Intel Tech Learning Lab Starts Tour to Shape Education’s Future

Intel Tech Learning Lab 1

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What’s New: Sharing an immersive, technology-based approach to education, Intel’s Tech Learning Lab begins a multi-city experiential tour today for students and teachers. The nationwide tour starts at the Bronx Academy of Letters in New York City.

“Intel is addressing the needs of educators through advanced technology that enables effective and dynamic classroom experiences and drives students’ skills development to prepare them for the demands of the future workforce.”
–Raysana Hurtado, education segment manager at Intel

What It Is: Intel’s Tech Learning Lab is a custom-built mobile container truck outfitted with virtual reality (VR) demo stations, powerful PCs, augmented reality (AR) and Internet of Things (IoT) smart whiteboards. Accompanied by immersive, hands-on workshops featuring artificial intelligence, coding and robotics, it will make stops at schools and other education institutions through Dec. 15.

Why It’s Important: Intel will bring innovative teaching methods to educators to help them build the leaders of tomorrow by developing fundamental career skills like communication, collaboration, self-awareness, problem-solving, critical thinking and more.

Today’s students live in a digital world. Modern teaching methods need to reflect this, with technology as a seamless integration applied across all areas of instruction. Despite the indisputable need for a sophisticated workforce, schools across the country are stuck using technologies and instructional models of the past to prepare students for careers of the future.

The Tech Learning Lab tour is designed to engage with educators and spark conversations that go beyond the classroom to fuel curiosity about the role of technology and its impact on our world and daily lives. Hands-on virtual lessons spanning arts, science and other subjects will introduce students, teachers and administrators to the power of technology as an instructional tool for the 21st century.

Why Now: The U.S. education system is changing, with drastic cuts to arts education; the rise of science, technology, engineering and math education (STEM); and innovative new models. Until now, classroom technology has been used as an add-on to existing instructional methods rather than as tools to improve or revolutionize instruction.

Cutting-edge technology-based educational programs can emphasize deeper collaboration and engagement, versus student instruction on software that likely will be obsolete by the time they enter the workforce. The future classroom is one that incorporates powerful technology and encourages creative approaches to learning, supporting education goals today and for tomorrow.

Where It will Visit: Intel’s Tech Learning Lab continues at schools across the country, with visits planned to:

  • Weston High School, in Weston, Mass. (Nov. 7-9)
  • Ron Clark Academy, in Atlanta (Nov. 15-16)
  • Design39Campus, in San Diego (Nov. 29-30)
  • McClymonds High School, in Oakland, Calif. (week of Dec. 3rd)
  • Oakland Tech, in Oakland, Calif. (week of Dec. 3rd)

More Context: For full details on the technologies featured throughout Intel’s Tech Learning Lab, visit the tour fact sheet.


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Intel and Arm Share IoT Vision to Securely Connect ‘Any Device to Any Cloud’

lorie wigle

By Lorie Wigle

The Internet of Things (IoT) is transitioning from first proof-of-concept deployments into a new growth phase that is expected, according to industry analysts, to deploy 1 trillion devices by 2035.1 What is driving these lofty projections are the incredible business benefits that will be achieved with data-driven IoT initiatives such as edge computing, artificial intelligence (AI), predictive maintenance and autonomous systems. The more data that is collected, the more valuable the data becomes. However, this model may not be realized unless the industry can collaborate on more open and scalable methods to securely provision devices and their data to the cloud.

To answer these challenges, Intel is teaming up with Arm* to provide solutions to securely onboard2 both Intel and Arm IoT devices to any application or cloud framework.

First, let me walk you through the traditional manual onboarding process for IoT devices, which has multiple challenges. It typically takes more than 20 minutes per device and involves coordination among installation technicians, IT network/security operations and operational technology teams. The device identity and network access credentials are either painstakingly preloaded into the device at manufacturing or configured in the field from a standard image using insecure human processes. Compounding the security issues are the proliferation of cloud-specific provisioning methods without a consistent hardware-protected device identity model. For IoT to scale to a trillion devices in less than two decades, this process must be faster, safer and more flexible.

Now, the solution: Last October, Intel® Secure Device Onboard was launched as the first solution that enabled a “late binding” approach to provisioning, where customers could dynamically discover their target cloud platform for provisioning seconds after the device is powered on in the field. The collaboration with Arm aims to extend this capability from Intel devices to include the Arm devices that commonly are deployed together by customers. This strategic collaboration of two major ecosystems is designed to provide the industry with a more flexible provisioning method that can be natively enabled in devices.

So how does it work? Watch the prototype video below that shows how Intel and Arm devices can be credentialed and provisioned in seconds to join any cloud application framework.

As a result, customers should be able to choose their onboarding systems of record without being locked into a single cloud provider’s provisioning method or a single device architecture. Flexibility can be built in before the device is purchased to onboard into any cloud ecosystem. Device management systems such as Pelion*, cloud/on-premise IoT platforms and connected partner ecosystems all benefit from increased variety of devices, lower cost and faster deployment. Device suppliers can simplify manufacturing to a single SKU that can be provisioned with customer-specific credentials in the field rather than in the factory, dramatically reducing cost while decreasing time to market.

“Intel and Arm are simplifying one of IoT’s most complex and challenging barriers with regard to streamlining the manufacturing and security deployment workflows for IoT. This is an ROI win for the customer, who will be able to deploy both Intel- and Arm-based devices at a lower cost and with less friction between IT and OT, while at the same time retaining flexibility over their data and cloud partner choice until the deployment phase,” said Michela Menting, director, ABI Research.

Learn more about the solution at IoT Solution World Congress’s smart building customer case study presentation and view the joint demo that is nominated for top TestBed award. You may also attend the technical presentation at Arm TechCon that will showcase the Pelion Device Management zero-touch experience. Intel and Arm are seeking customer and ecosystem feedback on the prototypes and expect to engage pilot customers later this year. Contact iotonboarding@intel.com for more information on the pilot programs.

Intel’s collaboration with Arm allows us to progress a joint vision of “any device, any cloud” to span multiple device architectures. As we enter this accelerated growth phase for IoT, we will continue to collaborate with technology vendors to provide customers the protections they need. On behalf of the entire Intel team, I thank our industry partners and customers for their ongoing support.

Lorie Wigle is vice president of Software and Services Group and general manager of Internet of Things Security at Intel Corporation.

1Trillion devices by 2035- source ARM white paper https://community.arm.com/cfs-file/__key/telligent-evolution-components-attachments/01-1996-00-00-00-01-30-09/Arm-_2D00_-The-route-to-a-trillion-devices-_2D00_-June-2017.pdf

2From out-of-box to securely streaming data to an IoT Platform

Intel technologies’ features and benefits depend on system configuration and may require enabled hardware, software or service activation. Performance varies depending on system configuration. No computer system can be absolutely secure. Check with your system manufacturer or retailer or learn more at https://www.intel.com/content/www/us/en/internet-of-things/secure-device-onboard.html.

Intel, the Intel logo, and Intel® Secure Device Onboard are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries.

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New Intel Vision Accelerator Solutions Speed Deep Learning and Artificial Intelligence on Edge Devices

iot vision 2x1What’s New: Today, Intel unveiled its family of Intel® Vision Accelerator Design Products targeted at artificial intelligence (AI) inference and analytics performance on edge devices, where data originates and is acted upon. The new acceleration solutions come in two forms: one that features an array of Intel® Movidius™ vision processors and one built on the high-performance Intel® Arria® 10 FPGA. The accelerator solutions build on the OpenVINO™ software toolkit that provides developers with improved neural network performance on a variety of Intel products and helps them further unlock cost-effective, real-time image analysis and intelligence within their Internet of Things (IoT) devices.

“Until recently, businesses have been struggling to implement deep learning technology. For transportation, smart cities, healthcare, retail and manufacturing industries, it takes specialized expertise, a broad range of form factors and scalable solutions to make this happen. Intel’s Vision Accelerator Design Products now offer businesses choice and flexibility to easily and affordably accelerate AI at the edge to drive real-time insights.”
–Jonathan Ballon, Intel vice president and general manager, Internet of Things Group

Why This Is Important: The need for intelligence on edge devices has never been greater. As deep learning approaches rapidly replace more traditional computer vision techniques, businesses can unlock rich data from digital video. With Intel Vision Accelerator Design Products, businesses can implement vision-based AI systems to collect and analyze data right on edge devices for real-time decision-making. Advanced edge computing capabilities help cut costs, drive new revenue streams and improve services.

What This Delivers: Combined with Intel Vision products such as Intel CPUs with integrated graphics, these new edge accelerator cards allow businesses the choice and flexibility of price, power and performance to meet specific requirements from camera to cloud. Intel’s Vision Accelerator Design Products will build upon growing industry adoption for the OpenVINO toolkit:

  • Smart, Safe Cities: With the OpenVINO toolkit, stadium security provider AxxonSoft* used existing installed-base hardware to achieve 9.6 times the performance on standard Intel® Core™ i7 processors and 3.1 times the performance on Intel® Xeon® Scalable processors in order to ensure the safety of 2 million visitors to the FIFA 2018 World Cup.*

Who Uses This: Leading companies such as Dell*, Honeywell* and QNAP* are planning products based on Intel Vision Accelerator Designs. Additional partners and customers, from equipment builders, solution developers and cloud service providers support these products.

More Context: Intel’s Vision Accelerator Design Products Customer QuotesVideo | Infographic

How This Works: Intel Vision Accelerator Design Products work by offloading AI inference workloads to purpose-built accelerator cards that feature either an array of Intel Movidius Vision Processing Units, or a high-performance Intel Arria 10 FPGA. Deep learning inference accelerators scale to the needs of businesses using Intel Vision solutions, whether they are adopting deep learning AI applications in the data center, in on-premise servers or inside edge devices. With the OpenVINO toolkit, developers can easily extend their investment in deep learning inference applications on Intel CPUs and integrated GPUs to these new accelerator designs, saving time and money.

The Small Print:

1Automated product quality data collected by Yumei using JWIPC® model IX7, ruggedized, fan-less edge compute node/industrial PC running an Intel® Core™ i7 CPU with integrated on die GPU and OpenVINO SDK. 16GB of system memory, connected to a 5MP POE Basler* Camera model acA 1920-40gc. Together these components, along with the Intel developed computer vision and deep learning algorithms, provide Yumei factory workers information on product defects near real-time (within 100 milliseconds). Sample size >100,000 production units collected over 6 months in 2018.

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Intel and Industry Partners Accelerate 5G in China

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What’s New: Today at the Intel 5G Network Summit in Beijing, China, Sandra Rivera, senior vice president of Intel’s Network Platforms Group, unveiled new developments across the 5G value chain alongside a powerful ecosystem of industry leaders, including Baidu*, China Mobile*, China Telecom*, China Unicom*, H3C*, Huawei*, Tencent*, Unisoc* and ZTE.*

“By providing end-to-end technologies and collaboration with our partner ecosystem in China, Intel will accelerate the path to 5G. This is another excellent example of how we are uniquely able to bring together the worlds of connectivity, computing and cloud for a seamlessly connected, powerfully smart 5G future.”
–Sandra Rivera, Intel senior vice president of the Network Platforms Group

Why It’s Important: Intel’s end-to-end portfolio of technologies and solutions makes it a key enabler delivering on the promise of 5G. Intel is bringing together an ecosystem of telecommunications equipment manufacturers (TEMs) and operators to accelerate 5G commercialization. Through leading industry keynotes and a panel, today’s event also gave attendees a deep look at the progress being made by Intel and partners in 5G networks in China.

What Was Unveiled: Among the day’s top news:

  • Unisoc, which produces chipsets for mobile phones, shared plans to utilize Intel 5G modems for mid-tier Android* smartphones in China and globally with its applications processor, ROC1. Unisoc CTO Xiaoxin Qiu appeared on stage with Dr. Cormac Conroy, Intel vice president and general manager of the Communication and Devices Group, who said Intel will target broad global markets, building upon its strong momentum in LTE modems as 5G scales.
  • Cloud provider Baidu’s System Department executive director Zhenyu Hou announced that a joint artificial intelligence and 5G innovation lab will be developed with Intel to explore converged edge and cloud services to provide better user experiences, delivering 5G-ready applications in the areas of the Internet of Things, entertainment and automotive.
  • China Unicom and the Beijing Organizing Committee for the Olympic Games (BOCOG) unveiled plans to collaborate with Intel to deliver new 5G experiences and capabilities at the coming 2022 Winter Olympics.

Why an Ecosystem Matters: Intel has a long history in China as an enabler with technologies for computing, data center and cloud and will deliver 5G with its ecosystem to service providers and operators. Its partners in the region are key to this transformation. Because 5G experiences will only be as capable as the network that supports them, Intel’s focus in cloud computing from the data center to the edge to devices enables partners to leverage existing Intel® Xeon® processor-based infrastructure to rapidly develop, test and deploy the next-generation experiences and services for customers. This includes network functions virtualization (NFV) and software-defined networking (SDN) solutions that run on Intel.

Other Unveilings:

  • Alibaba AliOS’ named Intel as one of the first strategic partners of its intelligent transportation initiative, aiming to support the construction of an intelligent road traffic network. The two companies, along with Datang Telecom* will explore v2x usage model with respect to 5G communication and edge computing based on the Intel Network Edge Virtualization Software Development Kit (NEV SDK), as shared at the recent Alibaba Yunqi Conference in Hangzhou. (Earlier story: Alibaba and Intel Transforming Data-Centric Computing from Hyperscale Data Centers to the Edge)
  • H3C, an Ethernet switch maker, and Comba Telecom Holdings* outlined plans to use an Intel FlexRAN 5G NR-compliant solution for 5G.
  • Huawei shared successes in interoperability trials with Intel as part of the IMT 2020 5G Phase 3 testing and announced that the two companies will continue to work together on driving this International Telecommunications Union (ITU) standard to completion.
  • Tencent WeTest is deploying an industry-leading edge-cloud gaming platform based on Intel Xeon processors to drive the gaming industry ecosystem into next phase of transformation with a focus on infrastructure, game R&D, distribution and devices.

More Context: 5G at Intel

2018 Intel Corporation. Intel, the Intel logo, and Intel Xeon are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries.

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Making Factories Better Places for Humans to Work

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Faith McCreary (left) and Irene Petrick work in Intel’s Internet of Things Group. Authors of a 2018 research paper on “Industry 4.0,” they interviewed people – CEOs to factory workers – at 133 manufacturers. (Credit: Walden Kirsch/Intel Corporation)
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Who: Irene Petrick, director of Industrial Innovation in the Industrial Solutions Division, Internet of Things Group; Faith McCreary, principal engineer, experience architect, and researcher, Internet of Things Group

How they would describe their work to a 10-year-old: “We imagine the factory of the future that is smart enough to take care of itself most of the time,” Faith says.

Hundreds of interviews later: Both Ph.Ds in Intel’s Internet of Things Group, Irene and Faith came to Intel after careers in consulting, research and academia. After they interviewed employees – CEOs to factory workers – at 133 manufacturers, they co-authored a research paper on “Industry 4.0.” One key finding: 59 percent of people in manufacturing want “intelligent” solutions to take on work described as manual or labor-intensive.

More: Read about all Intel Innovators

A factory that knows: Irene offers an example of an intelligent solution: “In an auto manufacturing plant, machines will ‘know’ when they need maintenance; they will collaborate with each other. Mobile robots will move materials rather than conveyor belts, and much of this manual labor will happen without people.”

Machines doing what they do best: “In the factory of the future, people will do what people do best and machines will do what machines do best,” Faith says. “Machines do the repetitive tasks and even learn to anticipate how to do those tasks better. The factory of the future will be constantly learning how to improve its operations.”

Less perspiration, more inspiration: Today, many factory environments require hard physical labor. In the future, maybe not so much. Thinking again of that hypothetical auto plant, Irene says, “Instead of the back-breaking work of the assembly line, people in the future will spend their time troubleshooting and improving overall operations. Their work will be more creative and strategic, and their work will not be rooted to the factory floor.”

Less repetition, fewer hazards: “A lot of what goes on in a factory today is hard on people,” Faith says, “either because of the repetitive nature of the work or the potential hazards. Done right, technology has the potential to help eliminate the negatives of factory work and make it more uniquely human.”

Technology’s effect on the worker: Irene explains that we often don’t give enough thought to the effects of technology on people – or the reverse. “There is nothing worse than creating a solution and then looking for a problem to solve with it,” Irene says.

In their factory interviews, Faith and Irene found an undercurrent of distrust or even fear of “letting go of human control in manufacturing processes.” Many of the people they talked with – especially on the factory floor – said they worried about being left behind as manufacturing becomes “smarter” and less reliant on human sweat or outmoded skills.

“Getting people and technologies to work together means that we need to understand them both better,” Faith says.

Listening to factory workers: Faith says there’s a wrong way and a right way to make factories smarter. “Most technology is introduced in the factory in a very top-down fashion.  If we can change that, and actually start leveraging the knowledge and passion of the people in the factory in the process, imagine what we could do? Our research shows that a majority of people in the factory world – from people on the factory floor to execs in the C-suite – agree there are opportunities for change. The right approach is to tap into this consensus and use it to speed the adoption of the future smart factory.”

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Alibaba and Intel Transforming Data-Centric Computing from Hyperscale Data Centers to the Edge

data centric 2x1What’s New: At The Computing Conference 2018 hosted by Alibaba Group* in Hangzhou, China, Intel and Alibaba revealed how their deep collaboration is driving the creation of revolutionary technologies that power the era of data-centric computing – from hyperscale data centers to the edge, to accelerate the deployments of new applications such as autonomous vehicles and Internet of Things (IoT).

“Alibaba’s highly innovative data-centric computing infrastructure supported by Intel technology enables real-time insight for customers from the cloud to the edge. Our close collaboration with Alibaba from silicon to software to market adoption enables customers to benefit from a broad set of workload-optimized solutions.”
– Navin Shenoy, Intel executive vice president and general manager of the Data Center Group

What the Headlines are: Intel and Alibaba Group are:

  • Launching of a Joint Edge Computing Platform to accelerate edge computing development
  • Establishing the Apsara Stack Industry Alliance targeting on-premises enterprise cloud environments
  • Deploying latest Intel technology in Alibaba to prepare for the 11/11 shopping festival
  • Bringing volumetric content to the Olympic Games Tokyo 2020 via OBS Cloud
  • Accelerating the commercialization intelligent roads

“We are thrilled to have Intel as our long-term strategic partner, and are excited to expand our collaboration across a wide array of areas from edge computing to hybrid cloud, Internet of Things and smart mobility,” said Simon Hu, senior vice president of Alibaba Group and president of Alibaba Cloud. “By combining Intel’s leading technology services and Alibaba’s experience in driving digital transformation in China and the rest of Asia, we are confident that our clients worldwide will benefit from the technology innovation that comes from this partnership.”

How They Accelerate on the Edge: Intel and Alibaba Cloud launched a Joint Edge Computing Platform that allows enterprises to develop customizable device-to-cloud IoT solutions for different edge computing scenarios, including industrial manufacturing, smart building and smart community, among others. The Joint Edge Computing Platform is an open architecture that integrates Intel software, hardware and artificial intelligence (AI) technologies with Alibaba Cloud’s latest IoT products. The platform utilizes computer vision and AI to convert data at the edge into business insights. The Joint Edge Computing Platform was recently deployed in Chongqing Refine-Yumei Die Casting Co., Ltd. (Yumei) factories and was able to increase defect detection speed five times from manual detection to automatic detection1.

hybrid cloud 2x1How They Drive Hybrid Cloud Solutions: Intel and Alibaba Cloud established the Apsara Stack Industry Alliance, which focuses on building an ecosystem of hybrid cloud solutions for Alibaba Cloud’s Apsara Stack. Optimized for Intel® Xeon® Scalable processors, the Apsara Stack provides large- and medium-sized businesses with on-premises hybrid cloud services that function the same as hyperscale cloud computing and big data services provided by Alibaba public cloud. This alliance will also enable small- and medium-sized businesses (SMBs) to access technologies, infrastructure and security on par with that of large corporations, while offering them a path to greater levels of automation, self-service capabilities, cost efficiencies and governance.

How They Power eCommerce: In preparation for the upcoming 11/11 “Singles Day” global shopping festival – which generated in excess of 168.2 billion yuan ($25 billion) in spending during the 2017 celebration – Alibaba plans to trial the next-generation Intel Xeon Scalable processors and upcoming Intel® Optane® DC persistent memory with Alibaba’s Tair workload. This workload is a key value data access and caching storage system developed by Alibaba and broadly deployed in many of Alibaba’s core applications such as Taobao and Tmall. Intel’s compute, memory and storage solutions are optimized for Alibaba’s highly interactive and data-intensive applications. These applications require the infrastructure to keep large amounts of hot accessible data in the memory cache to achieve the desired throughput (queries per second) in order to deliver smooth and responsive user experiences, especially during peak hours of the 11/11 shopping festival.

How They Accelerate the Olympics’ Digital Transformation: Also announced was a partnership aimed at advancing the digital transformation of the Olympics and delivering volumetric content over the OBS Cloud for the first time at the Olympic Games Tokyo 2020. As worldwide Olympic partners, Intel and Alibaba Cloud, will collaborate with OBS to explore a more efficient and reliable delivery pipeline of immersive media to RHBs worldwide that will improve the fan experience and bring them closer to the action via Intel’s volumetric and virtual reality technologies. This showcases the depth of Intel’s end-to-end capabilities, including the most advanced Intel Xeon Scalable processors powering OBS Cloud, compute power to process high volumes of data, and technology to create and deliver immersive media.

How They Accelerate the Commercialization of Intelligent Roads: Intel officially became one of Alibaba AliOS’ first strategic partners of the intelligent transportation initiative, aiming to support the construction of intelligent road traffic network and build a digital and intelligent transportation system to realize vehicle-road synergy. Intel and Alibaba will jointly explore v2x usage model with respect to 5G communication and edge computing based on the Intel Network Edge Virtualization Software Development Kit (NEV SDK).

More Context: Intel and Alibaba Cloud Deliver Joint Computing Platform for AI Inference at the Edge

1Automated product quality data collected by YuMei using JWIPC® model IX7, ruggedized, fan-less edge compute node/industrial PC running an Intel® Core™ i7 CPU with integrated on die GPU and OpenVINO SDK. 16GB of system memory, connected to a 5MP POE Basler* Camera model acA 1920-40gc. Together these components, along with the Intel developed computer vision and deep learning algorithms, provide YuMei factory workers information on product defects near real-time (within 100 milliseconds). Sample size >100,000 production units collected over 6 months in 2018.

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Baidu Cloud Collaborates with Intel AI to Advance Financial Services, Shipping and Video Processing

baidu 2x1What’s New: At the Baidu* 2018 ABC Summit in Shanghai, Baidu and Intel outlined new artificial intelligence (AI) collaborations showcasing applications ranging from financial services and shipping to video content detection. Specifically, Baidu Cloud* is leveraging Intel® Xeon® Scalable processors and the Intel® Math Kernel Library-Deep Neural Network (Intel® MKL-DNN) as part of a new financial services solution for leading China banks; the Intel OpenVINO toolkit in new AI edge distribution and video solutions; and Intel® Optane™ technology and Intel QLC NAND SSD technology for enhanced object storage.

skillern-2x1“Intel is collaborating with Baidu Cloud to deliver end-to-end AI solutions. Adopting a new chip or optimizing a single framework is not enough to meet the demands of new AI workloads. What’s required is systems-level integration with software optimization, and Intel is enabling this through our expertise and extensive portfolio of AI technologies – all in the name of helping our customers achieve their AI goals.”
–Raejeanne Skillern, Intel vice president, Data Center Group, and general manager, Cloud Service Provider Platform Group

How Intel Processors Help in Finance: Baidu is deploying advanced private financial clouds for customers including China Union Pay*, AI Bank* and the Agricultural Bank of China*. The financial clouds run on Intel Xeon Scalable processors and the Intel MKL-DNN library to meet the performance and security requirements of financial services companies.

How Intel AI Helps in Shipping: Baidu Cloud wanted to help companies monitor trucks in real time by increasing efficiency of edge devices to improve shipping operations and report back to the central office on outstanding events. For edge computing, Intel supported Baidu Cloud in implementing an AI video analysis system to accelerate the development of vision applications. For example, it was difficult to monitor municipal service trucks, even if they were equipped with a video recording device because the recordings could only be reviewed afterward. With the OpenVINO™ toolkit, Baidu Cloud is able to deploy a powerful AI video analysis system equipped with a camera that detects and instantly reports any unusual incidents (such as waste falling from a truck) through a wireless connection.

How Intel Helps Speed Video Processing: Baidu Cloud sought to bolster its video processing services to better support iQiyi*, the Chinese equivalent of Netflix*. iQiyi adopted the OpenVINO toolkit to detect videos that violate the content rules and achieved performance improvements on the existing platform, and an extra performance improvement on Baidu Cloud powered by Intel Xeon Scalable processors.

How Intel Storage Helps with AI Training: Baidu Cloud and Intel set out to develop a new AI storage solution that better meets requirements for performance, size and cost given the large amount of data generated by AI training. By leveraging both Intel Optane technology and Intel QLC Technology, Baidu Cloud is tackling the challenges posed by the massive generation of data and related performance, size and cost requirements.

Why It’s Important: Intel is continuously pushing the boundaries of AI through performance-leading products and broad ecosystem collaboration, all in an effort to unleash the power of data. Since no single hardware or framework meets the diversified requirements of all possible AI solutions and each customer faces different scenarios with different workloads, Intel is investing in a holistic approach to AI and developing unique solutions for customers across central processing units, storage and the network. Building on its strong partnership with Baidu Cloud, Intel will continue to accelerate AI breakthroughs and implementations – leveraging AI to solve real problems and eventually turning AI concepts into reality.

More Context: Artificial Intelligence at Intel | Intel AI at Baidu Create: AI Camera, FPGA-based Acceleration and Xeon Scalable Optimizations for Deep Learning

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Intel and Philips Accelerate Deep Learning Inference on CPUs in Key Medical Imaging Uses

healthcare illustrationWhat’s New: Using Intel® Xeon® Scalable processors and the OpenVINO™ toolkit, Intel and Philips* tested two healthcare use cases for deep learning inference models: one on X-rays of bones for bone-age-prediction modeling, the other on CT scans of lungs for lung segmentation. In these tests, Intel and Philips achieved a speed improvement of 188 times for the bone-age-prediction model, and a 38 times speed improvement for the lung-segmentation model over the baseline measurements.

“Intel Xeon Scalable processors appear to be the right solution for this type of AI workload. Our customers can use their existing hardware to its maximum potential, while still aiming to achieve quality output resolution at exceptional speeds.”
–Vijayananda J., chief architect and fellow, Data Science and AI at Philips HealthSuite Insights

Why It’s Important: Until recently, there was one prominent hardware solution to accelerate deep learning: graphics processing unit (GPUs). By design, GPUs work well with images, but they also have inherent memory constraints that data scientists have had to work around when building some models.

Central processing units (CPUs) – in this case Intel Xeon Scalable processors – don’t have those same memory constraints and can accelerate complex, hybrid workloads, including larger, memory-intensive models typically found in medical imaging. For a large subset of artificial intelligence (AI) workloads, Intel Xeon Scalable processors can better meet data scientists’ needs than GPU-based systems. As Philips found in the two recent tests, this enables the company to offer AI solutions at lower cost to its customers.

Why It Matters: AI techniques such as object detection and segmentation can help radiologists identify issues faster and more accurately, which can translate to better prioritization of cases, better outcomes for more patients and reduced costs for hospitals.

Deep learning inference applications typically process workloads in small batches or in a streaming manner, which means they do not exhibit large batch sizes. CPUs are a great fit for low batch or streaming applications. In particular, Intel Xeon Scalable processors offer an affordable, flexible platform for AI models – particularly in conjunction with tools like the OpenVINO toolkit, which can help deploy pre-trained models for efficiency, without sacrificing accuracy.

These tests show that healthcare organizations can implement AI workloads without expensive hardware investments.

What the Results Show: The results for both use cases surpassed expectations. The bone-age-prediction model went from an initial baseline test result of 1.42 images per second to a final tested rate of 267.1 images per second after optimizations – an increase of 188 times. The lung-segmentation model far surpassed the target of 15 images per second by improving from a baseline of 1.9 images per second to 71.7 images per second after optimizations.

What’s Next: Running healthcare deep learning workloads on CPU-based devices offers direct benefits to companies like Philips, because it allows them to offer AI-based services that don’t drive up costs for their end customers. As shown in this test, companies like Philips can offer AI algorithms for download through an online store as a way to increase revenue and differentiate themselves from growing competition.

More Context: Multiple trends are contributing to this shift:

  • As medical image resolution improves, medical image file sizes are growing – many images are 1GB or greater.
  • More healthcare organizations are using deep learning inference to more quickly and accurately review patient images.
  • Organizations are looking for ways to do this without buying expensive new infrastructure.

The Philips tests are just one example of these trends in action. Novartis* is another. And many other Intel customers – not yet publicly announced – are achieving similar results. Learn more about Intel AI technology in healthcare at “Advancing Data-Driven Healthcare Solutions.”

The post Intel and Philips Accelerate Deep Learning Inference on CPUs in Key Medical Imaging Uses appeared first on Intel Newsroom.

Walmart Files Blockchain Patent for Smart Appliance Management

Walmart has filed another patent application in the blockchain sector entitled “Managing Smart Applications Using Blockchain Technology.” The filing follows a number of previous applications for blockchain patents including blockchain package delivery systems, medical record storage systems, and a blockchain-based digital marketplace. The most recent patent application, published on Aug. 2, details systems and methods that

The post Walmart Files Blockchain Patent for Smart Appliance Management appeared first on CCN

2018 Computex

At COMPUTEX Taipei 2018, Intel will showcase how the company is powering the future of computing, connectivity and communications through advanced innovations in client computing, artificial intelligence, the internet of things and 5G network transformation. Intel also will take the stage at COMPUTEX. We invite you to join Gregory Bryant as he presents the opening keynote and discusses Intel’s strategy to deliver devices to help people focus, create and connect in more meaningful ways. COMPUTEX is June 5-9 in Taipei, Taiwan.

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A History of PC Innovation (Infographic)

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