Artificial intelligence has held a place in our imaginations for the better part of a century. Hollywood has given us films portraying humanoid robots and sentient computers since the 1920s. Recently, these futuristic ideas have become a reality, earning artificial intelligence a constant place in the spotlight of the business world. IBM Watson has competed against Jeopardy champions, Netflix is using machine-learning algorithms to make binge-worthy recommendations, and chat bots are now being used by businesses to change the face of customer service. Equally important, albeit under-the-radar, advancements in artificial intelligence have enabled companies to act on robust data sets, giving executives the ability to make data-driven decisions at a moment's notice.

Amazon (NASDAQ:AMZN) had the perfect answer to the potential threat posed by Alphabet's (GOOG, GOOGL) upcoming Google Home intelligent home assistant. Amazon's prompt answer was to just sell a 20-off Alexa-powered Amazon Tap Bluetooth speaker/smart home assistant. In fact, Apple's (NASDAQ:AAPL) alleged upcoming Siri Speaker will also likely get a beat-down from Amazon Echo's cheaper variations. Deep discounting is Amazon's deadly weapon against any threat to its popular brands of smart devices. All the cheapo Fire tablets, Fire TV console/stick products, and Alexa-powered speakers it sells are mere customer recruitment avenues for Amazon's online marketplace.

Microsoft Corp. has agreed to acquire Wand Labs, a startup whose messaging technology will help upgrade the software giant's efforts in chatbots. Financial terms of the deal weren't disclosed. Earlier this week, Microsoft MSFT, 1.41% agreed to a blockbuster acquisition of LinkedIn Corp. LNKD, 0.02% for 26.2 billion. Redwood City, Calif.-based Wand Labs will join the Bing engineering and platform group at Microsoft. The Bing group has been developing technology that fits into Microsoft's strategy surrounding what Chief Executive Satya Nadella calls "conversation as a platform."

Reuters – Apple unveiled a series of improvements to its Siri digital assistant last Thursday, but the tech giant still trails rivals such as Google and Amazon in the red-hot field of artificial intelligence, experts say. Apple's biggest move was to open up the talking iPhone assistant to third-party developers for inclusion in their apps, paving the way for users to hail a ride from Uber or send a message with Tencent's WeChat using voice commands. Experts in artificial intelligence applauded the move as an important step forward, in part because the more people use an artificial intelligence system, the better it becomes. But some wondered why Apple had not made Siri an open platform much sooner, noting that competing products including Amazon.com's Alexa, Microsoft's Cortana and the Google app are already open to developers. "Is it too little too late?"

Intelligent computers that can make decisions like humans may someday be on Hewlett Packard Enterprise's product roadmap. The company has been showing off a prototype computer designed to emulate the way the brain makes calculations. It's based on a new architecture that could define how future computers work. The brain can be seen as an extremely power-efficient biological computer. Brains take in a lot of data related to sights, sounds and smell, which they have to process in parallel without lagging, in terms of computation speed.

When I was working on my next pattern classification application, I realized that it might be worthwhile to take a step back and look at the big picture of pattern classification in order to put my previous topics into context and to provide and introduction for the future topics that are going to follow. Pattern classification and machine learning are very hot topics and used in almost every modern application: Optical Character Recognition (OCR) in the post office, spam filtering in our email clients, barcode scanners in the supermarket … the list is endless. In this article, I want to give a quick overview about the main concepts of a typical supervised learning task as a primer for future articles and implementations of various learning algorithms and applications. Predictive modeling is the general concept of building a model that is capable of making predictions. Typically, such a model includes a machine learning algorithm that learns certain properties from a training dataset in order to make those predictions.

David: I've gone through this myself in the past couple of years. There is so much out there right now that if you have any interest in machine learning or data science topics, you can buy any number of good books that will give you overviews and get you started. There are online courses and tons of blogs that will cover a lot of this stuff. I would say the best thing to do is to get started and just try some stuff. Honestly, for basic machine learning, a good start is to take a look at our presentation.

Google announced in a blog post on Thursday that it has set up a new AI research group in Europe to focus on machine learning (ML). Machine learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Google Research, Europe -- as the group is known -- is based out of Google's office in Zurich, Switzerland, which is home to Google's largest engineering office outside the US. Google said the group, which is expected to grow to over 100 people in the coming years, will focus on three key areas: machine intelligence, natural language processing and understanding, and machine perception. Companies like Amazon, Facebook, and Microsoft are all investing heavily in these areas as they look to make their platforms and services more intelligent.

"In 2016, selecting the top achievers was extremely difficult," said Alex Vieux, publisher and CEO of Red Herring. "The variety, depth, disruption and traction we saw from the early stage companies to those with significant scale made it one of the toughest vintages to judge. The North America winners are representative of the amazing ecosystem that never ceases to astound, with new and experienced entrepreneurs continuing to push the barriers of innovation. As one of the winners, Armorway should be proud of its accomplishment under such strong competition." Red Herring's editorial staff evaluated companies on both quantitative and qualitative criteria, such as financial performance, technological innovation and intellectual property, DNA of the founders, business model, customer footprint and market penetration.

In the future, people - certain people - may be able to download information directly into a device embedded in their skull and linked to their brain. These people will also be capable of improved physical performance, courtesy of pods embedded in their bodies and controlled by a link to the brain that can release chemicals or hormones to enable performance of all kinds of tasks, even in extreme conditions. That's what awaits us as biology and technology blend together, says business software developer MYOB Group in its latest Future of Business report entitled, appropriately, 'The Augmented Human'. MYOB chief technical officer and futurist Simon Raik-Allen says technology will move from mobile, wearable technological devices such as Fitbits to tiny embeddable devices that can provide real-time data or move parts of the body. Artificial intelligence (AI) will enable people to enhance their brain or personality.