Facebook (NasdaqGS: FB - news) extended its reach beyond online socializing by building artificial-intelligence powered "bots" into its Messenger application to allow businesses to have software engage in lifelike text exchanges. The move announced at the leading online social network's annual developers conference in San Francisco came as the number of monthly users of Messenger topped 900 million and the Silicon Valley company works to stay in tune with mobile Internet lifestyles. "We think you should be able to text message a business like you would a friend, and get a quick response," Facebook co-founder and chief Mark Zuckerberg said as he announced that developers can build bots that could even be better than real people at natural language text conversations. Bots are software infused with the ability to "learn" from conversations, getting better at figuring out what people are telling them and how best to respond. The bots could help Facebook over time monetize its messaging applications and get a start on what some see as a new way of interacting with the digital world, potentially shortcutting mobile applications and sidestepping search.

Intel's keynotes can be fun, with robots parading on stage and drones zigzagging around the room. Now Intel's making new hardware to help enthusiasts join the fun by building robots and drones at home. The Robotic Development Kit and Aero Kit provide the necessary hardware and software tools to build robots and drones, respectively. The kits were announced at the ongoing Intel Developer Forum in Shenzhen, China. A major element of the developer boards is the RealSense 3D camera, which will ship with the kits and help the robots and drones navigate and avoid obstacles.

Google Cloud Machine Learning is a managed platform that enables you to easily build machine learning models, that work on any type of data, of any size. Create your model with the powerful TensorFlow framework, that powers many Google products from Google Photos, to Google Cloud Speech. Build models of any size with our managed scalable infrastructure, which is powered by GPUs. Your trained model is immediately available for use with our global prediction platform that can support thousands of users and TBs of data. The platform is integrated with Google Cloud Dataflow for pre-processing, allowing you to access data from Google Cloud Storage, Google BigQuery, and others.

You are working on a classification problem and you have generated your set of hypothesis, created features and discussed the importance of variables. Within an hour, stakeholders want to see the first cut of the model. You have hunderds of thousands of data points and quite a few variables in your training data set. In such situation, if I were at your place, I would have used'Naive Bayes', which can be extremely fast relative to other classification algorithms. It works on Bayes theorem of probability to predict the class of unknown data set.

For a service provider, being able to anticipate its customer's behaviour has three major benefits. It can generate customer delight, prevent customer exhaustion, and improve the company's ROI. Let's look at each of these benefits through three different use cases in the Customer lifecycle: Complaints Management, Customer Upsell and Customer Retention. A dissatisfied customer, filing a complaint is difficult to manage. He is very often passionate about his claim - whether it is justified or not - and there is sometimes little which can be done to change his perception and his opinion towards the service he initially subscribed to. If however the company could tell precisely which customers are going to complain and when, it could avoid the management of a complaint by calling them pre-emptively to enquire about their satisfaction and offer them an incentive or a boon.

In 1950, artificial intelligence pioneer Alan Turing famously proposed what came to be known as the Turing Test: the proposition that a machine had achieved intelligence if it could carry on a conversation that was indistinguishable from a human one. In 2016, Turing's ghost has come to haunt Silicon Valley in a big way. Companies are racing to build technology that can talk with you. Last month, Microsoft launched the Microsoft Bot Framework, a set of software tools that let companies create their own conversational bots. Customers of Domino's, for instance, can order products by chatting back and forth with a robot, as if they were sending a text message.

Above the Trend Line: machine learning industry rumor central, is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items such as people movements, funding news, financial results, industry alignments, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz. Our intent is to provide our readers a one-stop source of late-breaking news to help keep you abreast of this fast-paced ecosystem. We're working hard on your behalf with our extensive vendor network to give you all the latest happenings. Be sure to Tweet Above the Trend Line articles using the hashtag: #abovethetrendline.

How can both the contact center manager and the end customer find satisfaction? The answer for many is artificial intelligence. In the customer contact space, artificial intelligence (AI) applies higher-level "thinking" to traditional IVR. This automated solution empowers natural speech recognition throughout the call and an intelligent brain on the back end to better interpret and even predict user responses. As a result, customer intentions are anticipated more effectively and directly, bringing greater satisfaction and less likelihood of zeroing out to speak to a live agent.

Facebook has finally unleashed Messenger Platform, letting developers build chatbots -- intelligent software that lets you get stuff done just by sending text messages. And investors are pouring cash into startups that promise to ride the wave. Which makes it even weirder that Facebook's introduction of the Messenger Platform feels a little tepid. Rather than follow in Microsoft's footsteps and pitch chatbots as a transformational shift that will change the future of computing, Facebook CEO Mark Zuckerberg is billing them as a better way to interact with businesses and go shopping. There's not even an app-store-like listing of available bots to see them in one place.

At a time when the banking industry needs to become increasingly focused on creating better customer experiences, the importance of distributing personalized communications that provide real value has never been greater. Artificial intelligence (AI) can help make this possible -- both automatically and at scale. The banking industry is undergoing a major transformation. Evolving regulatory requirements, more demanding customers, and greater competition from new, non-traditional players are among the catalysts driving change. Collectively, these and other factors are forcing banks and credit unions to rethink their business and how they engage with consumers.