How can we help millions of chronically ill patients lead healthier lives with fewer hospitalizations? Parsing through individual patient remote monitoring data doesn't seem like a scalable solution. But what if artificial intelligence could rapidly analyze this information and predict an individual's health problem, such as worsening heart failure, in time for caregivers to intervene and prevent an emergency department visit or hospital admission? That may sound like a pipe dream, yet the technology to make it happen already exists. This new "prescription" for chronically ill patients would be an algorithm -- a personalized disease model unique to each patient, based on streams of data collected from biosensors worn by patients.

Tesla and SpaceX owner Elon Musk, is now establishing an artificial intelligence'gym' for developers to train their AI systems through a series of games and challenges. Under Musk's 1 billion non-profit OpenAI initiative, the gym is now available as open source code and provides'environments' for developers to test their new AI bots. This includes 59 Atari games including the popular Alien, Air Raid, Asteroids and Pac-Man. The results from these test environments will be compiled by OpenAI into a list of the top performing systems. Instead of ranking the AIs by high scores, the systems will be judged on versatility.

When we think of innovators of the technology space we largely think of blokes like Mark Zuckerberg, Bill Gates, Steve Jobs, Elon Musk – the zeitgeist is largely male. But that hasn't always been the case. As a matter of fact, for the first decade or so programming was a'pink-collar' industry. The vast majority of early coders were women. What's more, it's an industry created by women.

Oussama Khatib held his breath as he swam through the wreck of La Lune, 100 meters below the Mediterranean. The flagship of King Louis XIV sank here in 1664, 20 miles off the southern coast of France, and no human had touched the ruins – or the countless treasures and artifacts the ship once carried – in the centuries since. With guidance from a team of skilled deep-sea archaeologists who had studied the site, Khatib, a professor of computer science at Stanford, spotted a grapefruit-size vase. He hovered precisely over the vase, reached out, felt its contours and weight, and stuck a finger inside to get a good grip. He swam over to a recovery basket, gently laid down the vase and shut the lid.

PA's automation experts, Helena Moren and Simon Andersson, have had an article published in NyTeknik about the rise of smart machines and how Swedish companies are lagging behind that trend. The article outlines how robots and artificial intelligence will have a significant impact on business and finance, with the market for smart machines expected to be worth approximately SEK 130 billion by 2020. While predicting robots' impact on the labour market is more difficult, there is a high probability that the robots will bring new, high-end jobs and greater freedom for mankind. Helena and Simon explain that robotisation can release a comprehensive range of resources and can be used to increase efficiency and productivity. But, as revealed in a report presented at the Davos summit in January, Swedish companies are falling behind in this digitisation, mainly because they are not efficiently resourced to make these developments.

Steve Wozniak tells the innovation summit that artificial intelligence researchers are getting close to the point of understanding "what the brain is". The man who helped bring Apple computers to the world says we're on the verge of an artificial intelligence revolution. Apple co-founder Steve Wozniak told an innovation summit in Brisbane artificial intelligence would be the next big disrupter, separate from the digital revolution that changed the world with personal computers and smartphones. Speaking via video link from the US, "The Woz" described AI as "machines acting like human friends". An attendee at the Brisbane summit films Mr Wozniak's broadcast.

The tech world's spotlight turned to chatbots after Facebook announced the launch of their own bot store on the Messenger platform at the F8 conference in April 2016. A few weeks later, the news has been covered extensively. It has also generated a lot of criticism. The two main arguments against are that this is nothing substantially new and that chatbots give only approximative answers. These hasty criticisms are due to the fact that most people haven't quite grasped the real concept behind the Messenger bot store.

Machine Learning is now on top of the Gartner hype cycle, and almost everyone in the world of digital marketing or e-Commerce talks about it or, at least, has heard about it. But although this term is discussed quite often, only a few do really know what it is or what it can do for them. Even less are aware about its limits. Within this article, we want to shed light on this dark through introducing you to the concept of machine learning, showing its application in online shops and comparing it to Operational Intelligence and Prescriptive Analysis for a better understanding. Basically, Machine Learning is a part of Artificial Intelligence (AI) that generates knowledge from experiences, i.e. historical data.

How easy it is to build a learning machine? Shouldn't one just hire some Machine Learning PhDs and have them run their algorithms? Well, this is most probably a good idea, but it won't be enough. I'll try to explain why in this blog entry. Before answering our questions, let's define what we are dealing with.

Artificial intelligence (AI) and machine learning are no longer story lines for science fiction. They are very much a part of our daily lives. Players like MadStreetDen, SnapShopr, and now Streamoid Technologies' piQit Fashion have brought AI into our everyday fashion shopping. Founded in 2013, Streamoid Technologies began operations in mid-2014 and is now present in India and the US. Their platform piQit Fashion uses a combination of human and machine intelligence to solve many problems commonly found in fashion retail.