, and take action in real-time on that. You could also use these services to build conversational experiences. For example, in cases where you might have an environment where a keyboard and a mouse is not the best interface like if you're operating heavy machinery, or doing anything else that requires the use of your hands, you could build experiences that use speech and interact with speech. And do that right inside of the application, both in terms of hearing what people say, and also being able to speak back to them. You could also use these services to do business process automation use cases, like scanning documents, and then reading them, and then converting that scanned text into actual digital text, that you then can take action on. There's a wide range of use cases that you can apply these services to. And we see customers doing that everyday. A couple other key things I'd like to point out and make sure you're aware of. [CS Momentum: Availability & Compliance] One is, we've really focused for these services on making them available broadly. In the last year, we've gone from having them in 5 to 7 regions, to now 25 different regions around the world. And that's important because it enables you to take advantage of the service in a region that is close to you. And also, store your data in a place that matches your geopolitical boundaries. We've also done work to add over 65 different certifications, like HITRUST and SOC and HIPAA, in order to be able to run these services in compliant regions and in compliant ways, even for applications that require a high amount of trust in governance over the data. And then finally, several of these services have been added to the Azure core services list, also giving further guarantees on how you can use them. The last thing I'd like to call out is, we offer many of these services, both as standalone services that run in our cloud in Azure, but also as a thing we call "containerized services." Containerized Cognitive Services let you take advantage of a service in whichever context matters for you. For example, you could run the service in the cloud. But let's say you needed to take advantage of that service in your local retail store. You could also run it there. Some cases, we see customers who want to be able to control exactly where the data goes. The data stays inside the containers. So you can actually run the containerized services anywhere that you can run a container. That could be in your local environment on your local network, in the cloud, or somewhere else. And that level of control, we think is really important because it lets you be in charge of your data, and take advantage of exactly how AI runs over your data, and where it runs. Regardless of where you run it, we're very excited to be able to see what people do with Cognitive Services. And there is a whole world of opportunities that it opens up for us.

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Posted by: csintl on Jun 18, 2019

10908_AI_BusiScho_Lance_Olson_FINAL_V2

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