Artificial Intelligence (AI) or machine learning can be used to help improve the accuracy of the diagnosis in lung diseases, finds a study. Machine learning utilizes algorithms that can learn from and perform predictive data analysis. The team developed an algorithm process in addition to the routine lung function parameters and clinical variables of smoking history, body mass index (BMI) and age. Based on the pattern of both the clinical and lung function data, the algorithm makes a suggestion for the most likely diagnosis. "We have demonstrated that AI can provide us with a more accurate diagnosis. The algorithm can simulate the complex reasoning that a clinician uses to give their diagnosis, but in a more standardized and objective way so it removes any bias," said Wim Janssens from the University of Leuven in Belgium.

It certainly has been another long week in cybersecurity. First, news that a third party hacked a group allegedly connected to the NSA and made off with secret "hacking tools" rocked the industry. It was shortly followed by news of cyber attacks in the form of smart email "bombs" raining down upon the mailboxes of .gov News of new ransomware-as-a-service platforms added to the headache, as did news of two big PoS hacks where credit card information may have been stolen from retailers, hotels and restaurants. As summer wanes and stretches towards Labor Day, it will also be hard to forget the hack of the servers at the Democratic National Committee.

The technology-minded capital markets participants do love a good trend. If 2014 was centered around "IBOR-mania" and 2015 was the year that the blockchain exploded into the hyperbole stratosphere, then the major trend of 2016 will arguably be machine learning. It may sound like the sexy new foundation upon which so much of asset management's future can be built, but at heart, machine learning is a data efficiency play, one that many on the buy side are still unable to get right for a variety of reasons. While no one wants to get left behind when it comes to the application of new technology, in this case it really will be those firms that have come to grips with the questions posed by big data management that will have the head start in machine learning. One of the key distinctions to make on this subject is the differentiation between machine learning and artificial intelligence; the former is concerned with automating processes and associated troubleshooting, such as documentation completion or trade confirmation, while the latter mainly concerns the application of that automation--for example, sending out the right information to investors or clients based on historic trends.

The world's largest artificial intelligence body, the European Association for Artificial Intelligence (EurAI), has appointed UCC's Prof Barry O'Sullivan as its deputy president. Professor O'Sullivan is director for the Insight Centre for Data Analytics, and UCC's chair of Constraint Programming. He leads Insight's research group on optimisation and decision analytics, and is responsible for Insight's strategic engagement in European initiatives, such as Horizon 2020. Professor O'Sullivan has been involved in winning over 140 million in research funding, of which approximately 25 million has directly supported his research activities at UCC. EurAI has more than 4,500 members across more than 30 countries, making it the largest AI organisation in the world. The primary objective of the association is to promote research in, and study of, artificial intelligence, as well as representing the AI community externally.

The system is called Recognition and will be running for three months in London up to 27 November 2016. A nice touch is that it will also take in feedback from matching selections made by viewers themselves at the art museum on Millbank. Created by Fabrica, it's the winner of the IK Prize 2016 for digital innovation, awarded by Tate Britain, in partnership with Microsoft. A display at Tate Britain accompanies the online project offering visitors to the gallery the chance to compare the machine's matches with their own and invites them to help retrain the algorithm. The experiment will explore whether an artificial intelligence programme can learn from the many personal responses humans have when looking at images.

Lenovo Group Ltd, the world s largest personal computer maker, will launch its augmented-reality-enabled smartphone in October in China, as part of its broad efforts to boost phone sales with innovative products. Yang Yuanqing, CEO and Chairman of the Beijing-based company, said on Saturday the Phab2 Pro, the world s first smartphone to host AR applications without the need of other accessories, will help create new business models by bringing new interactive experience to consumers. The new device, first unveiled in June, is based on Google Inc s Tango project and allows users to play virtual dominoes on a physical table and shoot digital robots that inhabit users living rooms. "Technology innovation and business model innovation are part of the new path for growth," Yang said, adding the company aims to leverage cutting-edge technologies to change the way people live and work. He made the comments at the B20 summit which was held in Hangzhou, capital of Zhejiang province on Saturday.

One of the country's biggest law firms has become the first to publicly announce that it has "hired" a robot lawyer to assist with bankruptcy cases. The robot, called ROSS, has been marketed as "the world's first artificially intelligent attorney." ROSS has joined the ranks of law firm BakerHostetler, which employs about 50 human lawyers just in its bankruptcy practice. The AI machine, powered by IBM's Watson technology, will serve as a legal researcher for the firm. It will be responsible for sifting through thousands of legal documents to bolster the firm's cases.

It is hyperbole to say deep learning is achieving state-of-the-art results across a range of difficult problem domains. There is a lot of excitement around artificial intelligence, machine learning and deep learning at the moment. It is also an amazing opportunity to get on on the ground floor of some really powerful tech. I try hard to convince friends, colleagues and students to get started in deep learning and bold statements like the above are not enough. It requires stories, pictures and research papers.

Like most things that are over-hyped, what is actually meant by the term is often lost in the noise. In this case that's really a shame, because these terms refer to at least two different things, either or both of which may be important in a given context. This post forms the basis of a lightning talk I'm giving (remotely) at the Real-time Big Data Meetup in Menlo Park, California. Generally, when I hear people talking about "machine learning from streaming data", they may be talking about a couple of things. These two phenomena sound like the same thing, but they are potentially very different.

Leaders should always be asking themselves What's new?, What's next? and What's better?; that's where the future is. What technologies will drive the biggest changes in industries over the next 10 to 20 years and create the next economy? There are many that in combination will drive massive change across enterprises and all size of business. Specifically, I think 10 are essential, and shaping the industries of the future: drones, blockchain, big data, augmented reality, virtual reality, 3D printing, artificial intelligence, robots, internet of things, genetics. We will see them both in the consumer and enterprise domain; specifically in how we get stuff done, how we hire and how we collaborate.