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If you think mobile apps have lost their charm and using them doesn't excite you anymore, you're in for a real surprise. Chatbots, or bots, are taking the digital world by storm, and they're even getting integrated into mobile apps. Even industry giants are encouraging developers to work on their chatbot platforms. In April 2016, Facebook allowed all developers and businesses to build chatbots for its Messenger service. Marketers can have a field day with this, because it allows them to interact with customers and prospects. For some businesses, chatbots can replace humans in customer service, while for others, it can become a powerful marketing tool.

Machine learning has had fruitful applications in finance well before the advent of mobile banking apps, proficient chat bots, or search engines. Given high volume, accurate historical records, and quantitative nature of the finance world, few industries are better suited for artificial intelligence. There are more uses cases of machine learning in finance than ever before, a trend perpetuated by more accessible computing power and more accessible machine learning tools (such as Google's Tensorflow). Today, machine learning has come to play an integral role in many phases of the financial ecosystem, from approving loans, to managing assets, to assessing risks. Yet, few technically-savvy professionals have an accurate view of just how many ways machine learning finds its way into their daily financial lives.

Why? Townsend's friend had searched for Harry Potter a few days ago. And when he put Allo on the spot with a question about its existence, it spit out a random link it had uttered recently. Allo had done something very frightening: It had aired his private search results. Google called the error an "issue." And I'm sure to any software developer, that's exactly what it was–another bug to be squashed.

AlphaGo is beating humans at Go - What's the big deal? Rob Miles explains what AI has to do to play a game. What on Earth is Recursion?: https://youtu.be/Mv9NEXX1VHc Many thanks to Nottingham Hackspace for providing the location and being downright awesome Easter Egg: https://youtu.be/B8CujhUwVic This video was filmed and edited by Sean Riley.

The home smart speaker market didn't even exist just a few short years ago, but it's taking the world by storm. It has since been joined by sibling products -- the smaller Echo Dot and the wireless Tap -- with Alexa at the heart of each one. Consumer Intelligence Research Partners (CIRP) reports that in just two short years after its introduction, Amazon has sold an estimated 8.2 million devices, and was one of the company's top selling items over the holidays. While competition in the field is intensifying, it may be difficult for similar products to overcome Amazon's early lead. Here are four reasons why Amazon could come out on top.

It's called the prisoner's dilemma and it goes like this: You and a fellow gang member are in jail. One of you committed a heinous crime, but the prosecutor doesn't know who. Instead, you are both booked on a lesser charge and serving a one-year sentence in solitary confinement. But here's the deal: The prosecutor has given you both an opportunity to rat. If you betray your fellow gang member but are not ratted on, you walk free while your buddy serves a three-year term.

This article was written by Roopam Upadhyay. Roopam is a seasoned professional of advanced analytics with more than a decade of experience in statistical modeling, data science, predictive analytics, optimization, & business consulting. They learn the same way as humans. Humans learn from experience and so do machines. For machines, experience is in the form of data.

If you want to see a great example of how data science can inform every stage of a business process, from product concept to operations, look no further than Stitch Fix's Algorithms Tour. Scroll down through this explainer to see how this personal styling service uses data and statistical inference to suggest clothes their customers will love, ship them from a nearby warehouse (already stocked thanks to demand modeling), and incorporate customer feedback and designer trends into the next round of suggestions. The design of the Tour is interactive and elegant, and clearly someone put a lot of work into it. It's a great example of simplifying the detail of data science into a format where the impacts are immediately apparent. Communicating the benefits of data science to non-experts is a key skill of any data scientist, and dialing down on the complexity, while not dumbing down the science, is key to that communication.

Last year, Swedbank in Sweden "hired" Nina, a dynamo of a company rep. Nina is adept at interacting with customers on the bank's website, answering their questions and routing them to the right human representative. She typically engages in some 45,000 conversations a month and successfully answers eight out of 10 inquiries. Not only can Nina understand and mimic human speech, she can also use data to make connections and recommendations. "Nina's brain for Swedbank is educated on all things Swedbank," says Robert Weideman, EVP and GM of the enterprise division at Nuance Communications, which created Nina.