Intel Speeds AI Development, Deployment and Performance with New Class of AI Hardware from Cloud to Edge

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What’s New: Today at a gathering of industry influencers, Intel welcomed the next wave of artificial intelligence (AI) with updates on new products designed to accelerate AI system development and deployment from cloud to edge. Intel demonstrated its Intel® Nervana™ Neural Network Processors (NNP) for training (NNP-T1000) and inference (NNP-I1000) — Intel’s first purpose-built ASICs for complex deep learning with incredible scale and efficiency for cloud and data center customers. Intel also revealed its next-generation Intel® Movidius™ Myriad™ Vision Processing Unit (VPU) for edge media, computer vision and inference applications.

“With this next phase of AI, we’re reaching a breaking point in terms of computational hardware and memory. Purpose-built hardware like Intel Nervana NNPs and Movidius Myriad VPUs are necessary to continue the incredible progress in AI. Using more advanced forms of system-level AI will help us move from the conversion of data into information toward the transformation of information into knowledge.”
–Naveen Rao, Intel corporate vice president and general manager of the Intel Artificial Intelligence Products Group

Why They Are Important: These products further strengthen Intel’s portfolio of AI solutions, which is expected to generate more than $3.5 billion in revenue in 2019. The broadest in breadth and depth in the industry, Intel’s AI portfolio helps customers enable AI model development and deployment at any scale from massive clouds to tiny edge devices, and everything in between.

What Intel Announced: Now in production and being delivered to customers, the new Intel Nervana NNPs are part of a systems-level AI approach offering a full software stack developed with open components and deep learning framework integration for maximum use.

The Intel Nervana NNP-T strikes the right balance between computing, communication and memory, allowing near-linear, energy-efficient scaling from small clusters up to the largest pod supercomputers. The Intel Nervana NNP-I is power- and budget-efficient and ideal for running intense, multimodal inference at real-world scale using flexible form factors. Both products were developed for the AI processing needs of leading-edge AI customers like Baidu and Facebook.

“We are excited to be working with Intel to deploy faster and more efficient inference compute with the Intel Nervana Neural Network Processor for inference and to extend support for our state-of-the-art deep learning compiler, Glow, to the NNP-I,” said Misha Smelyanskiy, director, AI System Co-Design at Facebook.

Additionally, Intel’s next-generation Intel Movidius VPU, scheduled to be available in the first half of 2020, incorporates unique, highly efficient architectural advances that are expected to deliver leading performance — more than 10 times the inference performance as the previous generation — with up to six times the power efficiency of competitor processors. Intel also announced its new Intel® DevCloud for the Edge, which along with the Intel® Distribution of OpenVINO™ toolkit, addresses a key pain point for developers — allowing them to try, prototype and test AI solutions on a broad range of Intel processors before they buy hardware.

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Why It Matters: Incredibly complex data, models and techniques are required to advance deep learning reasoning and context, bringing about a need to think differently about architectures.

With most of the world running some part of its AI on Intel® Xeon®™ Scalable processors, Intel continues to improve this platform with features like Intel® Deep Learning Boost with Vector Neural Network Instruction (VNNI) that bring enhanced AI inference performance across the data center and edge deployments. While that will continue to serve as a strong AI foundation for years, the most advanced deep learning training needs for Intel customers call for performance to double every 3.5 months, and those types of breakthroughs will only happen with a portfolio of AI solutions like Intel’s. Intel is equipped to look at the full picture of computing, memory, storage, interconnect, packaging and software to maximize efficiency, programmability and ensure the critical ability to scale up distributing deep learning across thousands of nodes to, in turn, scale the knowledge revolution.

More Context: 2019 AI Summit (Press Kit) |Artificial Intelligence at Intel (Press Kit) | At Hot Chips, Intel Pushes ‘AI Everywhere’

 

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Video: Intel AI for Social Good: Putting an End to Poaching

When placed in protected areas, the TrailGuard artificial intelligence camera uses AI inference at the edge to detect possible poachers and alert park rangers in near real-time, allowing them to take action before animals can be harmed. TrailGuard AI is powered by the Intel Movidius Vision Processing Unit. (Credit: Intel Corporation)

More: Intel AI Protects Animals with National Geographic Society, Leonardo DiCaprio Foundation

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Images: Intel AI Protects Animals with National Geographic Society, Leonardo DiCaprio Foundation

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Photo 1: Intel’s Anna Bethke and RESOLVE’s Eric Dinerstein hide a TrailGuard AI anti-poaching camera system in a tree during a recent demonstration in the mountains south of Monterey, Calif. The Intel Movidius Myriad 2 chip in the camera uses artificial intelligence to identify potential poachers. (Credit: Walden Kirsch/Intel Corporation)

Photo 2: Intel’s Anna Bethke holds the inside of the TrailGuard AI anti-poaching camera system during a recent demonstration in the mountains south of Monterey, Calif. The Intel Movidius Myriad 2 chip in the camera uses artificial intelligence to identify potential poachers. (Credit: Walden Kirsch/Intel Corporation)

Photo 3: RESOLVE’s Eric Dinerstein holds the internal workings of the TrailGuard AI anti-poaching camera system during a recent demonstration in the mountains south of Monterey, Calif. The Intel Movidius Myriad 2 chip in the camera uses artificial intelligence to identify potential poachers. (Credit: Walden Kirsch/Intel Corporation)

Photo 4: Censored photos using a TrailGuard device show poachers in Africa carrying bush meat (left) and moving through a natural area. (Credit: RESOLVE)

More: Intel AI Protects Animals with National Geographic Society, Leonardo DiCaprio Foundation

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Intel AI Protects Animals with National Geographic Society, Leonardo DiCaprio Foundation

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What’s New: Non-profit RESOLVE’s* new TrailGuard AI* camera uses Intel-powered artificial intelligence (AI) technology to detect poachers entering Africa’s wildlife reserves and alert park rangers in near real-time so poachers can be stopped before killing endangered animals. TrailGuard AI builds on anti-poaching prototypes funded by Leonardo DiCaprio Foundation and National Geographic Society.

”By pairing AI technology with human decision-makers, we can solve some of our greatest challenges, including illegal poaching of endangered animals. With TrailGuard AI, Intel’s Movidius technology enables the camera to capture suspected poacher images and alerts park rangers, who will ultimately decide the most appropriate response.”
– Anna Bethke, leader of AI for Social Good at Intel Corporation

How It Works: TrailGuard AI uses Intel® Movidius® Vision Processing Units (VPUs) for image processing, running deep neural network algorithms for object detection and image classification inside the camera. If humans are detected among any of the motion-activated images captured by the camera, it triggers electronic alerts to park personnel so they can mobilize rangers before poachers can do harm.

Why It’s Important: According to RESOLVE, an elephant is killed every 15 minutes by a poacher, at a rate of approximately 35,000 elephants per year. In a decade, experts predict there won’t be any more elephants. Rhinos, gorillas, tigers and other large mammals are also in danger from poachers, as are giraffes, antelopes and wildebeest that are often caught in poachers’ snares.

“Reckless human activity is causing species loss and extinction on an unprecedented scale, with recent reports showing that as many as 60 percent of all wildlife has been wiped out since 1970. If illegal poaching of wildlife continues at the current rate, elephants are just one of the large mammal species that will be completely erased in our lifetime,” said Justin Winters, executive director, Leonardo DiCaprio Foundation, which provided critical funding for prototypes and is working to support broad-based deployment of these systems. “A commitment to protecting wildlife has been at the heart of LDF’s work from the beginning and we are excited to collaborate with Intel and RESOLVE on this breakthrough AI technology, which is set to be a game-changer for park rangers in the monitoring and management of endangered species around the world.”

How It’s Different: TrailGuard AI uses deep neural network algorithms that allow the device to recognize humans and vehicles with a high degree of accuracy. TrailGuard AI builds upon the success of RESOLVE’s first-generation TrailGuard camera deployed in protected reserves that alerts rangers any time it detects motion. With the first-generation camera, rangers receive many photos that they had to manually review to determine if there is a poaching threat or a false-positive triggered by other motion. By adding an additional layer of AI into the system, TrailGuard AI intelligently knows when a potential poacher is present, allowing park rangers to rapidly intercept and apprehend.

TrailGuard AI is powered by the tiny yet powerful Intel® Movidius™ Myriad™ 2 VPU, which delivers visual intelligence to the camera itself, resulting in several important benefits:

  • Limited false-positives: Instead of alerting the rangers anytime there is motion in front of the camera, including from shifting cloud cover, birds and animals, TrailGuard AI only sends images to the rangers when a person or vehicle is detected. Limited false-positives means rangers have more time to focus on their work, instead of spending their time looking through hundreds of false alerts each day.
  • Long battery life: The Intel Movidius VPU powers all of TrailGuard AI’s processing needs – from wake-on-motion to image processing to AI inference to communication protocols — all while running at very low power. It is designed to perform in the wild for up to 1.5 years without depleting the battery. This is a great improvement over the original TrailGuard that has a separate computing unit requiring rangers to undertake the time-consuming and often dangerous task of field maintenance every four to six weeks. TrailGuard AI’s long battery life also means less foot-traffic around the hidden cameras, which could alert poachers to their locations.
  • Small in size: Due to the miniscule size of the Intel Movidius VPU, TrailGuard AI is about the size of a pencil and easier to hide and camouflage from poachers and wild animals.

“The Intel Movidius VPU allowed us to revolutionize TrailGuard AI by adding artificial intelligence to a proven end-to-end solution to stop illegal poaching around the world,” said Eric Dinerstein, director of biodiversity and wildlife at RESOLVE. “In addition to providing the AI technology, Intel engineers worked closely with us to build, test and optimize this incredible anti-poaching solution that will make a real difference in saving animals.”

Where TrailGuard AI is Deployed: In partnership with the National Geographic Society, Leonardo DiCaprio Foundation and others, TrailGuard AI will be deployed in 100 reserves in Africa throughout 2019, starting with Serengeti and Garamba, with plans to expand to Southeast Asia and South America.

“Edge computing technology has the power to revolutionize the way we understand and protect our natural heritage,” said Dr. Fabien Laurier, vice president of National Geographic Labs. “National Geographic is excited to work with Intel on TrailGuard AI and deploy these anti-poaching systems throughout Africa. This collaboration is critical to accelerating conservation and working toward our mission of achieving a planet in balance.”

More Context: Fighting Illegal Poaching with a Purpose-Built AI Camera (Case Study) | RESOLVE | Artificial Intelligence at Intel

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Users Put Intel Movidius Neural Compute Stick to Real-Life Uses

The first-generation Intel NCS, launched in July 2017, has fueled a community of tens of thousands of developers, has been featured in more than 700 developer videos and has been utilized in dozens of research papers.

More: Intel Unveils the Intel Neural Compute Stick 2 at Intel AI Devcon Beijing for Building Smarter AI Edge Devices

neural compute stick 1 Innovator: Peter Ma (USA)
Project: Clean Water AI
Description: According to the World Health Organization, every minute a newborn dies from infection caused by a lack of safe water and an unclean environment. To alleviate this, developer Peter Ma built an AI system to detect harmful bacteria in water in real-time, without needing to connect to the cloud. His Clean Water AI prototype is powered by the Intel Movidius Neural Compute Stick and has a 95 percent accuracy rate.
More Information: https://devmesh.intel.com/projects/ai-bacteria-classification and https://software.intel.com/en-us/articles/ai-driven-test-system-detects-bacteria-in-water
neural compute stick 2 Innovator: Peter Ma (USA)
Project: BlueScan AI (formerly Dr Hazel)
Description: According the CDC, skin cancer is the most common form of cancer in the United States, with more than 80,000 new cases in 2015. After losing a friend to cancer, Peter Ma created BlueScan AI, which uses the Intel Movidius Neural Compute Stick to screen for skin cancer in real time.
More Information: https://devmesh.intel.com/projects/ai-skin-cancer-detection and https://software.intel.com/en-us/articles/ai-helps-with-skin-cancer-screening
neural compute stick 3 Innovator: Christian Haschek (Austria)
Project: NSFW as a service
Description: Innovator Christian Haschek used Intel Movidius Neural Compute Sticks to build a system that scans the internet for illegal images of children. He’s found thousands of images and reports every one to Interpol.
More Information: https://blog.haschek.at/2018/fight-child-pornography-with-raspi-and-deep-learning.html
neural compute stick 4 Innovator: Adam Milton-Barker (Spain)
Project: ASL Classification
Description: Innovator Adam Milton-Barker is using the Intel Movidius Neural Compute Stick to translate American Sign Language to text in real-time
More Information: https://devmesh.intel.com/projects/american-sign-language-asl-classification-using-computer-vision-iot
Innovator: Justin Shenk (Sweden)
Project: Emotion detection
Description: Innovator Justin Shenk is using the Intel Movidius Neural Compute Stick for real-time emotion detection
More Information: https://devmesh.intel.com/projects/emotion-detection-on-movidius-ncs-with-openvino-and-intel-optimized-tensorflow
neural compute stick 6 Innovator: Justin Shenk (Sweden)
Project: Posture Pal
Description: Innovator Justin Shenk is using the Intel Movidius Neural Compute Stick to monitor your posture during computer usage, to provide user feedback and analytics, and to support mindfulness and physical health.
More Information: https://devmesh.intel.com/projects/posture-pal-with-openvino


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From Intel Movidius Neural Compute Stick to Tiny Artificial Intelligence Camera

Today, FLIR® Systems announced the FLIR Firefly® camera family, which incorporates the Intel® Movidius™ Myriad™ 2 Vision Processing Unit (VPU) for artificial intelligence at the edge. The Firefly* combines a new machine vision platform with the power of deep learning to address complex and subjective problems, such as classifying the quality of a solar panel or determining whether fruit is of export quality.

FLIR engineers accelerated the Firefly’s development cycle using the Intel® Movidius™ Neural Compute Stick (NCS) for prototype development. For large-scale commercial production, they  ported that development work to the Intel Movidius Myriad 2 VPU. By rapidly prototyping on the Intel Movidius Neural Compute Stick and the Neural Compute SDK, FLIR streamlined the development of machine learning in the camera. The production version of the Firefly uses the tiny, stand-alone Intel Movidius Myriad 2 VPU to perform two roles at the edge: image signal processing and open platform inference.

The 27- by 27-milimeter Firefly is roughly the size of a U.S. quarter.

More: Reimagined Machine Vision with On-Camera Deep Learning (Case Study) | FLIR Systems Announces Industry-First Deep Learning-Enabled Camera Family (News Release) | Intel Movidius (Press Kit) | All Intel Explainers

flir ncs
The FLIR Firefly camera family announced on Oct. 18, 2018, incorporates the Intel Movidius Myriad 2 Vision Processing Unit. What started as three distinct devices is transformed into the 27- by 27-milimeter Firefly unit. (Credit: FLIR)

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Intel and Microsoft Enable AI Inference at the Edge with Intel Movidius Vision Processing Units on Windows ML

Today during Windows Developer Day, Microsoft announced Windows* ML, which enables developers to perform machine learning tasks in the Windows OS. Windows ML efficiently uses hardware for any given artificial intelligence (AI) workload and intelligently distributes work across multiple hardware types – now including Intel Vision Processing Units (VPU). The Intel VPU, a purpose-built chip for accelerating AI workloads at the edge, will allow developers to build and deploy the next generation of deep neural network applications on Windows clients.

Press Kit: Intel Movidius

The Intel® Movidius™ Myriad™ X VPU is the industry’s first system-on-chip shipping with a dedicated neural compute engine for hardware acceleration of deep learning inference at the edge. This third-generation VPU from Intel is specifically designed to run deep neural networks at high speed and low power to offload specific AI tasks from burdening other hardware.

By implementing support for Intel’s VPU in Windows ML, Microsoft is providing independent software vendors the option of a dedicated deep learning inference solution, freeing up traditional hardware for other workloads or reducing the overall system power consumption without requiring custom code. The Windows ML and Intel VPU combination has the potential to enable more intelligent client applications and core OS features, such as personal assistants, enhanced biometric security, smart music, and photo search and recognition.

“Intel Movidius VPU technology will deliver increasingly sophisticated AI experiences for the hundreds of millions of Microsoft users worldwide,” said Intel’s Remi El-Ouazzane, Intel vice president and general manager of Intel Movidius. “This is just the latest example of how Intel is accelerating the promise of bringing AI from the data center to edge devices through our high-performance, low-power vision processor technology.”

“We’re excited to work closely with Intel to enable developers around the world to build engaging and magical AI-powered experiences using Windows ML and the Intel Movidius VPU,” said Kevin Gallo, corporate vice president, Windows Developer Platform, Microsoft.

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

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Intel Introduces ‘Intel AI: In Production’ Program – a New Way to Bring Artificial Intelligence Devices to Market

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The AI Core from AAEON’s UP Bridge the Gap is a mini-PCIe module that features an Intel Movidius Myriad 2 VPU designed to work with a wide range of x86 host platforms. It is shown with the Intel Movidius Neural Compute Stick. (Credit: Intel Corporation)

Intel today unveiled “Intel AI: In Production,” a new program that makes it easier for developers to bring their artificial intelligence prototypes to market. Since its introduction last July, the Intel® Movidius™ Neural Compute Stick (NCS) has gained a developer base in the tens of thousands.

Press Kit: Intel Movidius

Once developers have a prototype, the next step is to take it into production, which can be challenging and costly for small companies and entrepreneurs. To make it easier, Intel selected AAEON Technologies*, a leading manufacturer of advanced industrial and embedded computing platforms, as the first Intel AI: In Production partner. Through the program, AAEON provides two streamlined production paths for developers integrating the low-power Intel® Movidius ™ Myriad™ 2 Vision Processing Unit (VPU) into their product designs.

The first option is the new AI Core from AAEON’s UP Bridge the Gap. It is a mini-PCIe module that features an Intel Movidius Myriad 2 VPU designed to work with a wide range of x86 host platforms. The AI Core delivers the low-power, high-performance capabilities of the Intel Movidius Myriad 2 VPU deep neural networks accelerator. It is also compatible with the Intel® Movidius™ Neural Compute SDK software suite already used by thousands of machine learning developers and companies worldwide.

For companies requiring further customization, AAEON offers development and board manufacturing services that will allow companies to move from Neural Compute Stick-based prototypes to custom boards in a streamlined manner.

“Intel AI: In Production means we can expect many more innovative AI-centric products coming to market from the diverse and growing segment of technologies utilizing Intel technology for low-power inference at the edge,” said Remi El-Ouazzane, Intel vice president and general manager of Intel Movidius.

“Intel Movidius Myriad 2 technology makes AI Core one of the most powerful and versatile AI hardware accelerators for edge computing,” said Fabrizio Del Maffeo, AAEON vice president, managing director of AAEON Technology Europe and founder of UP Bridge the Gap. “AI Core bridges the gap between the lab and volume production, allowing the innovators who adopted the Intel Movidius Neural Compute Stick to roll out a field deployment.”

Intel customers already are building products through the Intel AI: In Production program. The first is by CONEX*, a Diam International company and global leader in the design and creation of point-of-sale display systems for the cosmetics industry.

“Our innovation team started prototyping advanced retail deep learning algorithms and tested the Intel Movidius Neural Compute Stick,” said Nicolas Lorin, president of CONEX. “Now through the Intel AI: In Production program, CONEX will be able to rapidly go from our validated prototypes to actual end products. Thanks to this new path to production, we will be deploying an AI-enhanced, point-of-sale retail device to some of the largest cosmetic goods retailers as soon as this spring.”

Intel, the Intel logo, Movidius and Myriad are trademarks of Intel Corporation in the United States and other countries.

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Movidius Myriad X VPU

Intel introduced its new Movidius™ Myriad™ X vision processing unit (VPU), advancing Intel’s end-to-end portfolio of artificial intelligence solutions to deliver more autonomous capabilities across a wide range of product categories from drones and robotics to smart cameras and virtual reality. Myriad X is world’s first system-on-chip shipping with a dedicated Neural Compute Engine for accelerating deep learning inferences at the edge. The Neural Compute Engine is an on-chip hardware block specifically designed to run deep neural networks at high speed and low power without compromising accuracy, enabling devices to see, understand and respond to their environments in real time.

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Movidius Myriad X VPU

Intel introduced its new Movidius™ Myriad™ X vision processing unit (VPU), advancing Intel’s end-to-end portfolio of artificial intelligence solutions to deliver more autonomous capabilities across a wide range of product categories from drones and robotics to smart cameras and virtual reality. Myriad X is world’s first system-on-chip shipping with a dedicated Neural Compute Engine for accelerating deep learning inferences at the edge. The Neural Compute Engine is an on-chip hardware block specifically designed to run deep neural networks at high speed and low power without compromising accuracy, enabling devices to see, understand and respond to their environments in real time.

News

Resources

Images

The Movidius™ Myriad™ X VPU delivers artificial intelligence at

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Videos

 

 

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