If you think you're computer doesn't know you better than anybody in your life, then you're very, very wrong. This type of artificial intelligence is becoming more and more common and is just kind of the way it's going to be with new technology from now on. TechCrunch breaks it down for us, saying that RankBrain is really ANI – artificial narrow intelligence, which is like, "AI for one particular thing (e.g. Last year, Google announced their new search software, RankBrain, that according to Bloomberg News, "Can make a guess as to what words or phrases might have a similar meaning and filter the result accordingly, making it more effective at handling never-before-seen search queries." While it may sound a little too Ex Machina for comfort, it's actually a pretty cool development.

Berlin - 03 Sep 2016: at IFA Berlin – one of the world's leading trade shows for consumer electronics – IBM (NYSE: IBM) was joined by some of the biggest names in the industry to highlight how Watson IoT technologies are poised to drive a new wave of innovation in the home and play a key role in one of the biggest technological transformations in the history of the world. According to Harriet Green, Global Head of IBM Watson IoT: "millions of sensors are giving appliances and devices eyes and ears, increasing their inbuilt intelligence and enabling them to interact with us better." "The challenge is that over next few years, the Internet of Things will become the biggest source of data on the planet. That's where IBM's Watson cognitive computing system comes in. Watson uses machine learning and other techniques to understand this data and turn it into insight, which can help automate tasks, enable manufacturers to design better products, innovate new services and enhance our overall quality of life – especially in the home. And with cognitive technologies, interactions with'things' through natural language and voice commands will dramatically improve," added Green during her keynote at IFA. Examples of companies tapping IBM's Watson IoT platform include: Whirlpool is using Watson technologies to help deliver superior customer service and enhance people's lives at home by enabling its home appliances to connect with and interact with one another and their users.

There's an emerging market called Dataism, which venerates neither gods nor man - it worships data. From a Dataist perspective, we may interpret the entire human species as a single data-processing system, with individual humans serving as its chips. A city of 100,000 people has more computing power than a village of 1,000 people. Different processors may use diverse ways to calculate and analyse data. Using several kinds of processors in a single system may therefore increase its dynamism and creativity. A conversation between a peasant, a priest and a physician may produce novel ideas that would never emerge from a conversation between three hunter-gatherers. There is little point in increasing the mere number and variety of processors if they are poorly connected. A trade network linking ten cities is likely to result in many more economic, technological and social innovations than ten isolated cities. 4. Increasing the freedom of movement along existing connections. Connecting processors is hardly useful if data cannot flow freely.

While many of the different works on artificial intelligence (A.I.) focus on improving the quality of human life and easing the burden on people for certain tasks, the threat of machines taking over our jobs is nothing new. With the Fourth Industrial Revolution that brings fancy concepts like Internet of Things (IoT) or Big Data to the traditional industrial facilities in order to embrace unprecedented automation opportunities, more and more blue collar workers are faced with the unemployment threat. But judging by the way things are going, robots will not stop at factories. Another traditional profession, news reporting, is also under near threat of A.I. and the reason for this is very simple: Machines love categorical information. If it is possible to put every piece of data in order on an Excel spreadsheet, no matter how complex it is, then A.I. is perfectly capable of analyzing and producing meaningful information from this sheet.

In this lesson we are going to walk through the exciting topic of big data analysis. At a high level, big data analysis is the process that helps to build algorithms that can analyze vast amounts of data and be able to generate behavior-based decisions from that data. For big data analysis in this section, we'll be using the Decision Tree gem. It uses the ID3 algorithm and is very efficient in taking data and making decisions based on it. I'd like to show you a practical big data project I built for a client about a year ago.

Cortana may eventually be able to peek inside your refrigerator following news that Microsoft is bringing its machine learning tech to kitchens. The computer firm is working on a new computer vision module called SmartDeviceBox, which will be installed inside fridges to make them capable of recognising objects inside and telling owners when they need to re-stock. The SmartDeviceBox is essentially an internet-connected camera unit that sits inside fridges and tracks the objects inside. The unit contains an image processing system based on Microsoft's suite of deep learning tools, which has been trained to recognise a variety of products such as milk cartons, ketchup bottles and pickle jars. The system is able to collate these into an inventory list that customers can view in list form using a smartphone app.

In June, Facebook unveiled a new technology with a remarkable ability: DeepText, an artificial-intelligence engine that can understand "with near-human accuracy," according to its engineers, the content in thousands of posts per second–in more than 20 different languages. The program, which promises to grow increasingly adept at grasping the subtleties of human communication, has profound implications for how Facebook serves up content, products, and services to its more than 1.65 billion active monthly users. On Facebook's Messenger app, DeepText can anticipate when someone needs a car and serve up a link to Uber; on the site's News Feed, it can analyze a person's interests to surface the most relevant stories and comments. Ultimately, it can help Facebook create a more personalized and seamless user experience. As CEO Mark Zuckerberg wrote in a June post about his company's AI investments, "One of our long-term initiatives is to build a new generation of Internet services that are more intuitive and can more easily connect you with the things you care about by understanding the meaning of voice, text, images, videos, and other information."

The word Artificial Intelligence has been thrown around in the start-up world over the past few months, with phrases like Machine Learning and Natural Language Processing following shortly after. That said, can these rapidly evolving technologies really be used to influence the travel industry, and if so, by how much? Machine learning, in its many forms, has allowed computers to build an understanding of who we are, by making use of the data that we provide. As a result, advertising has become more specific, algorithms have got more intelligent, and the background processing of mobile applications and computer software has become more tailored to the user. Remember the last time you saw that advert pop up onto your computer screen after having a look for something?

Many years ago, a company pitched me an intriguing product to review: a display you mount in the rear window of your car, which you can use to send customized messages to drivers behind you. With the tap of a button near your dashboard, the display would light up with a scrolling message of whatever it was you wanted to tell other drivers--a great way to get pulled over by a cop, if not outright killed by some already-angry tailgater. The Silicon Valley startup Drive.ai The theory is that digital signs would make self-driving vehicles a bit safer, since they don't really have a great way of letting pedestrians know their intentions beyond simple turn signals. The sign would be able to indicate various statuses about the vehicle to those near it, including when it might be safe to lane-split (because the self-driving car has noticed you and promises to not merge into the next lane and smoosh you).

Prashant Natarajan Iyer (AKA "PN") is an analytics and data science professional based out of the Silicon Valley, CA. He is currently Director of Product Management for Healthcare products. His experience includes progressive & leadership roles in business strategy, product management, and customer happiness at eCredit.com, He is currently coauthoring HIMSS' next book on big data and machine learning for healthcare executives - along with Herb Smaltz PhD and John Frenzel MD. He is a huge fan of SEC college football, Australian Cattle Dogs, and the hysterically-dubbed original Iron Chef TV series.