Results


Storage in 2017: Big improvements are on the way

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The pace of storage change continues to accelerate, and its impact on us continues to grow. Digital storage is central to a digital civilization, and as we grow more digital, we grow more dependent on improvements in storage. Here's what to expect in 2017. AI will make stored data - and therefore storage- more valuable. When you can take - as we can today - a grainy surveillance video or a blurred face and read a license plate number of determine someone's identity using AI, the value of stored data rises, for good or ill.


Intel integrates Nervana technology into product roadmap

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Diane Bryant, Intel executive vice president and general manager of the Data Center Group, stands with Nervana co-founder Naveen Rao. Within just two months acquiring Nervana, Intel is integrating the deep learning startup's technology into its product roadmap, the company announced Thursday. The new Nervana platform will be the industry's most comprehensive portfolio for AI, the company contends, built for speed and ease of use. "We expect the Intel Nervana platform to produce breakthrough performance and dramatic reductions in the time to train complex neural networks," Diane Bryant, Intel executive vice president and general manager of the Data Center Group, said in a statement. "Before the end of the decade, Intel will deliver a 100-fold increase in performance that will turbocharge the pace of innovation in the emerging deep learning space."


Effects of the Digital Transformation on Businesses - Helpful Use Cases in the Consumer Products industry - Service Enhanced Products

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To achieve this, the company needs to equip their products with sensors, and collect and analyze product performance data through predictive analytical models. For instance with analytical insights, which would give customers the ability to monitor their machine's consumption patterns and improving their operations via optimized schedules for replenishment tasks. Another example are predictive maintenance services, which help customers to reduced machine down-times and lowering their maintenance costs. This company's goal was it to realize benefits like cost reduction, customer satisfaction, revenue increase, and quality increase.


Ford to focus on electric vehicles, autonomous tech in company shakeup

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Ford has revealed plans to grow and increase profit margins by streamlining and transforming the company into a dominant player in next-generation automotive technology. On Wednesday, the Dearborn, Michigan-based firm said that expansion into the mobile area is moving apace, but more opportunities await the automaker in next-generation technologies -- including electric vehicles (EVs) and self-driving technology. Ford plans to grow the company through an enhanced focus on utility vehicles and heavy investment in "emerging opportunities," with the overall aim of becoming a leader in "electrification, autonomy and mobility," the firm said in a press release. "We expect Ford's performance to be strong through 2018 -- with our core business improving, allowing us to invest in the emerging opportunities that will ensure our future success," said Ford CFO Bob Shanks.


Nvidia releases Pascal GPUs for neural networks

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Compared to using an Intel Xeon E5-2690v4, which was launched earlier this year, Nvidia claimed its offering is 40 times more power efficient while being 45 times faster to respond. "A single server with a single Tesla P4 replaces 13 CPU-only servers for video inferencing workloads, delivering over 8x savings in total cost of ownership, including server and power costs," the company boasted. "Most customers will tell you that a GPU becomes a one-off environment that they need to code and program against, whereas they are running millions of Xeons in their datacentre, and the more they can use single instruction set, single operating system, single operating environment for all of their workloads, the better the performance of lower total cost of operation," she said. Nvidia today also announced its Drive PX 2 platform that is set to be deployed by Baidu in its self-driving car.


Pymble Ladies' College using data to track students' performance

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With a focus on numbers to measure a student's success flagged as passé, Justin Raymond, Dean of Curriculum Innovation at Pymble Ladies' College in Sydney, has implemented an analytics platform at the all-girls school that tracks an individual to monitor their overall performance. As part of the digital journey at the school, Raymond implemented a platform that tracks students "from functioning to thriving", gathering their performance data from each teacher and class the student is in. The concept of sharing data on a student was a big paradigm shift for the school; Raymond said teachers would previously keep that information for themselves and share it on occasion with parents. He said that the school is now dabbling with business insights and its existing dashboards to gain further insights into each individual student's learning journey, and is also working with its dashboards from an enrolment perspective to be able to gain a better insight into areas such as where each student resides "It's about really making the most of our big data sets and being proactive," he said.


7 essentials of well-connected hybrid clouds

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"There are a number of enabling technologies that have to be put in place in order to enable a hybrid cloud to operate to support changing business requirements." Here's how it may all work, in a hypothetical scenario for hybrid cloud the authors lay out: Hybrid cloud requires integration on many levels, the authors state. "It must be able to monitor those services so there's clear visibility so the entire environment can be controlled in a predictable manner.This means being able to monitor and control not just internal services but those services that are owned and controlled by third-party public cloud vendors or managed services providers." "Organizations need a single unified way to manage and synchronize applications and data across public and private clouds."


Vision and neural nets drive demand for more powerful chips

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Earlier this year, Nvidia announced the Drive PX 2 module, which has two Parker SoCs (12 CPU cores) and two discrete GPUs delivering a total of 8 teraflops of single-precision (FP32) performance. The Ceva-XM4 is a high-performance vision DSP capable of reaching speeds of up to 1.5GHz on TSMC's 28nm HPM process and designed for embedded vision and AI in areas such as surveillance cameras, ADAS and autonomous driving, augmented reality, and drones. The latest addition to Cadence's Tensilica line of vision processors, the Vision P6, delivers two to four times the performance on convolutional neural networks thanks to additional MACs (multiply-accumulate) support for half- and single-precision floating-point (as well as 8-, 16- and 32-bit fixed-point data), and enhanced memory parallelism and data movement. Autonomous vehicles, drones, augmented reality and virtual reality, video surveillance, and other smart devices will all require embedded processors that can handle lots of number crunching without using a lot of power.


Federal agency probing Tesla's Autopilot feature after fatal crash

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The National Highway Traffic Safety Administration (NHTSA) has opened a preliminary investigation into the performance of Tesla's Autopilot feature during a fatal crash that occurred last month. Tesla reported the incident to the NHTSA, and the agency deployed its Special Crash Investigations Team to investigate the vehicle and crash scene. Tesla learned about the preliminary Autopilot investigation on Wednesday evening, the company said in a blog post. Tesla noted that when activated, the Autopilot feature alerts drivers that they must remain in control.


Australian Institute of Sport taps into data to help athletes train for gold

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The Australian Institute of Sport (AIS) has predicted, and is hopeful, the Australian team will pick up six or seven gold medals at the upcoming Rio Olympics. The information is collected from 2,000 athletes each week, including 300 data points per athlete, making up a total of 600,000 data points per week. According to Nick Brown, AIS performance science and innovation deputy director, using data and analytics means athletes are able to train and compete consistently, without losing days to recovery or illness. AIS has partnered with Microsoft and BizData to use predictive analytics and machine learning to analyse the collected data, which is uploaded each night through an Azure SQL Database to the Athlete Management System, where all of the data is stored.