As a research scientist at IBM, Malioutov spends part of his time building machine learning systems that solve difficult problems faced by IBM's corporate clients. The team tried several different methods, including various kinds of neural networks, as well as software-generated decision trees that produced clear, human-readable rules. It was hospital policy to send asthma sufferers with pneumonia to intensive care, and this policy worked so well that asthma sufferers almost never developed severe complications. He and other computer scientists are importing techniques from biological research that peer inside networks after the fashion of neuroscientists peering into brains: probing individual components, cataloguing how their internals respond to small changes in inputs, and even removing pieces to see how others compensate.

Data is everywhere – masses of it. And it's helping businesses to make better decisions across departments. Marketing can utilise data to discover the effectiveness of email campaigns, Finance can analyse past trends to make predictions and projections for the future, and Sales can target their follow-up with detailed information on prospective customers. But data is only useful when business tools transform it into valuable information. Data intelligence through algorithms and analytics make business data relatable. The most advanced solutions require enormous amounts of data to be able to offer accurate insight to users.

Alexa can already order you an Uber, control your smart home devices, and keep you company. She's about to learn much better DJ skills, save you six bucks a month on streaming music, and possibly even change the way you listen to music in your house. Amazon Music Unlimited, a beefed-up subscription service built to compete with the likes of Spotify and Apple Music, launches today. It's cheaper than those big-name services--for many users, at least--and it features clever voice control with the company's Echo speakers. If you're using Music Unlimited on an Amazon Echo, Tap, or Dot, the service only costs 4 a month. To use it on anything else--mobile devices, your computer, a Fire TV stick, or even Sonos speakers--the pricing falls more in line with Spotify or Apple Music.

Billions of connected devices, zetabytes of data, power and brand loyalty now in the hands of the consumer, businesses having to market and sell to each and every one of us. How can any business make sense of it all? How can they learn and avoid making the same mistakes – and become smarter. Oh – and did I mention much of this needs to happen in real time? That's where Machine Leaning as part of a cognitive strategy comes in to its own.

A formal branch of artificial intelligence, machine-learning builds systems that learn directly from the data they are fed and effectively program themselves to analyse that data and make accurate predictions. Having already helped multiple business sectors create new models and drive competitive advantage, now it's the turn of the insurance industry. So just how is machine-learning changing the way insurers do business? "It gives insurers three distinct advantages," explains Max Richter, managing director in Accenture's UK insurance analytics group. "The first is to mine greater volumes of data, the second to scale analytics across the organisation by working smarter and faster, and lastly by answering more complex questions from'will this customer leave me at renewal?' to'what can I do about it?'" As such it is quickly becoming an essential tool for the insurance sector, specifically enabling companies to yield higher predictive accuracy as it can fit more flexible and complex models.

More and more, chatbots are entering the B2C world without consumers even realizing it's happening. But are we waiting for some big, wow-worthy, famous, life-changing chatbot in order for the concept to become mainstream? Chatbots are clearly not yet dinner table discussion topics. "There is no doubt that chatbots will become a critical onramp for brands to connect with customers," said Jake Bennett, CTO at POP. "Chatbots [are] giving brands a direct communication channel and storefront inside the apps that users already use every day. A recent study by Ovum reported that 53 percent of American and German respondents prefer chatting with businesses through chat apps, like Facebook Messenger, rather than speaking by phone with the business.

When someone important to us dies, we feel their loss keenly, and it can be difficult to let go of the pain we feel. People find different ways to cope – religion, focusing on happy memories, sometimes talking aloud to the departed person – even though they will never again receive a reply. But what if you could receive a reply? Eugenia Kuyda, the co-founder and CEO of a Russian artificial intelligence startup called Luka Inc (formerly IO), has developed a chatbot that lets anyone talk to her dearly departed best friend Roman Mazurenko, a fellow tech entrepreneur who died in a car accident in November 2015. Anyone who downloads the iOS mobile app Luka can instantly talk to the bot in either English or Russian by adding @Roman. You can select from the bot's options to learn about Mazurenko's career, or ask him questions to see how the bot responds.

"Artificial intelligence has some way to go before we see systems and robots as portrayed in the creative arts such as Star Wars. At present, 'AI machines' have narrow and specific roles, such as in voice-recognition or playing the board game'Go'. But science fiction is slowly becoming science fact, and robotics and AI look destined to play an increasing role in our lives over the coming decades. It is too soon to set down sector-wide regulations for this nascent field but it is vital that careful scrutiny of the ethical, legal and societal ramifications of artificially intelligent systems begins now." AI systems are starting to have transformational impacts on everyday life: from driverless cars and supercomputers that can assist doctors with medical diagnoses, to intelligent tutoring systems that can tailor lessons to meet a student's individual cognitive needs.

Artificial Intelligence, always a very polarizing subject, is back on top of the news. Unless you have been on a deep space mission for the past year, you have been exposed to opinions ranging from "this will change everything for the better" to "this will spell our doom". But what are the facts? Why is it seeing a resurgence now? How can I benefit from it?

If you're a video game fan of a certain age, you may remember Edge magazine's controversial review of the bloody sci-fi shooting game, Doom. Perhaps you enjoyed a good laugh, as many first-person shooter fans have, at the writer's much-mocked assertion: "if only you could talk to these creatures, then perhaps you could try and make friends with them, form alliances ... Now that would be interesting." Of course, we all know what happened. There would be no room in the Doom series, nor any subsequent first-person blast-'em-up, for such socio-psychological niceties. Instead, we enjoyed 20 years of shooting, bludgeoning and stabbing, the ludicrous idea of diplomacy cast roughly aside. But during this era, something else was happening in game design, and in academic thinking around video games and artificial intelligence. Buoyed by advances in AI research and aided by increasingly powerful computer processors, developers were beginning to think about the possibilities of non-player characters (NPCs) who could think and act in a more complex and human way – who could provide the emotional feedback that the Edge reviewer was thinking about.