Microsoft has acquired Genee, a startup that provided a virtual assistant for scheduling appointments. The deal, announced Tuesday, will bring the Genee team into the Microsoft fold and put them to work on bringing intelligence into Office 365. Genee's service lets users loop in an artificial intelligence assistant that could interpret sentences like "set up lunch at some point this week" and turn them into calendar appointments. Acquiring Genee is part of Microsoft's ongoing crusade to build intelligent productivity software and services using AI. The company has focused on that area under the tenure of CEO Satya Nadella, with features like Office Delve, which finds documents shared within an organization that are relevant to a user, and Focused Inbox in Outlook, which filters unimportant email into a separate tab so it's not cluttering a user's experience. The Genee service will be shutting down on Sept. 1 as part of the deal.

Bots are officially everywhere -- they're available to assist with almost every part of our lives, from shopping and gift-giving to news-tracking and political decision-making. They can even tell us what to make for dinner. The thing that seems odd to me, though, is that the entire bot conversation has been focused on A.I., machine learning (ML), and natural language processing (NLP). This makes me question whether we're looking at bots the wrong way. Having been in the business of building software for quite some time, and learned about workflows, business logic and other riveting concepts, I can't help but feel there's a misunderstanding about what constitutes a bot and what is just an access layer to the bot.

This article is the first of a series dedicated to amazing ChatScript, an open-source natural language processing and dialog flow scripting platform. First of all I explain some general concepts and platform architectures. I introduce the beginner chatbots authors to practice with ChatScript programming (in this article, just starting with standalone platform installation on a personal computer). I precede this sort of installation guide for dummies, with an overview on software platforms architectures for conversational engines. The reader with a basic programming skill will be able to install and run the engine on his personal computer enjoying to chatbots scripts development!

This book is for anyone who intends to work with large and complex data sets. Familiarity with basic Python and machine learning concepts is recommended. Working knowledge in statistics and computational mathematics would also be helpful. Large Python machine learning projects involve new problems associated with specialized machine learning architectures and designs that many data scientists have yet to tackle. But finding algorithms and designing and building platforms that deal with large sets of data is a growing need.

You can get a pretty good idea of a country's wealth by seeing how much it shines at night – just compare the intense brightness of China and South Korea to the dark mass of North Korea that's sandwiched between them. But nighttime lights don't tell you which neighborhoods or villages within a large region are merely poor and which are home to people living in abject poverty. That's the level of detail policymakers need when they decide where to deploy their economic development programs. You could get that detail by sending legions of survey-takers into crowded slums and sparsely populated rural areas. But that would be hugely time-consuming and cost tens of millions of dollars or more.

Microsoft acquires AI-powered scheduling service Genee, to be shut down and merged with Office ... 'Software is eating the world': How robots, drones and artificial intelligence will change everything

Feels like a home away from home. Microsoft acquires AI-powered scheduling service Genee, to be shut down and merged with Office ... 'Software is eating the world': How robots, drones and artificial intelligence will change everything

Intel Corp. INTC 0.34 % signaled it wants a bigger role in artificial intelligence, revealing plans to modify a line of chips to target a fast-growing market turning into a battleground for technology suppliers. The company told technology developers Wednesday that it plans next year to deliver a new version of the Xeon Phi processor--a product line previously targeted at scientific applications--with added features designed to accelerate tasks associated with what Silicon Valley calls artificial intelligence. Intel said the technology will help accelerate a technique called deep learning, increasingly used for tasks such as interpreting speech, identifying objects in photos and piloting autonomous vehicles. Intel's Xeon processors already are a fixture in data centers, and have a role in nearly all deep-learning tasks carried out there. But some users also install auxiliary processors for artificial-intelligence tasks, notably chips called GPUs that rival Nvidia Corp. NVDA 0.42 % has long sold for videogames.

In the healthcare industry, natural language processing has many potential applications. NLP can enhance the completeness and accuracy of electronic health records by translating free text into standardized data. It can fill data warehouses and semantic data lakes with meaningful information accessed by free-text query interfaces. It may be able to make documentation requirements easier by allowing providers to dictate their notes, or generate tailored educational materials for patients ready for discharge.

Over the past few weeks, we've started to learn more and more about machine learning and the role it plays in computer vision, image classification, and deep learning. We've seen how Convolutional Neural Networks (CNNs) such as LetNet can be used to classify handwritten digits from the MNIST dataset. We've applied the k-NN algorithm to classify whether or not an image contains a dog or a cat. And we've learned how to apply hyperparameter tuning to optimize our model to obtain higher classification accuracy. However, there is another very important machine learning algorithm we have yet to explore -- one that can be built upon and extended naturally to Neural Networks and Convolutional Neural Networks.