If you're a dating app regular, you know that a photo only says so much about yourself. But do you really want to go to the trouble of recording a whole video for people who could swipe left before you've even spoken a word? Tinder thinks there's a better balance between the two. It's launching a Loops feature that (surprise) adds two-second looping videos to your profile alongside the usual still shots. You just have to trim an existing video to portray yourself as a fun-loving party person or tender romantic. The feature is initially available for iOS users in the US, UK, Canada and large chunks of Western Europe, Asia and the Middle East.

Researchers at the University of Wyoming are working with online community Snapshot Serengeti to develop artificial intelligence that can identify, count and describe wild animals in Tanzania. Over 3.2 million pictures of animals - captured by hidden cameras - have been identified by Snapshot Serengeti volunteers and the data collected is being used to power the AI algorithm, using deep neural networks.

In Serengeti National Park, there are 225 hidden cameras constantly photographing the creatures that roam this Tanzanian wilderness. To date, these camera traps have captured more than three million images. Through Serengeti Snapshot, as the program is called, they've studied everything from the migrations of the region's herbivores to the surprising co-existence of lions, hyenas, and cheetahs. It's work that wouldn't have been possible without an army of 30,000 citizen scientists, who manually sorted the collection, identifying and naming the species in each frame. It's time-consuming work, and the volunteers are doing it for kicks.

Groupe PSA and Inria today announced the creation of an OpenLab dedicated to artificial intelligence. The studied areas will include autonomous and intelligent vehicles, mobility services, manufacturing, design development tools, the design itslelf and digital marketing as well as quality and finance. "Artificial intelligence will quickly become an efficiency factor for the group. The OpenLab will work on artificial intelligence algorithms enabling autonomous vehicles to drive in complex environments for example. It will also work on predictive maintenance, powertrain design optimisation and the modelling of complex systems such as cities, to offer mobility services adapted to people's needs" said Carla Gohin, Groupe PSA's Vice President for Research and Advanced Engineering. Inria's project teams will participate in this OpenLab bringing their high-level algorithmic expertise as part of a fruitful dialogue with Groupe PSA's experts on all the identified topics.

The newly established Center for the Fourth Industrial Revolution in the Japanese capital aims to update old regulations that hinder effective usage of cutting-edge technologies and accelerate social change by developing appropriate policy frameworks for a rapidly changing society, said Chizuru Suga, who heads the institution. "In short, what we are trying to do is like determining the size of a soccer goal before playing the game. We are trying to set up common policy frameworks that help people play a fair game," she said during a recent interview with The Japan Times. "Today's technology has been advancing so fast that no one could have been able to catch up with the most up-to-date movement and set the rules … to benefit as many people as possible," said Suga, originally from the Ministry of Economy, Trade and Industry (METI). The Tokyo facility, which opened Monday, is the first sister institution of the Center for the Fourth Industrial Revolution in San Francisco.

On 5 July 1948, 70 years ago on Thursday, the National Health Service (NHS) was born. We look at seven decades of the development of the NHS, alongside medical advancements, highlighting events that have been documented with archive photography. After the planning of an ambitious project to bring healthcare to everyone in the UK, the NHS was launched by Aneurin Bevan, the Health Secretary of the post-War Labour government. Bevan, seen below in 1945, was the chief architect of the plan to bring together hospitals, doctors, nurses, pharmacists, opticians and dentists under the umbrella of one organisation. The services were available to everyone, financed entirely from taxation with the central principle being that people would pay according to their means.

We revisit logistic regression and its nonlinear extensions, including multilayer feedforward neural networks, by showing that these classifiers can be viewed as converting input or higher-level features into Dempster-Shafer mass functions and aggregating them by Dempster's rule of combination. The probabilistic outputs of these classifiers are the normalized plausibilities corresponding to the underlying combined mass function. This mass function is more informative than the output probability distribution. In particular, it makes it possible to distinguish between lack of evidence (when none of the features provides discriminant information) from conflicting evidence (when different features support different classes). This expressivity of mass functions allows us to gain insight into the role played by each input feature in logistic regression, and to interpret hidden unit outputs in multilayer neural networks. It also makes it possible to use alternative decision rules, such as interval dominance, which select a set of classes when the available evidence does not unambiguously point to a single class, thus trading reduced error rate for higher imprecision.

Suddenly it's all about small- and medium-sized businesses (SMEs) as this oft-overlooked sector of the global economy now takes center stage. In the FinTech world, a swathe of products are being launched to suit the sector, be that blockchain-based ideas to speed up invoice payment or access to capital funds that were previously unavailable. Now the AI world is joining in with promises of predicting consumer behavior geared towards SMEs who have to compete with tech giants that mop up the best data scientists and their algorithms. The current state of play means SMEs find it hard to compete with the cost, complexity and consulting taken by big enterprises. So step forward tech company Xineoh that says it has developed a platform for predicting customer behaviour with AI'which allows businesses to out-predict their competition thus allowing them to maximize efficiency and customer satisfaction'. Its so-called bespoke AI solutions on Xineoh's platform can be implemented rapidly without the cost, complexity and consulting required by other methods.

Artificial Intelligence (AI) may conjure up images of robots and science fiction. But AI has practical applications in today's data-driven organization for product recommendation engines, customer support, inventory management, and more. To support AI in order to drive concrete business outcomes, a strong data foundation is needed. This webinar will discuss practical applications for AI in your organization, and how to build a data architecture to support its use. Donna Burbank is a recognized industry expert in information management with over 20 years of experience helping organizations enrich their business opportunities through data and information.