Google's DeepMind announced today that it was open sourcing Sonnet, its object-oriented neural network library. Sonnet doesn't replace TensorFlow, it's simply a higher-level library that meshes well with DeepMind's internal best-practices for research. Specifically, DeepMind says in its blog post that the library is optimized to make it easier to switch between different models when conducting experiments so that engineers don't have to upend their entire projects. To this avail, the team made changes to TensorFlow to make it easier to consider models as hierarchies. DeepMind also added transparency to variable sharing. It's in DeepMind's own interest to open source Sonnet.

The global market of artificial intelligence is anticipated to grow at a CAGR of over 60% during 2017-2022. On the basis of application, global artificial intelligence market has been broadly segmented into image recognition, natural language processing, speech recognition, gesture control & others. Among these categories, image recognition dominated global artificial intelligence market in 2016, and the segment is expected to maintain its dominance over the next five years as well. These machines are also capable of taking decisions by self-learning from the nearby environment. Global artificial intelligence market is expected to grow at a robust pace over the next five years, owing to its widespread implementation in numerous industries, such as automobile, finance, healthcare, consumer electronics, etc.

Cassini, the spacecraft that has been orbiting Saturn for 13 years, is running out of fuel and nearing the end of its mission. Over the next few months, Cassini will dive into the space between Saturn and its rings, moving closer and closer to the planet until it eventually disintegrates in its atmosphere in September. This week, NASA released a short animation showing these final moments, set to a majestic, brassy overture.

SmartCompany readers believe data analytics, artificial intelligence (AI), automation and the Internet of Things are set to be the biggest disruptors of business in the next decade -- although autonomous vehicles aren't even close to registering as a disruption yet. But SMEs will need to do more in order to harness the power of analytics and use it to drive profit-driven decision making, one expert warns. These findings come as part of SmartCompany's annual SME Directions Survey, sponsored by Netsuite Oracle, which questioned more than 700 small business respondents to gauge their views on the future of their businesses and the state of the market in the year ahead. The businesses surveyed come from all states and territories and a wide range of industries. The findings show SMEs are clearly cognisant of the disrupting forces coming in the next decade, even though many are not immediately threatened.

In the latest attempt to figure out what consumers want and how much they are willing to pay to get it, a "narrative analysis" platform launched this week crunches "cross-platform data sets" to divine consumer "beliefs and motivations." San Francisco-based Protagonist (formerly Monitor 360) said this week its platform leverages machine learning and natural language processing to gauge the "narratives that impact a given market." Narratives are defined as "consumer beliefs that drive behavior." The platform, which combines data science with social science to reveal consumer "beliefs at scale," is aimed at chief marketing officers and advertisers. It is also intended to replace traditional market research tools such as focus groups, customer surveys and social media campaigns.

It is approximately 50 years since the first computational experiments were conducted in what has become known today as the field of Genetic Programming (GP), twenty years since John Koza named and popularised the method, and ten years since the first issue appeared of the Genetic Programming & Evolvable Machines journal. In particular, during the past two decades there has been a significant range and volume of development in the theory and application of GP, and in recent years the field has become increasingly applied. There remain a number of significant open issues despite the successful application of GP to a number of challenging real-world problem domains and progress in the development of a theory explaining the behavior and dynamics of GP. These issues must be addressed for GP to realise its full potential and to become a trusted mainstream member of the computational problem solving toolkit. In this paper we outline some of the challenges and open issues that face researchers and practitioners of GP.

Educational, training institutions and eLearning content publishers must adapt themselves to the new technological landscape in order to keep their courses and learning materials relevant to today's learners. The development of educational mobile apps provides exciting new ways to develop educational courses that are both effective in reaching educational objectives for teachers and rewarding to the online learner. This presentation will serve as a guide for managers at learning organizations into ways to adapt courses for the multi-screen and multi-device app based environment that today's learners engage in. Mobile devices are outpacing traditional desktop environments when it comes to accessing the web. In fact, 60% of search queries are now done through mobile devices (source: SearchEngineLand).

In this tutorial we covered some of the basic concepts of machine learning and why it can be a useful thing. How do we install the required libraries in our system for machine learning? What type of data is provided to the machine to train it and how does it make the prediction? In the upcoming tutorial, we will use data to train the machine using different algorithms. Different models for machine learning will be used to train the machine and we will make predictions by querying our machine. After the next tutorial you will be able to train the machine using Python libraries. You will also be able to use different models of machine learning which can be used train machines.

The study provides preliminary data to support a nascent movement to utilize teleconcussion equipment at all school sporting events where neurologists or other concussion experts aren't immediately accessible. "I see teleconcussion being applicable anywhere in the world," said Dr. Bert Vargas, the study's lead author, who directs the sports neuroscience and concussion program at the O'Donnell Brain Institute at UT Southwestern Medical Center. Concussion awareness has moved to the mainstream of national dialogue in recent years, fueled by revelations that former NFL players suffered permanent damage to their brains due to repeated head impacts. Having personnel on hand to quickly identify and remove concussed players from games is an important part of protecting against such long-term injuries, Dr. Vargas said. But across the country -- and most notably in rural regions -- more than half of public high schools don't have athletic trainers available to spot such incidents, increasing the chances that a concussion could go unnoticed and perhaps be exacerbated by additional injuries.

At last year's Bafta Game Awards, the developer of Her Story, Sam Barlow, famously so struggled with his three awards that he carried them around in a champagne bucket. This year, indie developer Playdead went one better by winning four for their dystopian puzzle platformer Inside: Artistic Achievement, Game Design, Narrative, and Original Property. After their previous game, Limbo, won none from four in 2011, the team at Playdead were delighted to take home so many this year: "We kind of expected to continue the clean slate, so we're very happy." Inside just missed out on the award for Best Game which went to Uncharted 4, continuing a tradition of big-budget titles walking away with the top prize (Fallout 4 in 2016 and Destiny in 2015). It was the second Best Game win in five years for Uncharted 4's developer Naughty Dog after The Last of Us won in 2013.