The first NVIDIA AI Conference in Sydney on September 4 will kick off with two keynote addresses. Marc Hamilton, Vice President of Solutions Architecture and Engineering, NVIDIA, will talk about Transforming Industries With AI. Jason Humphrey (right), Head of Retail Risk, ANZ Bank, will then share on Creating the Infrastructure to Undertake Deep Learning.
NetApp has introduced NetApp ONTAP AI proven architecture to simplify, accelerate and scale the data pipeline across edge, core and cloud for deep learning deployments and to help customers achieve real business impact with AI.
Daimler and Bosch have chosen NVIDIA Drive Pegasus AI supercomputer to power their robotaxis, which are expected to start testing in Silicon Valley next year.
On June 13, Intel had the GPU world in a flurry when it tweeted “Intel’s first GPU coming in 2020”. The media were quick to post stories of this incoming new GPU, which would add interesting competition to a market dominated by NVIDIA with AMD a distant second.
The United States has regained its pole position at the fastest supercomputer race with the aptly named Summit.
Taiwan is going big on artificial intelligence (AI) and its Ministry of Science and Technology (MOST) will be collaborating with NVIDIA on AI initiatives.
NVIDIA has introduced the NVIDIA HGX-2, the first unified computing platform for both artificial intelligence (AI) and high performance computing (HPC).
Information and communications technology (ICT) spending in Asia/Pacific (excluding Japan) will hit US$1.5 trillion in 2021, according to IDC.
Security is a major concern in airports, government buildings and major infrastructures around the world. Governments need to be able to quickly identify potential threats among the many people that enter and exit their countries daily. An effective facial recognition system is critical in safeguarding the country and critical infrastructures.
Tokyo-based startup incubator DEEPCORE is partnering NVIDIA to support AI startups and promote university research programmes across Japan.
NVIDIA CEO Jensen Huang (above) dubbed it the “world’s biggest GPU”. And he certainly wasn’t kidding as the NVIDIA DGX-2 is a massive 350-pounder that delivers an amazing two petaflops of computational power.
The GPU Technology Conference (GTC) has hit new highs with a record of more than 8,000 participants, and filling the entire San Jose McEnery Convention Center.
Marina Bay Sands Expo and Convention Centre was a hive of activities of a different sort as more than 700 technologists from 21 countries converged for EmTech Asia on January 30 and 31.
Think artificial intelligence (AI) and the advent of powerful thinking machines and images of Arnold Schwarzenegger of The Terminator come to mind.
It’s easy to understand why the media and gamers were getting all excited following NVIDIA’s announcement of the Titan V. After all, it’s dubbed as “the world’s most powerful GPU for the PC, driven by the world’s most advanced GPU architecture, NVIDIA Volta”.
Singapore’s aim to be an artificial intelligence (AI) hub has been boosted with two initiatives — the setting up of a shared AI platform for researchers and the awarding of scholarships to develop AI talents.
At the NVIDIA AI Conference in Singapore yesterday, NVIDIA and Singapore’s National Supercomputing Centre (NSCC) agreed to establish a platform to bolster AI capabilities among its academic, research and industry stakeholders and in support of AI Singapore (AISG), a national programme set up in May to drive AI adoption, research and innovation in Singapore.
Called AI.Platform@NSCC, it will provide AI training, technical expertise and computing services to AISG, which brings together all Singapore-based research and tertiary institutions, including the National University of Singapore (NUS), Nanyang Technological University (NTU), Singapore University of Design and Technology (SUTD), Singapore Management University (SMU), as well as research institutions in the Agency for Science, Technology and Research (A*STAR).
The two keynote speakers are Dr David B Kirk, NVIDIA Fellow and inventor of more than 60 patents and patent applications relating to graphics design; and Dr Wanli Min, AI scientist of Alibaba Cloud, who will touch on A Revolutionary Road to Data Intelligence.
Besides these two, there are special guest-of-honour Chng Kai Fong, Managing Director of Singapore’s Economic Development Board, and a panel discussion on AI for the Future of Singapore Economy.
With artificial intelligence (AI) being a hot topic this year, NVIDIA is organising its first AI-focused regional conference in Singapore on October 23 and 24.
The event will be held in two parts with the first day focusing on Deep Learning Institute (DLI) workshop where participants will received hands-on training on deep learningl and the second day filled with keynote addresses, panel discussion and three tracks. It is targeted at data scientists and senior decision makers in the field of AI in both public and private sectors.
“Singapore is aiming to be the world’s first smart nation and AI is playing a critical role. NVIDIA is well positioned to help drive the government’s Smart Nation initiative with the development of solutions based on AI. Our GPUs are making headlines across the world by enabling many breakthroughs in various industries using deep learning,” said Raymond Teh, Vice President of APAC sales and marketing at NVIDIA.
“I’m amazed at the quality of the papers presented. The project teams’ line of thinking and breakthrough concepts are refreshing,” exclaimed a leading artificial intelligence (AI) scientist at the International Conference on Machine Learning (ICML) in Sydney.
International Convention Centre Sydney was a massive hive of activities as 3,000 of the world’s top researchers, developers and students in AI gathered for ICML. The participants moved rapidly from one workshop to another and took great interest in the exhibition booths of top deep learning proponents such as NVIDIA, Google and Facebook.
With so many bright young talents. the event proved to be a good fishing ground for vendors as they held recruitment interviews at their booths, as well as posted openings on the board.
They were participating in Computer Vision and Pattern Recognition (CVPR) conference in Honolulu.
“AI is the most powerful technology force that we have ever known. I’ve seen everything. I’ve seen the coming and going of the client-server revolution. I’ve seen the coming and going of the PC revolution. Absolutely nothing compares,” said Jensen Huang, CEO of NVIDIA.
NVIDIA is bringing its wealth of artificial intelligence (AI) solutions and expertise to the International Conference on Machine Learning (ICML) in Sydney.
Held at Sydney International Convention Centre from August 6 to 11, the event is expected to attract up to 3,000 participants, primarily faculty, researchers and PhD students in machine learning, data science, data mining, AI, statistics, and related fields.
The NVIDIA booth (Level 2, The Gallery, Booth #4) will feature many firsts in Australia, such as demos on 4K style transfer, a deep neural network to extract a specific artistic style from a source painting, and then synthesises this information with the content of a separate video; self-driving auto using the Drive PX2 AI car computing platform; Deepstream SDK that simplifies development of high performance video analytics applications powered by deep learning; and NVIDIA Isaac, the AI-based software platform lets developers train virtual robots using detailed and highly realistic test scenarios.
NVIDIA and Baidu have teamed up to bring artificial intelligence (AI) technology to cloud computing, self-driving vehicles and AI home assistants.
Baidu will deploy NVIDIA HGX architecture with Tesla Volta V100 and Tesla P4 GPU accelerators for AI training and inference in its data centres. Combined with Baidu’s PaddlePaddle deep learning framework and NVIDIA’s TensorRT deep learning inference software, researchers and companies can harness state-of-the-art technology to develop products and services with real-time understanding of images, speech, text and video.
To accelerate AI development, the companies will work together to optimise Baidu’s open-source PaddlePaddle deep learning framework on NVIDIA’s Volta GPU architecture.
NVIDIA is among six technology companies to receive a total of US$258 funding from the US Department of Energy’s Exascale Computing Project (ECP).
The funding is to accelerate the development of next-generation supercomputers with the delivery of at least two exascale computing systems, one of which is targeted by 2021.
Such systems would be about 50 times more powerful than the US’ fastest supercomputer, Titan, located at Oak Ridge National Laboratory.
At the keynote of NVIDIA AI Forum, NVIDIA CEO and Founder Jensen Huang called “Taiwan is the home of NVIDIA’s GeForce system”.
Video gaming is a US$100 billion industry and “GeForce PC gaming is the number one platform, nearly 200 million GeForce installed base,” declared Huang.
He announced the new NVIDIA Max-Q platform which lets gaming notebook makers produce faster, slimmer and quieter machines.
NVIDIA has pulled yet another trick out of its always-filled hat of technology goodies with the launch of Volta, the world’s most powerful GPU computing architecture. At his keynote address at GTC in San Jose, NVIDIA CEO Jensen Huang dubbed it “the next level of computer projects”.
Volta is created to drive the next wave of advancement in artificial intelligence (AI) and high performance computing.
The first Volta-based processor is the NVIDIA Tesla V100 data centre GPU, which brings extraordinary speed and scalability for AI inferencing and training, as well as for accelerating HPC and graphics workloads.
Can’t say this was unexpected as NVIDIA retorts Google’s claim that its custom ASIC Tensor Processing Unit (TPU) was up to 30 times faster than CPUs and NVIDIA’s K80 G for inferencing workloads.
NVIDIA pointed out that Google’s TPU paper has drawn a clear conclusion – without accelerated computing, the scale-out of AI is simply not practical.
The role of data centres has changed considerably in today’s economy. Instead of just serving web pages, advertising and video content, data centres are now recognising voices, detecting images in video streams and connecting users with information they need when they need it.
First, it was Singapore Management University (SMU). Now two other Singapore universities — Singapore University of Technology and Design (SUTD) and Nanyang Technological University (NTU) — have also deployed the NVIDIA DGX-1 deep learning supercomputer for their research projects on artificial intelligence (AI).
SUTD will use the DGX-1 at the SUTD Brain Lab to further research into machine reasoning and distributed learning. Under a memorandum of understanding signed earlier this month, NVIDIA and SUTD will also set up the NVIDIA-SUTD AI Lab to leverage the power of GPU-accelerated neural networks for researching new theories and algorithms for AI. The agreement also provides for internship opportunities to selected students of the lab.
“Computational power is a game changer for AI research, especially in the areas of big data analytics, robotics, machine reasoning and distributed intelligence. The DGX-1 will enable us to perform significantly more experiments in the same period of time, quickening the discovery of new theories and the design of new applications,” said Professors Shaowei Lin and Georgios Piliouras, Engineering Systems and Design, SUTD.
RIKEN, Japan’s largest comprehensive research institution, will have a new supercomputer for deep learning research in April. Built by Fujitsu using 24 NVIDIA DGX-1 AI systems, the new machine will accelerate the application of artificial intelligence (AI) to solve complex challenges in healthcare, manufacturing and public safety.
Conventional high performance computing architectures are proving too costly and inefficient for meeting the needs of AI researchers. That’s why research institutions such as RIKEN are looking for GPU-based solutions that reduce cost and power consumption while increasing performance. Each DGX-1 combines the power of eight NVIDIA Tesla P100 GPUs with an integrated software stack optimised for deep learning frameworks, delivering the performance of 250 conventional x86 servers.
“We believe that the NVIDIA DGX-1-based system will accelerate real-world implementation of the latest AI technologies technologies as well as research into next-generation AI algorithms. Fujitsu is leveraging its extensive experience in high-performance computing development and AI research to support R&D that utilises this system, contributing to the creation of a future in which AI is used to find solutions to a variety of social issues,” said Arimichi Kunisawa, Head of the Technical Computing Solution Unit at Fujitsu.
Tokyo Institute of Technology plans to create Japan’s fastest AI supercomputer, which is will deliver more than twice the performance of its predecessor to slide into the world’s top 10 fastest systems.
Called Tsubame 3.0, it will use Pascal-based NVIDIA P100 GPUs that are nearly three times as efficient as their predecessors, to reach an expected 12.2 petaflops of double precision performance.
Tsubame 3.0 will excel in AI computation with more than 47 PFLOPS of AI horsepower. When operated with Tsubame 2.5, it is expected to deliver 64.3 PFLOPS, making it Japan’s highest performing AI supercomputer.
Singapore is renowned as a food paradise. And with so many mouth-watering dishes to pick from, sometimes even locals have difficulty identifying a specific dish.
Singapore Management University (SMU) is working on a food artificial intelligence (AI) application that is calling on a supercomputer to help with recognising the local dishes to achieve smart food consumption and healthy lifestyle.
The project, developed as part of Singapore’s Smart Nation initiative, requires the analysis of a large number of food photos.