SAP SE is exploring augmented reality and intelligent assistant software in initiatives intended to boost employee productivity, according to new SAP CIO Thomas Saueressig, who at 31 is the youngest CIOworking for a global 2000 company. More productive employees will ultimately improve the business software maker's ability to serve customers, one of the German company's core tenets. "I fundamentally believe that the new generation and the expectations of our customers and our employees are changing so significantly," says Saueressig, who took over for Helen Arnold on May 1. "And we need to shift our focus purely on the end-user [employees and customers]." Saueressig is something of a rarity among first-time IT leaders. As a millennial, he is a member of a generation HPE CEO Meg Whitman describes as as supremely confident if not entitled.

Artificial intelligence has produced sound so realistic it can fool human ears. Using machine learning, AI learned how to recreate the precise sounds of objects being hit with a drumstick after MIT researchers fed thousands of examples. Human subjects had difficulty distinguishing between the algorithm's sounds and real ones - and actually chose the AI's twice as many times during the online study. MIT researchers fed a massive audiovisual dataset of objects being hit with a drumstick to their AI, which detected patterns in the sounds and learned how to recreate each one. Although there are limitations, human subjects had difficulty distinguishing between the algorithm's sounds and real ones In order to train this sound-producing algorithm, MIT needed to feed it sounds to learn.

Claned Co-founder Vesa Perala believes that instead of attempting to retrofit technology to out-dated educational systems, EdTech start-ups should be helping to write a new rulebook. For the past 3 years, Claned has been in what he describes as semi-stealth mode, focusing on developing a robust artificial intelligence system that uses machine-learning algorithms to map out what factors most impact individual learning. That knowledge, he says, was already out there, because it's something universities routinely do. Over time, tutors build an understanding of how each student learns, yet that data is trapped in a system which simply isn't scalable. Claned set out to solve this by combining these tried-and-tested academic evaluation metrics with machine learning algorithms and Artificial Intelligence.

The market research firm expects the attach rate of AI-based systems in new vehicles to increase from 8 percent in 2015 (the vast majority of today's AI systems in cars are focused on speech recognition) to 109% in 2025. IHS sees multiple AI systems of various types to be installed in many cars. In the human-machine interface in vehicles, IHS believes AI will play a role in speech and gesture recognition, eye-tracking, driver monitoring and natural language interfaces. In the autonomous car, AI will advance machine vision systems, while it will also migrate in sensor fusion engine control units (ECU). In a phone interview with EE Times, Luca De Ambroggi, principal analyst, automotive semiconductors at IHS told us, "AI is viewed as a key enabler for real autonomous vehicles. Everyone in the automotive supply chain is getting pretty bullish."

Developers are increasingly adopting intelligent, automated systems in the data center as they seek to offload manual processes in order to keep up with the accelerating pace of IT operations. That conclusion was taken from a new survey of IT executives about the adoption of intelligent, AI-based systems and machines in the enterprise. However, the survey, sponsored by IT management software firm Ipswitch Inc., warned that early adopters have not yet gotten to grips with the security and access risks posed by delegating tasks to bots and other autonomous systems. "IT decision makers recognize that, while a force for good, these technologies also expose the enterprise to new internal and external risk vectors," said Tony Lock, an analyst with survey author Freeform Dynamics Ltd, in a statement. "As the pace of adoption increases, there will be no escaping the impact of intelligent systems on the enterprise, regardless of whether or not organizations directly invest in such technologies."

This undated image provided by the Orlando Police Department shows Omar Mateen, the shooting suspect at the Pulse nightclub in Orlando, Fla., Sunday, June 12, 2016. The gunman opened fire inside the crowded gay nightclub early Sunday before dying in a gunfight with SWAT officers, police said.

Hierarchy is an important organizational property in many biological and man-made systems, ranging from neural [1, 2], ecological [3], metabolic [4], and genetic regulatory networks [5], to the organization of companies [6], cities [7], societies [8], and the Internet [9, 10]. There are many types of hierarchy [11–13], but the one most relevant for biological networks [14, 15], especially neural networks [1, 2, 16], refers to a recursive organization of modules [10, 13]. Modules are defined as highly connected clusters of entities that are only sparsely connected to entities in other clusters [17, 19, 20]. Such hierarchy has long been recognized as a ubiquitous and beneficial design principle of both natural and man-made systems [14]. For example, in complex biological systems, the hierarchical composition of modules is thought to confer greater robustness and adaptability [1, 2, 16, 21], whereas in engineered designs, a hierarchical organization of simple structures accelerates the design, production, and redesign of artifacts [19, 22, 23].

Hindsait's AI platform identifies and extracts actionable data from information trapped in clinical notes and other electronic records for improved patient outcomes at lower costs Based on its recent analysis of the market for artificial intelligence (AI) systems for the healthcare industry, Frost & Sullivan recognizes Hindsait, Inc. with the 2016 Global Frost & Sullivan Award for Visionary Innovation Leadership. Hindsait has demonstrated a strong commitment to breaking down communication barriers and enhancing healthcare delivery using AI and cognitive computing technology. With its novel software-as-a-service (SaaS) platform, Hindsait helps payers reduce costs and improve the quality of services while simultaneously enabling healthcare providers, such as accountable care organizations (ACOs) and hospitals, to reduce risks and offer superior, more affordable care. Although there are organizations that apply AI and cognitive computing in healthcare, many of them simply adapt approaches applied in other industries to healthcare. Hindsait, on the other hand, is dedicated to the needs of the healthcare industry.

Why start with Weka over another tool like the R environment or Python for applied machine learning? In this post you will discover why Weka is the perfect platform for beginners interested in rapidly getting good at applied machine learning. Rapidly Accelerate Your Progress in Applied Machine Learning With Weka Photo by Jonathan Riddell, some rights reserved. When you start out in applied machine learning, there is so much to learn. Often you need to learn a new programming language, like python or more esoteric languages like Matlab or R. It is so much easier to learn one thing well rather than try, and possibly fail to learn a host of new things.

A new method of assembling tyres that promises to improve quality and productivity while eliminating the risk of human error has been introduced within a Bridgestone Corporation plant in Japan. The tyre maker has announced the installation of the new Examation system at its flagship Hikone passenger car tyre production site. The tyre maker reports that Examation "combines Bridgestone's proprietary information and communication technologies with artificial intelligence." The proprietary technologies Bridgestone refers to have been developed in stages over the past two decades: Research into tyre production systems employing ICT and other cutting-edge technologies began at Bridgestone in the late 1990s with the aim of creating more functional tyres and improving quality. In 2002, the company developed the BIRD (Bridgestone Innovative and Rational Development) production system, which was the world's first system for realising complete automation in areas of production ranging from components processes to product inspection processes.