Robots are getting more versatile and artificial intelligence (AI) is getting exponentially smarter! Our jobs are in jeopardy and no one is safe! We've all seen the headlines. Anxiety and fear are steadily mounting that we are on the edge of a profound transition (some might even call it a Big Shift) that will put us out of work and on the streets. Some respond that this is simply a resurfacing of a Luddite fear of new technology that has erupted every time new technology breakthroughs occur.

Historically speaking, people defending digital infrastructure are at a significant disadvantage. Bad guys can morph their malware tools at will, while security professionals must always be at the ready to shove out new versions of their products when previously undetected malware is discovered--often too late for the defenders who then have to clean up the mess. And bad guys are opportunists, always casting their nets in waters teeming with unsuspecting victims. Nowhere is this more apparent than in the mobile industry, in particular devices running the Android operating system. Security companies have been reporting massive increases in malware infections.

You've probably heard of Prisma, one of the hottest apps this year. Downloaded more than 50 million times since June and powered by artificial intelligence, it uses filters to transform any photo into a stunning work of art evocative of say, Pablo Picasso or a Renaissance master. It's trending in the App Store: ranked fourth in the free photo and video category behind Snapchat, Instagram, and YouTube. But you've probably heard less about the Prisma bot with similar features and the same name, launched less than a month ago on Telegram. It's notable that one of today's most popular mobile apps waited only about a month before launching a bot, and it begs the question: Are bots replacing apps?

New research reveals how to trick facial-recognition systems. The question is, how do you fix it? Our machines are littered with security holes, because programmers are human. In building the software that drives these computing systems, they allow code to run in the wrong place. They let the wrong data into the right place.

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I also look after our NVIDIA Inception Program. Inception has been designed for start-up companies in the field of AI who are interested in having a relationship with NVIDIA that allows them to leverage our technical and go-to-market expertise. They also receive early access to software and hardware releases to help them better develop their products and platforms. What are the key factors that have enabled recent advancements in deep learning? Competition in the research and data science space has been very important in driving progress.

Natural Language Processing (NLP) has long been one of the holy grails of computer science. While we all know that computers are better than humans at making sense of highly structured information, there are still some important areas where humans are undeniably better than machines. Understanding language is one of those areas. For humans, understanding language is so natural we usually don't even have to make a conscious effort to do it. In reality, though, processing language and turning it into meaningful information is an extremely complex and difficult task.

The key point is that we are not interested in all possible ML problems, most of them don't make any sense and will never occur with real data. Imagine I have a training and test set for a binary classifier, you can train a good algorithm and get 95% accuracy for the test set, now you flip the labels in the test set and the same algorithm that was excellent is a disaster. But there's a trick: the new problem doesn't make any sense. We are expecting the algorithm to learn how data works and then predict in the opposite direction. We don't have this problems with real data, they just don't make sense.

Over the years, artists, writers, filmmakers and game studios have all tackled the concept of artificial intelligence. Often their vision is of machines that are brutally hostile to humans. Philip K. Dick envisioned androids that murder their owners. Of course, there's Skynet, which launches an all-out war on mankind. We could go on like this for a long time. But there are also those, like Spike Jonze, who envision us having a more complex relationship with computer-based personalities; one in which they could even be love interests.

At the confluence of the rise in messaging applications, advances in text and language processing, and mobile form factors, bots are emerging as a key area of innovation and excitement. Bots (or conversation agents) are rapidly becoming an integral part of your digital experience--they are as vital a way for people to interact with a service or application as is a web site or a mobile experience. Developers writing bots all face the same problems: bots require basic I/O, they must have language and dialog skills, and they must connect to people--preferably in any conversation experience and language a person chooses. This code-heavy talk focuses on how to solve these problems using the Microsoft Bot Framework, a set of tools and services to easily build bots and add them to any application. We'll cover use cases and customer case studies for enhancing an application with a bot, and how to build a bot--focusing on each of the key problems: how to integrate with various messaging services, how to connect to users, and how to process language to understand the user's intent.