Like a b-plot from a particularly bad Bond movie, the Huawei security scandal has been a bit of a slow burner, with the roots of the saga reaching right back to January 2019 at CES, when AT&T announced themselves as the first major partner to ditch the Chinese technology giant. The next month, the director of the FBI warned against buying their phones and by May, Huawei and ZTE phones (ZTE being another company with potential ties to the Chinese government) were banned on US military bases. In the ensuing months, established partnerships began dropping like flies.
My summer usually starts with the International Super Computing (ISC) show in Frankfurt, and this year was no exception. Across the previous week in London at the AI Summit it rained every day, but thankfully high-performance computing’s influence on weather forecasting clearly shone through and in Frankfurt it was sunny and a warm 30⁰C.
Jan Witte, a leading quantitative analyst, writes for us about the predictive power of high-performance computing in finance and how the principles of machine learning apply to AI.
When you imagine what visualisation is in the world of HPC, most people think of astronomy, such as images of galaxies or black holes, or they think of weather, like analyses of tornadoes or hurricanes. Astronomical and atmospheric data is huge, requires HPC to analyse, and can make for amazing, sophisticated visualisations.
In an interesting Medium Article, Andrew Leonard wrote about how Amazon may be starting to compete with some of its Open Source software partners. Andrew’s article delved into the specifics of the case involving Elastic and their Elasticsearch open source software. Elastic has been happy to offer Elasticsearch in its Open Source form on the AWS platform, and many customers were happy to consume Elastic’s capabilities that way.
Consisting of the combination of biology, computer science, and mathematics, the science of bioinformatics has advanced rapidly in recent years. Thanks in part to HPC (high performance computing) and the expanding knowledge of and expertise in how to collect and analyse growing datasets, industries from agriculture to healthcare and more are experiencing the benefits of a bioinformatics revolution.
This article will provide examples of bioinformatics in industry and describe advancements in applications and compute power that have helped to raise the impact of bioinformatics to new heights that are changing the world.
How data is collected and analysed is changing at exponential rates. In industry — and I know this from talking and consulting with hundreds of companies — so much data is being collected that many companies are either confused with, or overwhelmed by, all of the ways to leverage and analyse their data.
At the high end of High-Performance Computing, the disruptive arrival of cloud computing has often been met with skepticism by those accustomed to making decisions upon hard evidence - a rare commodity in the nebulous cloud sector.
Psst, please only share this enterprise quantum computing insight with your HPC enthusiast friends. My boss would have a bird if he thought I was leaning 2+ years into the future with enterprise quantum computer hosting material!
In the early days of industrial high-performance computing (HPC), modeling and simulation (M&S) was, in many ways, the stalwart - the ideal domain area where companies could leverage advanced computing resources. Today, a confluence of traditional HPC M&S with artificial intelligence (AI) is occurring, changing the solution set significantly. Let's look at this in more detail...
On Monday of this week, the Bank of England governor Mark Carney promised to reinvent the Bank of England to make it fit for the “new economy” of the “Fourth Industrial Revolution", reflecting changes in how society, business and government operate.
Blink, and the silicon industry changes. I thought we knew what kinds of microprocessor we needed, and the silicon chip makers were just getting on with making them faster, cheaper and better. But now, I’m seeing reports of a whole bunch of so-called “AI chips”. So what’s happening, and why?
The birth of AI chips is a strange thing, because they are not coming from the usual places: cloud providers like Google and Alibaba, telecoms firm Huawei, and tiny start-ups like GraphCore. IBM is making AI chips, after it seemed to be scaling down its silicon work. And even Intel, when it got involved, bought a start-up called Nervana, and then teamed up with Facebook.