Intel’s partnership with the China Foundation for Cultural Heritage Conservation (CFCHC) to protect and preserve the Jiankou section of the Great Wall of China is underway. And experts from Wuhan University LIESMARS have been added to the project, leveraging Intel technologies to preserve the wall more efficiently and safely than before.
An Intel Falcon 8+ drone is prepared for aerial inspection of the Great Wall of China. In 2018, Intel Corporation announced a partnership with the China Foundation for Cultural Heritage Conservation to protect and restore the Great Wall of China. (Credit: Intel Corporation
This is the next step in Intel’s recently announced commitment to inspect and preserve the Jiankou section of the Great Wall. By incorporating advanced technologies into this partnership, Intel is giving conservationists new tools to protect history and help preserve one of the great architectural wonders of the world.
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Tags: CFCHC, china, Falcon, GreatWall, Intel, Jiankou
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 What’s New: Today at Baidu* Create in Beijing, Intel Vice President Gadi Singer shared a series of collaborations with Baidu on artificial intelligence (AI), including powering Baidu’s Xeye* a new AI retail camera with Intel® Movidius™ vision processing units (VPUs); highlighting Baidu’s plans to offer workload acceleration as a service using Intel® FPGAs; and optimizing PaddlePaddle*, Baidu’s deep learning framework for Intel® Xeon® Scalable processors.
“From enabling in-device intelligence, to providing data center scale on Intel Xeon Scalable processors, to accelerating workloads with Intel FPGAs, to making it simpler for PaddlePaddle developers to code across platforms, Baidu is taking advantage of Intel’s products and expertise to bring its latest AI advancements to life.”
–Gadi Singer, vice president and architecture general manager, Artificial Intelligence Products Group, Intel
How the Camera Works: Baidu’s Xeye camera uses Intel® Movidius™ Myriad™ 2 VPUs to deliver low-power, high-performance visual intelligence for retailers. Thanks to Intel’s purpose-built VPU solutions coupled with Baidu’s advanced machine learning algorithms, the camera can analyze objects and gestures, while also detecting people to provide personalized shopping experiences in retail settings.
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Tags: Acceleration, AI, artificial intelligence, Baidu, camera, nGraph, PaddlePaddle
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Intel and Ecosystem Partners Introduce New Solutions to Secure Data in Emerging Technologies
 By Rick Echevarria
The future of a trusted and secure computing environment hinges on our collective ability to deliver solutions that improve the performance across a variety of workloads, while also optimizing security.
This week, at Cyber Week in Israel, I am joined by partners, customers, and cybersecurity industry and policy leaders from across the globe. Intel is committed to providing silicon-based security solutions that address the most pressing issues. There are three key themes at the conference, highlighting the challenges and opportunities facing our industry.
Emerging Workloads Deliver More Data to Analyze and Secure
Incoming data is increasingly difficult to effectively leverage without the computing power to process and learn from its growing volume and complexity. Machine learning (ML) algorithms, and other artificial intelligence (AI) applications and capabilities, have achieved remarkable results and are being extensively used in different domains. ML algorithms often require access to sensitive data, especially as the focus on data privacy increases around the world. Limiting access to the right data may limit the outcomes that can be achieved with the use of AI. In the case of blockchain, the security and privacy of data join transaction scalability as key technical considerations.
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Tags: blockchain, Intel, security
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Intel researchers are taking new steps toward quantum computers by testing a tiny new “spin qubit” chip. The new chip was created in Intel’s D1D Fab in Oregon using the same silicon manufacturing techniques that the company has perfected for creating billions of traditional computer chips. Smaller than a pencil’s eraser, it is the tiniest quantum computing chip Intel has made.
 A 2018 photo shows Intel’s new quantum computing chip balanced on a pencil eraser. Researchers started testing this “spin qubit chip” at the extremely low temperatures necessary for quantum computing: about 460 degrees below zero Fahrenheit. Intel projects that qubit-based quantum computers, which operate based on the behaviors of single electrons, could someday be more powerful than today’s supercomputers. (Credit: Walden Kirsch/Intel Corporation) The new spin qubit chip runs at the extremely low temperatures required for quantum computing: roughly 460 degrees below zero Fahrenheit – 250 times colder than space.
The spin qubit chip does not contain transistors – the on/off switches that form the basis of today’s computing devices – but qubits (short for “quantum bits”) that can hold a single electron. The behavior of that single electron, which can be in multiple spin states simultaneously, offers vastly greater computing power than today’s transistors, and is the basis of quantum computing.
The zigzag lines in the photo are printed wires connecting the chip’s qubits to the outside world.
One feature of Intel’s tiny new spin qubit chip is especially promising. Its qubits are extraordinarily small – about 50 nanometers across and visible only under an electron microscope. About 1,500 qubits could fit across the diameter of a single human hair.
This means the design for new Intel spin qubit chip could be dramatically scaled up. Future quantum computers will contain thousands or even millions of qubits — and will be vastly more powerful than today’s fastest supercomputers.
Tags: Intel, multiple spin states, quantum bits, Qubits, spin qubit
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Intel Optane DC Persistent Memory Represents a New Class of Memory and Storage Technology Architected to Extract Further Value from Data
By Lisa Spelman
We’ve all heard about escalating mountains of data – and yes, there is a tremendous amount of data generated daily that must be stored, secured and organized. More interesting than the amount of data is the value it represents. Value that comes from analysis and the resulting insights. Data may store the next great business opportunity, societal advancement or scientific discovery.
While we’ve made great progress as an industry in providing the infrastructure, tools and best practices to drive this analysis, limitations are also emerging. Not only is the volume and variety of data growing, but the velocity of desired insights is accelerating. To really tap into all of this data, we must remove the bottlenecks that restrict its flow and readiness for processing.
Today, we’re sharing the first in-depth look at how Intel is reimagining the memory and storage hierarchy for application developers and data solution providers with the upcoming introduction of Intel® Optane™ DC persistent memory. Intel Optane DC persistent memory represents a new class of memory and storage technology architected specifically for data center usage. One that we believe fundamentally breaks through some of the constricting methods for using data that have governed computing for more than 50 years.
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Tags: DRAM, HDD, Intel, memory, SSD
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Intel’s Gadi Singer believes his most important challenge is his latest: using artificial intelligence (AI) to reshape scientific exploration.
In a Q&A timed with the first Intel AI DevCon event, the
 Gadi Singer, vice president and architecture general manager for the Artificial Intelligence Products Group at Intel, uses artificial intelligence to reshape scientific exploration. Before his role with AI, the 35-year Intel veteran helped create the first Pentium processor; led development of the first Xeon processors and the first Atom processor; and oversaw architecture for generations of the Intel Core processors. (Photo Credit: Walden Kirsch/Intel Corporation) Intel vice president and architecture general manager for its Artificial Intelligence Products Group discussed his role at the intersection of science — computing’s most demanding customer — and AI, how scientists should approach AI and why it is the most dynamic and exciting opportunity he has faced.
Q. How is AI changing science?
Scientific exploration is going through a transition that, in the last 100 years, might only be compared to what happened in the ‘50s and ‘60s, moving to data and large data systems. In the ‘60s, the amount of data being gathered was so large that the frontrunners were not those with the finest instruments, but rather those able to analyze the data that was gathered in any scientific area, whether it was climate, seismology, biology, pharmaceuticals, the exploration of new medicine, and so on.
Today, the data has gone to levels far exceeding the abilities of people to ask particular queries or look for particular insights. The combination of this data deluge with modern computing and deep learning techniques is providing new and many times more disruptive capabilities.
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Tags: AI, artificial intelligence, Intel
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What’s New: Intel collaborates with Novartis* on the use of deep neural networks (DNN) to accelerate high content screening – a key element of early drug discovery. The collaboration team cut time to train image analysis models from 11 hours to 31 minutes – an improvement of greater than 20 times1.
Collaboration team members from Novartis and Intel used eight CPU-based servers, a high-speed fabric interconnect and optimized TensorFlow to achieve the improvement in time needed to process a dataset of 10K images.
Why It’s Important: High content screening of cellular phenotypes is a fundamental tool supporting early drug discovery. The term “high content” signifies the rich set of thousands of pre-defined features (such as size, shape, texture) that are extracted from images using classical image-processing techniques. High content screening allows analysis of microscopic images to study the effects of thousands of genetic or chemical treatments on different cell cultures.
The promise of deep learning is that relevant image features that can distinguish one treatment from another are “automatically” learned from the data. By applying deep neural network acceleration, biologists and data scientists at Intel and Novartis hope to speed up the analysis of high content imaging screens. In this joint work, the team is focusing on whole microscopy images as opposed to using a separate process to identify each cell in an image first. Whole microscopy images can be much larger than those typically found in deep learning datasets. For example, the images used in this evaluation are more than 26 times larger than images typically used from the well-known ImageNet* dataset of animals, objects and scenes.
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Tags: Deep learning, Image analysis, Intel, Neural Network, novartis, Phi Processor, TensorFlow, Xeon
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New Toolkit Already in Use at Agent Vi, Dahua, Dell, Current by GE, GE Healthcare, Hikvision and Honeywell
 By Tom Lantzsch
It’s been an amazing year leading the Internet of Things (IoT) Group at Intel. During this time we have been working hard to define and develop a data-driven technology foundation for industry innovation. Our strategy is to drive end-to-end distributed computing in every vertical by focusing on silicon platforms and workload consolidation at the edge.
Critical to our success is aligning our ecosystem of partners and developers to deliver the benefits. This focused effort is paying off, as Intel’s IoT business grew by 20 percent in 2017 and continued with strong growth in this year’s first quarter.
We are seeing significant growth in IoT markets worldwide, driven in part by a dramatic increase in vision applications, particularly those leveraging artificial intelligence (AI). These imaging and video use cases span nearly every IoT segment. They include finding product defects on assembly lines, managing inventory in retail, identifying equipment maintenance needs in remote locations, and enabling public safety in cities and airports. They all leverage high-resolution cameras and create extraordinary amounts of data, which needs to be aggregated and analyzed.
More: OpenVINO™ Toolkit Accelerates CV Development across Intel® Platform (Adam Burns Blog) | Internet of Things News
Given this expansive data growth, Intel announces the OpenVINO™ (Open Visual Inference & Neural Network Optimization) toolkit. The OpenVINO toolkit is designed to fast-track development of high-performance computer vision and deep learning inference applications at the edge. It is the latest offering in the comprehensive Intel® Vision Products portfolio of hardware and software accelerating deep learning and transforming vision data into business insights.
Intelligence and Autonomous Technology Begins with Vision
Processing high-quality video requires the ability to rapidly analyze vast streams of data near the edge and respond in real time, moving only relevant insights to the cloud asynchronously. To process video data efficiently, companies need the right solution for the job. Unlike others with a one-size-fits-all philosophy, Intel believes the market requires a powerful portfolio of scalable hardware and software solutions to move into an intelligent data-powered future. This immediately includes widely deployed and available Intel computing products, including those with integrated graphics, Intel FGPAs and Intel® Movidius™ VPU (Vision Processing Unit).
With the addition of the OpenVINO toolkit to the Intel Vision Product lineup, Intel’s vision solution provides the capability to distribute AI solutions from the edge to the network to the cloud across a diverse set of products. This empowers our customers with the flexibility to economically distribute vision solutions for actionable business insights.
Intel’s Extensive Partner Ecosystem
Intel® Vision Products and the OpenVino toolkit are being used by global partners such as Dahua*, for smart city and traffic solutions, GE Healthcare* in medical imaging, and Hikvision* for industrial and manufacturing safety. Additional companies include Agent Vi*, Current by GE*, Dell* and Honeywell*.
Our deep collaboration with these industry leaders makes one thing clear: Intel provides a future that’s intelligent and transformative.
Technology Choice and Flexibility with Performance
The new OpenVINO toolkit combined with a broad range of advanced silicon provides a complete high-performance solution for edge-to-cloud video analytics and deep learning. It empowers developers to easily deploy deep learning inference and computer vision solutions, leveraging a wide range of common software frameworks like TensorFlow*, MXNet* and Caffe*.
Intel Vision Products, combined with the OpenVINO toolkit, provide developers the flexibility, and choice with performance and power to accommodate the wide range IoT infrastructure.
- Intel CPUs with integrated graphics are commonly used and provide developers access to widely deployed systems that are consistent with existing architectures and products.
- Intel FPGAs provide raw throughput and programming flexibility to rapidly adapt to new networks and applications.
- The Intel Movidius VPU provides cost and power efficiency for constrained environments while delivering performance required for a broad range of applications.
Intel’s comprehensive vision strategy stretching from the camera to the cloud will accelerate the adoption of video technologies across industries.
Our deep collaboration with businesses has made one thing clear: Intel no longer sells parts; it is providing an easy and accessible vision.
For more information, check out the OpenVINO toolkit or Intel Vision Products. Come talk to us at the upcoming Embedded Vision Summit May 22-24 or at AI Devcon May 23-24.
Tom Lantzsch is senior vice president and general manager of the Internet of Things (IoT) Group at Intel Corporation.
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Tags: Intel, IOT, Movidius, OpenVINO
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NBA and Intel Capital Emerging Technology Initiative will Identify Potential Partnership and Investment Opportunities with New Technologies at the Cutting Edge of Sports and Entertainment
NEWS HIGHLIGHTS
- At the Intel Capital Global Summit 2018, the NBA and Intel Capital announced the “NBA + Intel Capital Emerging Technology Initiative”
- The NBA and Intel Capital will jointly identify and evaluate global technology companies for potential investment and other collaboration opportunities
- The multiyear collaboration targets technology disruption in the sports and entertainment industries
PALM DESERT, Calif., May 8, 2018 – The National Basketball Association (NBA)* and Intel Capital today announced a sports and entertainment technology innovation collaboration called the “NBA + Intel Capital Emerging Technology Initiative.” The multiyear collaboration will foster the identification, formation and growth of technology companies that have the potential to impact the future of the NBA, sports and entertainment.
This initiative aims to identify new technologies from global companies at all stages, but particularly U.S.-based startups that the NBA and Intel Capital will evaluate for potential partnership and investment opportunities. Among the companies that the NBA and Intel Capital will assess will be those with new technology solutions that can enhance the NBA game on the court, the overall fan experience and the sports industry worldwide. In addition, the NBA and Intel Capital will provide mentorship, strategic planning and business development support for the selected companies.
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Tags: Emerging Technology, NBA
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What’s New: Intel plans to break its world record title for most drones flown simultaneously with more than 1,500 drones flown as part of the company’s 50th anniversary events this summer.
“Intel has been advancing technology for 50 years. To celebrate that fact and showcase our ongoing innovation, we’re looking to break another drone light show record with our Intel Shooting Star drones and related technology.”
– Anil Nanduri, vice president and general manager, Intel drone team
 Intel Shooting Star drones form the Olympics rings as part of the Olympic Winter Games PyeongChang 2018 opening ceremony drone light show. (Credit: Intel Corporation) How It Works: The current record of 1,218 Intel® Shooting Star™ drones was set earlier this year. The new show featuring more than 1,500 drones is planned for this summer and will be a live one-time public show at an Intel site for employees and their families.
The Intel Shooting Star drones are unmanned aerial vehicles (UAVs) specifically designed for entertainment purposes, equipped with LED lights that can create countless color combinations and easily be programmed for any animation. The fleet of drones is controlled by one pilot.
Intel’s Goals: The technology employed in our drone light shows can be applied to other applications, including search and rescue, where multiple drones can look for a lost hiker, or commercial applications for large infrastructure inspections that reduce inspection time and improve efficiency.
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Tags: 50th anniversary, drone, drone light show, drones, Intel, Shooting Star, unmanned drones
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By Rick Echevarria
