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it hardware


「COMPUTEX 2022」で「NVIDIA Jetson Orin」搭載のエッジ AI や組み込みシステムを紹介 日本語字幕の基調講演動画も公開 - ロボスタ ロボスタ - ロボット情報WEBマガジン

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シェア 0 ツイート 0 はてブ 1 NVIDIAは、世界中の30を超える大手テクノロジ パートナーが5月24日から27日まで台北で開催しているCOMPUTEX 2022にて、「NVIDIA Jetson AGX Ori […]


AI Hardware Technology Imitates Changes in Neural Network Topology

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A group of researchers at The Korea Advanced Institute of Science and Technology (KAIST) has proposed a new system inspired by the neuromodulation of the brain, which is called a "stashing system." This newly proposed system requires less energy consumption.


Nvidia leaves a 'paper' trail

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Groundbreaking research has always been an important aspect of SIGGRAPH, as scientists and researchers present the latest industry advancements to conference-goers. So, the fact that Nvidia, in collaboration with top academic researchers at 14 universities, will be presenting a record number (16) of research papers at this year's conference is astounding. When a reinforcement learning model is used to develop a physics-based animated character, the AI typically learns just one skill at a time: walking, running, or perhaps cartwheeling. But researchers from UC Berkeley, the University of Toronto, and Nvidia have created a framework that enables AI to learn a whole repertoire of skills--demonstrated with a warrior character who can wield a sword, use a shield, and get back up after a fall. Achieving these smooth, lifelike motions for animated characters is usually tedious and labor-intensive, with developers starting from scratch to train the AI for each new task.


NetApp Teams with NVIDIA to Accelerate AI and HPC Infrastructure

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NetApp, a global, cloud-led, data-centric software company, announced that NetApp EF600 all-flash NVMe storage combined with the BeeGFS parallel file system is now certified for NVIDIA DGX SuperPOD. The new certification simplifies artificial intelligence (AI) and high-performance computing (HPC) infrastructure to enable faster implementation of these use cases. Since 2018, NetApp and NVIDIA have served hundreds of customers with a range of solutions, from building AI Centers of Excellence to solving massive-scale AI training challenges. The qualification of NetApp EF600 and BeeGFS file system for DGX SuperPOD is the latest addition to a complete set of AI solutions that have been developed by the companies. NetApp's portfolio of NVIDIA-accelerated solutions includes ONTAP AI to eliminate guesswork for faster adoption by using a field-proven reference architecture as well as a preconfigured, integrated solution that is easy to procure and deploy in a turnkey manner.


NetApp Teams with NVIDIA to Accelerate HPC and AI with Turnkey Supercomputing Infrastructure

#artificialintelligence

NetApp, a global, cloud-led, data-centric software company, announced that NetApp EF600 all-flash NVMe storage combined with the parallel file system is now certified for NVIDIA DGX SuperPOD. The new certification simplifies artificial intelligence (AI) and high-performance computing (HPC) infrastructure to enable faster implementation of these use cases. Since 2018, NetApp and NVIDIA have served hundreds of customers with a range of solutions, from building AI Centers of Excellence to solving massive-scale AI training challenges. The qualification of NetApp EF600 and BeeGFS file system for DGX SuperPOD is the latest addition to a complete set of AI solutions that have been developed by the companies. "The NetApp and NVIDIA alliance has delivered industry-leading innovation for years, and this new qualification for NVIDIA DGX SuperPOD builds on that momentum," said Phil Brotherton, Vice President of Solutions and Alliances at NetApp.


The AI Powered Telco

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This eBook explores some of the use cases driving telco investment in AI, as well as ways organizations can benefit from becoming AI-powered.


How AI/ML Improves Fab Operations

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Chip shortages are forcing fabs and OSATs to maximize capacity and assess how much benefit AI and machine learning can provide. This is particularly important in light of the growth projections by market analysts. The chip manufacturing industry is expected to double in size over the next five years, and collective improvements in factories, AI databases, and tools will be essential for doubling down on productivity. "We're not going to fail on this digital transformation, because there's no option," said John Behnke, general manager in charge of smart manufacturing at Inficon. "All the fabs are collectively going to make 20% to 40% more product, but they can't get a new tool right now for 18 to 36 months. To leverage all this potential, we're going to overcome the historical human fear of change."


AI students optimistic about healthcare innovation at Intel Vision

ZDNet

Nate writes about the intersection of education and technology. He's also worked as a newspaper staff writer covering K-12 and higher education, business, local government, and public safety. As the pandemic nears its third year, healthcare remains top of mind for many people. Intel on Tuesday gave three students a high-profile platform at Intel Vision 2022. These young innovators all chose to share how they'd use technology to address healthcare challenges.


More Freedom on the Freeway: AI Lifts Malaysia's Toll Barriers

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Working as an aerospace engineer in Malaysia, Chee How Lim dreamed of building a startup that could really take off. Today his company, Tapway, is riding a wave of computer vision and AI adoption in Southeast Asia. A call for help in 2019 with video analytics led to the Kuala Lumpur-based company's biggest project to date. Malaysia's largest operator of toll highways, PLUS, wanted to reduce congestion for its more than 1.5 million daily travelers. A national plan called for enabling car, taxi, bus and truck traffic to flow freely across multiple lanes -- but that posed several big challenges.


Neural Network Generates Global Tree Height Map, Reveals Carbon Stock Potential

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A new study from researchers at ETH Zurich's EcoVision Lab is the first to produce an interactive Global Canopy Height map. Using a newly developed deep learning algorithm that processes publicly available satellite images, the study could help scientists identify areas of ecosystem degradation and deforestation. The work could also guide sustainable forest management by identifying areas for prime carbon storage--a cornerstone in mitigating climate change. "Global high-resolution data on vegetation characteristics are needed to sustainably manage terrestrial ecosystems, mitigate climate change, and prevent biodiversity loss. With this project, we aim to fill the missing data gaps by merging data from two space missions with the help of deep learning," said Konrad Schindler, a Professor in the Department of Civil, Environmental, and Geomatic Engineering at ETH Zurich.