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Tech pundit Tim O'Reilly had just tried the new Google Photos app, and he was amazed by the depth of its artificial intelligence. O'Reilly was standing a few feet from Google CEO and co-founder Larry Page this past May, at a small cocktail reception for the press at the annual Google I/O conference--the centerpiece of the company's year. Google had unveiled its personal photos app earlier in the day, and O'Reilly marveled that if he typed something like "gravestone" into the search box, the app could find a photo of his uncle's grave, taken so long ago. Google is open sourcing software that sits at the heart of its empire. The app uses an increasingly powerful form of artificial intelligence called deep learning. By analyzing thousands of photos of gravestones, this AI technology can learn to identify a gravestone it has never seen before.

Guest blog post by Christopher Dole and other contributors, originally posted here. Deep Learning is one of the most revolutionary and disruptive technologies ever developed in Data Science. Essentially, this is a class of algorithms inspired by how the human brain works, and it has the ability to automate and replace most of the world's jobs. This is what enables self-driving cars to function and what allows Spotify to create very customized playlists and recommendations. This is how YouTube is able to identify faces and animals in videos and how Siri can understand and process free speech in milliseconds.

The term artificial intelligence (AI) has been around since the 1950s. However, it's only within the last five years that excitement about it has really begun to grow. This excitement is, in part, due to a new technique called'deep learning'. This is where artificial systems'learn' (in that they make and strengthen connections), through repeatedly working through large numbers of examples. The systems consist of networks of artificial'brain cells' (or neurons) that combine signals and send them between different layers within the network.

Note that the machine learning algorithm is better when you deliver more accurate data. To make the system more effective, you need to spend a few weeks manually indicating whether each payment is fraudulent or not.

Update: Though Yoshua Bengio originally referred to his incubator as Element.AI, the official name is now Element AI.

Office 365 is going to get a whole lot smarter, all thanks to Genee. Genee, an AI that has been around for two and a half years, is essentially a digital assistant that books appointments, sets reminders, and can even reschedule meetings on the fly using simple commands from your phone or computer. Now, Genee is set to come to Office 365, and it is not exactly clear what role it will play. "As we continue to build new Office 365 productivity capabilities and services our customers value, I'm confident the Genee team will help us further our ambition to bring intelligence into every digital experience," writes Corporate Vice President for Microsoft Outlook and Office 365, Rajesh Jha, in an official release. According to Genee co-founders Ben Cheung and Charles Lee, the service shuts down on September 1 in its current form.

IBM Watson Virtual Agent is a set of preconfigured cognitive components based on the IBM Watson Conversation service. By configuring the virtual agent with your company's information, you can quickly implement an automated chat bot that enables your customers to achieve their goals. The established model of creating a digital or virtual agent requires experienced developers with a highly specific skill set to create complex systems that rely on custom – and often cumbersome – rules. Watson Virtual Agent allows businesses to simply build and deploy conversational agents. Watson Virtual Agent helps accelerate users' ability to deploy bots, including pre-trained cross-industry content, with minimal configuration, simplifying the process for both seasoned developers or users without formal technical training.

Black holes are an ongoing area for research and discovery. However, many mysteries of the universe can be solved with Big Data analytics. Artificial intelligence (AI) is the killer application of Big Data analytics. Logically based on machine learning and Big Data analytics, the more data available, the more intelligent it will get, resulting in more widespread applications. In future, you may own a smart robot or even a smart dog.

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