It has been well documented that technology has played a major role in the Olympics this year in Rio. Athletes are using technology to train smarter, wearing specialized equipment to compete stronger and are recovering faster and more effectively all due to advances in technology and new innovations. Barbara Kendall has seen this transformation in a way in which few can relate. She competed in the 1992, 1996 and 2000 Olympics in Barcelona, Atlanta and Sydney and won gold, silver and bronze medals through her 25-year Sailboarding career. When her athletic career ended, she got into the technology world and is now a member of board of directors for an artificial intelligence (AI) company Arria NLG.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

The discovery by Tufts University biologists presents the first model of regeneration discovered by a non-human intelligence and the first comprehensive model of planarian regeneration, which had eluded human scientists for over 100 years. The work, published in the June 4, 2015, issue of PLOS Computational Biology, demonstrates how "robot science" can help human scientists in the future. In order to bioengineer complex organs, scientists need to understand the mechanisms by which those shapes are normally produced by the living organism. However, a significant knowledge gap persists between molecular genetic components identified as being necessary to produce a particular organism shape and understanding how and why that particular complex shape is generated in the correct size, shape and orientation, said the paper's senior author, Michael Levin, Ph.D., Vannevar Bush professor of biology and director of the Tufts Center for Regenerative and Developmental Biology. "Most regenerative models today derived from genetic experiments are arrow diagrams, showing which gene regulates which other gene. That's fine, but it doesn't tell you what the ultimate shape will be. You cannot tell if the outcome of many genetic pathway models will look like a tree, an octopus or a human," said Levin.

This week saw the placation of GST bill on logistics along with many more news such as evolvement of digital payments and artificial intelligence in E-commerce industry. The meeting of AI and e-commerce could not only transform the way jillions of online transactions are done, but also change the in-store purchase behaviors which are influenced by digital interactions. According to Sachin Bansal, CEO, Flipkart, artificial intelligence is a key differentiator in the fiercely competitive e-commerce business. Digital payments will grow 10 times to reach 500 billion by 2020 and contribute 15% of gross domestic product (GDP). Some of the key reasons of these acquisitions include privacy of customer's payment data, secured payment facility and use of payment data for big data analysis to the company.

Rush hour--the dreaded time of day when traffic conditions seem bent on making you late. As your car slowly creeps in line behind countless others stuck at a stop light, you think to yourself, "Why aren't these lights changing faster?" Traffic control scientists have long tried to solve this signaling problem. Unfortunately, the complexity of traffic situations makes the job extremely hard. A recent study suggests that machines can learn how to plan traffic signals just right to reduce wait times and make traffic queues shorter.

Analysis Artificial intelligence and machine learning engines are underpinning many emerging applications and services, from making sense of big data for enterprises, to supporting hyper-personalized consumer content, or virtual reality gaming. The current challenge is to move AI from the supercomputer to the mobile device, supporting technologies like computer vision locally on the handset, car, camera or VR headset. Qualcomm has been a leader here, but the past weeks have seen Intel and its Chinese partner Rockchip invest in chip-level computer vision and AI capabilities, while Apple has acquired machine learning startup Turi, presumably to enhance its AI-driven personal assistant Siri. Rockchip has licensed the XM4 imaging and vision DSP (digital signal processor) design from IP provider CEVA, to enhance these aspects of its system-on-chip (SoC) products. It says it will enable advanced vision features at the low power levels required for mobile devices, supporting digital video stabilization, object detection and tracking, and 3D depth sensing, among others.

The genetic cause of autism spectrum disorder is notoriously hard to research. Genetic markers for the disorder are tough to match from patient to patient because they're so rare--one of the most common genetic signifiers is only found in less than one percent of those diagnosed with autism. Even when genetic anomalies are found, they must be checked against family members genomes to ensure it's not attributable to a more commonly inherited mutation that doesn't cause disease. Researchers at Princeton and the Simons Foundation turned the traditional approach on its head, teaching a machine learning algorithm to look for the genetic relationships that could cause autism. The algorithm scoured a digital network of the human genome's interactions, looking for relationships and connections that are similar to those in previously-known markers for autism.

Data scientists and deep and machine learning researchers rely on frameworks and libraries such as Torch, Caffe, TensorFlow, and Theano. Studies by Colfax Research and Kyoto University have found that existing open source packages such as Torch and Theano deliver significantly faster performance through the use of Intel Scalable System Framework (Intel SSF) technologies like the Intel compiler and performance libraries for Intel Math Kernel Library (Intel MKL), Intel MPI (Message Passing Interface), and Intel Threading Building Blocks (Intel TBB), and Intel Distribution for Python (Intel Python). Andrey Vladimirov (Head of HPC Research, Colfax Research) noted that "new Intel SSF hardware and software in combination with code modernization delivered an observed 50x machine learning performance improvement in our case study". In the Colfax Research and Kyoto case studies as well as general Python scientific computing benchmarks, results run up to two orders of magnitude (100x) faster as a result of using Intel SSF technologies. Python is a powerful and popular scripting language that provides fast and fundamental tools for machine learning and scientific computing through popular packages such as scikit-learn, NumPy and SciPy.

In collaboration with the Norwegian University of Science and Technology (NTNU) and the leading research institute SINTEF, Telenor will establish a lab focused on artificial intelligence and big data at NTNU in Trondheim, Norway. As the second initiative, Telenor will develop and launch a dedicated, next-generation Internet of Things (IoT) network in several Norwegian cities. Norwegian startups and students will get cost-free access to the IoT network in order to develop and test their products and services. The first pilot will be located in Oslo, in collaboration with StartupLab. "We need to build critical competencies within artificial intelligence and we want to give Norwegian startups the resources they need to succeed. This is imperative for our ability to seize digital opportunities and contribute to creating new jobs. Startups play a key role in net job creation. We aim to stimulate productivity in Norway by developing new competencies and supporting the startup community," says Sigve Brekke, President and CEO, Telenor Group.

Humans are amazing creatures – driven by curiosity, intellect, ambition. The Olympic Games this month and the Nobel Prize Awards are examples of how our society reveres those who push their limits to achieve the seemingly impossible in both work and life. Digital advancements and new technologies are quickly redefining what is possible by accelerating human potential beyond the physical and intellectual capabilities of just a few years ago. But what can humans achieve with a little help from artificial intelligence? According to Erik Brynjolfsson, economist at MIT and the co-author of The Second Machine Age, "The accumulated doubling of Moore's Law, and the ample doubling still to come, gives us a world where supercomputer power becomes available to toys in just a few years, where ever-cheaper sensors enable inexpensive solutions to previously intractable problems, and where science fiction keeps becoming reality."