That's the conviction held by Russian entrepreneurs Artem Kukharenko and Alexander Kabakov, whose startup, NTechLab, recently launched a facial recognition app that nearly obliterates the concept of anonymity. Called FindFace, the app has remained exclusive to Russia since going live earlier this year. Soon, though, Kuhkarenko and Kabakov are introducing a cloud-based platform that makes their frighteningly accurate algorithm available to everyone, the pair said in a Skype interview in May. In a practical sense, what this means is that none of us is safe from an always-probing public eye. "In 10 or 20 years, there won't be a place on the earth [where] ... nobody [can] see you," Kabakov said over Skype.

Deep learning and artificial intelligence are set to be the next big innovations that change the way that people run their businesses. At Shopify's Tech @ Scale in Toronto -- an event that included a day full of talks exploring how developers and engineers could stay agile in a world of fast-moving technology -- one talk included expert insights on exactly how these emerging technologies would impact both businesses and their customers. "The fabric of the internet is not ready to scale for what's coming. If you think of the components we built our service on top of, the one part that is not ready to scale is security because it is the most centralized." Chris Matys, chief analytics officer at Georgian Partners, moderated a panel featuring Damian McCabe, VP of Engineering at Connected Lab; Hesham Fahmy, VP of Technology at ecobee; Inmar Givoni VP of Big Data at Kobo; and Karl Martin, co-founder and CTO of Nymi.

The Google DeepMind challenge match in March 2016 was a historic achievement for computer Go development. This article discusses the development of computational intelligence (CI) and its relative strength in comparison with human intelligence for the game of Go. We first summarize the milestones achieved for computer Go from 1998 to 2016. Then, the computer Go programs that have participated in previous IEEE CIS competitions as well as methods and techniques used in AlphaGo are briefly introduced. Commentaries from three high-level professional Go players on the five AlphaGo versus Lee Sedol games are also included. We conclude that AlphaGo beating Lee Sedol is a huge achievement in artificial intelligence (AI) based largely on CI methods. In the future, powerful computer Go programs such as AlphaGo are expected to be instrumental in promoting Go education and AI real-world applications.

For complex, high-dimensional Markov Decision Processes (MDPs), it may be necessary to represent the policy with function approximation. A problem is misspecified whenever, the representation cannot express any policy with acceptable performance. We introduce IHOMP : an approach for solving misspecified problems. IHOMP iteratively learns a set of context specialized options and combines these options to solve an otherwise misspecified problem. Our main contribution is proving that IHOMP enjoys theoretical convergence guarantees. In addition, we extend IHOMP to exploit Option Interruption (OI) enabling it to decide where the learned options can be reused. Our experiments demonstrate that IHOMP can find near-optimal solutions to otherwise misspecified problems and that OI can further improve the solutions.

We introduce the Adaptive Skills, Adaptive Partitions (ASAP) framework that (1) learns skills (i.e., temporally extended actions or options) as well as (2) where to apply them. We believe that both (1) and (2) are necessary for a truly general skill learning framework, which is a key building block needed to scale up to lifelong learning agents. The ASAP framework can also solve related new tasks simply by adapting where it applies its existing learned skills. We prove that ASAP converges to a local optimum under natural conditions. Finally, our experimental results, which include a RoboCup domain, demonstrate the ability of ASAP to learn where to reuse skills as well as solve multiple tasks with considerably less experience than solving each task from scratch.

Three early-career engineers who are making a big difference in three very different areas of technology are to receive the Royal Academy's prestigious Silver Medal at the Academy Awards Dinner at the Tower of London on Thursday 23 June 2016. The Silver Medal celebrates outstanding personal contributions to UK engineering, which has resulted in successful market exploitation. Professor Dame Ann Dowling OM DBE FREng FRS, President of the Royal Academy of Engineering, says: "Damian Gardiner, Demis Hassabis and Tong Sun have all demonstrated the power of use-inspired research in taking ideas they have developed in academia and applying them to solve real-world problems. They are working with colleagues all over the world and making an enormous impact early in their careers that is both enriching academic knowledge and generating real economic benefit for the UK." Dr Damian Gardiner is taking the world of product authentication by storm, with his Cambridge University start-up company ilumink Limited acquired by Johnson Matthey's Process Technologies Division in 2015. They were keen to adopt his unique method of printing'liquid crystal' material onto any surface using an ink-jet printer.

There are huge advancements in information and communications technology and these have changed how we work and live. Technologies such as blockchains are shaping the future of banking with potential applications in the health and other sectors. Books like the Augmented have predicted what the future societies will be like considering the Internet of things (IOT), our cars will not need drivers, the computers might not need keyboards anymore as it would recognise our voices and obey our commands, we may be selective in the kind of friends we keep as we can have meaningful conversations with chat bots considering the huge gains made in Artificial Intelligence (AI). It is with fascination that we watch these advancements in technologies and a huge shift from the socio-cultural norms which is being experienced in every sphere of our life, we do not need physical presence to open bank accounts anymore, we have apps that track our spending, apps that prepare our shopping list based on our shopping patterns, tell us the best deals and even place orders, we anticipate a time when wearable health devices will alert us about something happening to our body before we even know; devices will alert doctors and carers before a patient have a heart attack. What a beautiful future – "life in the smart lane" Brett King (2016), but how evenly distributed is the anticipation for the augmented?

From guide dogs for the visually impaired to search-and-rescue animals, canines can be trained to help with a wide range of critical tasks. So, it might come as no surprise that researchers are now designing machines to learn more like dogs. Computer scientists have modeled machines to learn like dogs, with the short-term goal of improving human interactions with robots and the long-term hope of more efficiently training service animals. These machines rely on human feedback. Real animal trainees, like dogs, also provide helpful, subtle cues about their understanding to human trainers, and now that aspect of a training relationship is being transferred to machine learning.

Israel's General Robotics has developed tiny'combat robots' that can climb stairs, traverse difficult terrain, and perform with greater accuracy than a human. Called'Dogo,' the remote-controlled system is equipped with a fully loaded Glock pistol and eight cameras to create a 360 degree view. Despite its small size, the lightweight robot is designed to go up against a range of targets, allowing it to aim at a standing person or even hit an enemy hiding under the bed. Israel's General Robotics has developed tiny'combat robots' that can climb stairs, traverse difficult terrain, and perform with greater accuracy than a human. Dogo contains a 9mm Glock pistol and has enough batter power to complete a 2-5 hour mission.

"Alexa, ask Pebble how the Kickstarter campaign is doing." Today, we're very excited to announce that integrated Amazon Alexa support is coming Pebble Core! Core will be the first truly independent 3G wearable to give you the magic of Alexa on the go. Ask for your latest workout summary, catch up on current news, check the weather, or change your tunes--Alexa has you covered with its ever improving set of skills. Pebble Core streams music from Spotify, tracks your workouts with GPS, and now gives you the power of Alexa--all from the palm of your hand. Back the first truly connected ultra-wearable on Kickstarter, starting at 69.