AMD is finally making its first moves into deep learning. Google will start equipping its sprawling data center infrastructure with AMD's graphics processing units (or GPUs) to accelerate deep learning applications, AMD announced on Tuesday at a supercomputing conference in Salt Lake City, Utah. GPUs, typically used for generating the latest in gaming graphics, have been booming in deep learning, which is a flavor of artificial intelligence where the computer teaches itself how to do certain tasks. GPUs have caught on because of their capabilities in "parallel computing," a technique that involves multiple calculations happening simultaneously. That makes GPUs much faster at running deep learning neural nets than more generalized processors.

Artificial intelligence (AI) is not only the next big wave in computing – it's the next major turning point in human history. Similar to how machine tools, factory systems and steam power ushered in the Industrial Revolution, changing every aspect of daily life in some way, the Intelligence Revolution will be driven by data, neural networks and computing power. AI will extend our human senses and capabilities to teach us new things, enrich how we interact with the world around us, and improve our decision-making. AI is changing our world for the better, and Intel is uniquely capable of enabling and accelerating AI technology. We will see unprecedented developments in medicine, scientific discovery, education and how work gets done.

One of the most popular acronyms of the decade - IoT actually stands for Internet of Things but due to the rising cyber crime cases in the past few years, many are decoding it as Internet of Threats. Cybersecurity Ventures, a pioneer organisation in the field of internet security, claims that cyber crime is going to increase the world expenses up to 6 trillion USD annually by 2021. Today, hackers are not only targeting the corporate data, but they are also threats to the security of various countries. Recently, they managed to steal the details of a deal between the Indian Navy and French submarine maker'DCNS' even before the deployment of Scorpène submarines. How Pandemic is IoT Threats From financial institutions to defence research agencies all are under the radar of malicious hackers and spies.

Many day-to-day business processes could benefit from a better understanding of company contracts, which even for mid-sized companies often number in the thousands. The processes, procedures, and technologies that make up e-discovery are well-suited to delivering those benefits. The process starts with a foundation provided by e-discovery and its document review specialists, processes, and technologies, augmented by artificial intelligence (AI) that allows attorneys to teach analytics software to recognize and interpret contract provisions. An AI-powered contract review application applies this training to contracts it hasn't seen before, resulting in the extraction of key contract provisions. Technology-aided contract review is a natural companion to e-discovery and conventional contract management tools.

Wildlife advocates began testing an advanced system this spring to better identify and apprehend poachers. They say the technology has led to dozens of arrests that wouldn't have happened otherwise. Brian Heath, chief executive of the Mara Conservancy in Kenya, believes expanding the use of the technology throughout Africa could significantly improve anti-poaching efforts. "Our rangers now feel completely disadvantaged and blind without it," Heath said. "They get a huge amount of reassurance by having it and the ability to [better] see and identify people and animals." Heath, in partnership with the World Wildlife Fund, relies on a thermal imaging camera that uses artificial intelligence to identify animals and poachers up to a kilometer away.

New analytics engine for users allows anyone to receive fast, accurate imaging analysis for key clinical conditions, by simply uploading their scans to Zebra's online system Zebra Medical Vision (https://www.zebra-med.com/), the leading machine learning imaging analytics company, is launching Profound (http://profound.zebra-med.com) The company's new service allows people to upload their medical imaging scans such as CTs and Mammograms to Zebra's online service, and receive an automated analysis for key clinical conditions. This Smart News Release features multimedia. "We are all anxious about our health. Undergoing an imaging scan such as a CT or a Mammogram is stressful for many people, often compounded by a long wait for results, with additional follow-up tests and examinations." said Elad Benjamin, co-founder and CEO of Zebra Medical Vision.

Computer algorithms can interpret echocardiographic images and distinguish between two similar heart conditions affecting young athletes, according to research published in the Journal of the American College of Cardiology. Researchers from the Icahn School of Medicine at Mount Sinai tested three different machine-learning algorithms for their effectiveness in the discrimination of physiological versus pathological hypertrophic cardiomyopathy. Pathological hypertrophic cardiomyopathy (HCM), in which a portion of the myocardium enlarges, leading to impaired heart function, is the leading cause of sudden death in young athletes. Distinguishing between it and physiological hypertrophy (heart enlargement often due to exercise) generally requires testing for the two conditions with interpretation by a highly trained cardiologist, according to an announcement. "This demonstrates how machine-learning models and other smart interpretation systems could help to efficiently analyze and process large volumes of cardiac ultrasound data, and with the growth of telemedicine, it could enable cardiac diagnoses even in the most resource-burdened areas," said study author Joel Dudley, Ph.D.

Since I joined Stack Exchange as a Data Scientist in June, one of my first projects has been reconsidering the A/B testing system used to evaluate new features and changes to the site. Our current approach relies on computing a p-value to measure our confidence in a new feature. Unfortunately, this leads to a common pitfall in performing A/B testing, which is the habit of looking at a test while it's running, then stopping the test as soon as the p-value reaches a particular threshold- say, .05. This seems reasonable, but in doing so, you're making the p-value no longer trustworthy, and making it substantially more likely you'll implement features that offer no improvement. How Not To Run an A/B Test gives a good explanation of this problem.

Technology is advancing so rapidly that we will experience radical changes in society not only in our lifetimes but in the coming years. We have already begun to see ways in which computing, sensors, artificial intelligence and genomics are reshaping entire industries and our daily lives. As we undergo this rapid change, many of the old assumptions that we have relied on will no longer apply. Technology is creating a new set of rules that will change our very existence. Digitization began with words and numbers.

Innovative technology has developed to enhance human lives whether that be for better security, organisation, energy usage, entertainment or education, the list goes on. . . One place where all of these prospective improvements come together is in your home. Through the Internet of Things (IoT), developers have sought to make our home lives seamlessly compatible with the technology we use, from coffee machines to highly advanced house-bots. Recently, companies like Google, Apple and Amazon have jostled to become the leader in Smart Home devices, offering Artificially Intelligent, IoT connected products like Echo, Nest and Google Home. According to a survey by Accenture, 69% of homes will be installed with a connected device of some kind by 2019.