NVIDIA founder and CEO Jensen Huang will deliver the opening keynote address at the 10th annual GPU Technology Conference, being held March 17-21, in San Jose, Calif. “If you’re interested in AI, there’s no better place in the world to connect to a broad spectrum of developers and decision makers than GTC Silicon Valley,” said Greg Estes, vice president of developer programs at NVIDIA. “This event has grown tenfold in 10 years for a reason — it’s where experts from academia, Fortune 500 enterprises and the public sector share their latest work furthering AI and other advanced technologies.”
NVIDIA CEO Jensen Huang to Keynote World’s Premier AI Conference
February 4, 2019 by Leave a Comment
Choice Comes to HPC: A Year in Processor Development
January 27, 2019 by Leave a Comment
In this special guest feature, Robert Roe from Scientific Computing World writes that a whole new set of processor choices could shake up high performance computing. “While Intel is undoubtedly the king of the hill when it comes to HPC processors – with more than 90 per cent of the Top500 using Intel-based technologies – the advances made by other companies, such as AMD, the re-introduction of IBM and the maturing Arm ecosystem are all factors that mean that Intel faces stiffer competition than it has for a decade.”
Podcast: Weather Forecasting Goes Crowdsourcing, Q means Quantum
January 26, 2019 by Leave a Comment
In this episode of Radio Free HPC, Dan, Henry, and Shahin start with a spirited discussion about IBM’s recent announcement of a “crowd sourced weather prediction application.” Henry was dubious as to whether Big Blue could get access to the data they need in order to truly put out a valuable product. Dan had questions about the value of the crowd sourced data and how it could be scrubbed in order to be useful. Shahin was pretty favorable towards IBM’s plans and believes that they will solve the problems that Henry and Dan raised.
IBM rolls out Quantum Computer for Commercial Use
January 8, 2019 by Leave a Comment
Today IBM unveiled IBM Q System One, the world’s first integrated universal approximate quantum computing system designed for scientific and commercial use. “The IBM Q System One is a major step forward in the commercialization of quantum computing,” said Arvind Krishna, senior vice president of Hybrid Cloud and director of IBM Research. “This new system is critical in expanding quantum computing beyond the walls of the research lab as we work to develop practical quantum applications for business and science.”
IBM’s Plan to bring Machine Learning Capabilities to Data Scientists Everywhere
December 18, 2018 by Leave a Comment
Over at the IBM Blog, IBM Fellow Hillary Hunter writes that the company anticipates that the world’s volume of digital data will exceed 44 zettabytes, an astounding number. “IBM has worked to build the industry’s most complete data science platform. Integrated with NVIDIA GPUs and software designed specifically for AI and the most data-intensive workloads, IBM has infused AI into offerings that clients can access regardless of their deployment model. Today, we take the next step in that journey in announcing the next evolution of our collaboration with NVIDIA. We plan to leverage their new data science toolkit, RAPIDS, across our portfolio so that our clients can enhance the performance of machine learning and data analytics.”
IBM Publishes Compendium of Ai Research Papers
December 14, 2018 by Leave a Comment
Today IBM Research released a 2018 retrospective and blog essay by Dr. Dario Gil, COO of IBM Research, that provides a sneak-peek into the future of AI. “We have curated a collection of one hundred IBM Research AI papers we have published this year, authored by talented researchers and scientists from our twelve global Labs. These scientific advancements are core to our mission to invent the next set of fundamental AI technologies that will take us from today’s “narrow” AI to a new era of “broad” AI, where the potential of the technology can be unlocked across AI developers, enterprise adopters and end-users.”
NOAA Report: Effects of Persistent Arctic Warming Continue to Mount
December 11, 2018 by Leave a Comment
NOAA is out with their 2018 Arctic Report Card and the news is not good, folks. Issued annually since 2006, the Arctic Report Card is a timely and peer-reviewed source for clear, reliable and concise environmental information on the current state of different components of the Arctic environmental system relative to historical records. “The Report Card is intended for a wide audience, including scientists, teachers, students, decision-makers and the general public interested in the Arctic environment and science.”
OCF Deploys Largest IBM POWER9 Machine Learning Cluster in the UK
December 10, 2018 by Leave a Comment
With a new upgrade, the University of Birmingham is set to benefit from the largest IBM POWER9 machine learning cluster in the UK, delivering unprecedented performance for AI workloads. Working with OCF, the high-performance compute, the University will integrate a total of 11 IBM POWER9-based IBM Power Systems servers into its existing HPC infrastructure. “With our early deployment of the two IBM POWER9 servers we have seen what is possible. By scaling up, we can keep-pace with the escalating demand and offer the computational capacity and capability to attract leading researchers to the University.”
Deconstructing the Complexities of the Data Pipeline for Connected Cars
December 3, 2018 by Leave a Comment
A connected car can generate up to a gigabyte of data per day, and perhaps even more. Impressively, it is estimated that there are approximately 2 million connected cars on our roadways at this very moment. This means the storage demands can be up to 200 exabytes per day. IBM walks readers through the complexities of the data pipeline for connected cars, and how to address these challenges and storage questions.
Solving the Data Management Challenge of Autonomous Driving
November 26, 2018 by 1 Comment
The action of driving an automobile is destined to take a very different route in the coming years as autonomous cars become commonplace on our roadways. The notion of autonomous driving is both scary and exciting, pushing the boundaries of what we know. IBM takes a look at one of the most vexing technology challenges posed by autonomous vehicles: how to manage all the data used in artificial intelligence development.
