The Boeing-owned test Stingray, MQ-25 T1, passed fuel to an E-2D airborne early warning and control (AEW&C) receiver aircraft flown by the US Navy’s (USN’s) Air Test and Evaluation Squadron VX-20 during the event the day prior to the announcement.
“During a test flight from MidAmerica St Louis Airport on 18 August, pilots from VX-20 conducted a successful wake survey behind MQ-25 T1 to ensure performance and stability before making contact with T1’s aerial refuelling drogue. The E-2D received fuel from T1’s aerial refuelling store during the flight,” Boeing said.
This first contact for the Stingray unmanned tanker with an Advanced Hawkeye receiver aircraft came nearly three months after the first aerial refuelling test was performed on 4 June with a Boeing F/A-18F Super Hornet receiver. Both the Advanced Hawkeye and Super Hornet flights were conducted at operationally relevant speeds and altitudes, with both receiver aircraft performing manoeuvres in close proximity to the Stingray.
Technology Breakthroughs Enable Training of 120 Trillion Parameters on Single CS-2, Clusters of up to 163 Million Cores with Near Linear Scaling, Push Button Cluster Configuration, Unprecedented Sparsity Acceleration.
Cerebras Systems is a team of pioneering computer architects, computer scientists, deep learning researchers, and engineers of all types. We have come together to build a new class of computer to accelerate artificial intelligence work by three orders of magnitude beyond the current state of the art. The CS-2 is the fastest AI computer in existence. It contains a collection of industry firsts, including the Cerebras Wafer Scale Engine (WSE-2). The WSE-2 is the largest chip ever built. It contains 2.6 trillion transistors and covers more than 46,225 square millimeters of silicon. The largest graphics processor on the market has 54 billion transistors and covers 815 square millimeters. In artificial intelligence work, large chips process information more quickly producing answers in less time. As a result, neural networks that in the past took months to train, can now train in minutes on the Cerebras CS-2 powered by the WSE-2.
IBM has announced its new chip, Telum – a new CPU chip that will allow IBM clients to leverage deep learning inference at scale. The new chip features a centralised design, which allows clients to leverage the full power of the AI processor for AI-specific workloads, making it ideal for financial services workloads like fraud detection, loan processing, clearing and settlement of trades, anti-money laundering, and risk analysis.
A Telum-based system is planned for the first half of 2022. “Our goal is to continue improving AI hardware compute efficiency by 2.5 times every year for a decade, achieving 1,000 times better performance by 2029,” said IBM in a press release.
The chip contains eight processor cores, running with more than 5GHz clock frequency, optimised for the demands of enterprise-class workloads. The completely redesigned cache and chip-interconnection infrastructure provide 32MB cache per core. The chip also contains 22 billion transistors and 19 miles of wire on 17 metal layers.
From voice-controlled personal assistants to smart robots on factory floors, Artificial Intelligence is having a profound effect on our lives. No surprise then that countries all over the world are trying to stay ahead of the curve. But when it comes to investment, who’s putting their money where their mouth is? Looking at private funding, the United States leads the way — with well over 23 billion dollars going into the sector last year. Coming in second is China, with almost 10 billion dollars. That said, Chinese state investment is particularly significant. And the European Union falls far behind, with investment of just over 2 billion dollars. So why is the EU lagging? And does Germany — its largest economy — have any plans to play catch-up? An example of AI in action can be found at a Rolls Royce control room just outside Berlin. Robots destroy jobs and artificial intelligence will soon make us all superfluous. We’ve all seen headlines like that. But the reality of the situation looks a little different. Artificial intelligence is nothing more than a system that processes large amounts of data and makes predictions about the future based on that data. Engine manufacturer Rolls Royce has been a fan of AI for a long time. Even in emergencies, it keeps its cool. In the control room at Rolls Royce just south of Berlin, safety engineers monitor more than 9,000 airplane engines worldwide. Long before the owners of the commercial jets would even notice a defect, the systems here sound the alarm. Artificial intelligence at work. The systems are fed massive amounts of data. Then the owners of the aircraft are informed. The plane can then be taken in for maintenance long before the problem becomes expensive or life-threatening. In the adjacent building, engines are assembled. Many parts are custom-made, previously developed by the design engineers, who also use artificial intelligence. For example, how would it affect the engine if certain components are changed? AI helps to find the best method. The Center for Artificial Intelligence opened at the Dahlewitz site near Berlin in 2019. People here aren’t afraid that artificial intelligence will take their jobs. In fact, the mechanics will probably have to install even more sensors and cables in the future. After all, in about five years’ time, the plan is for the aircraft to fly here with hybrid drive systems — based on sustainable fuel and electricity.
A new suite of algorithms by Google Brain can now design computer chips —those specifically tailored for running AI software —that vastly outperform those designed by human experts. And the system works in just a few hours, dramatically slashing the weeks-or months-long process that normally gums up digital innovation.
At the heart of these robotic chip designers is a type of machine learning called deep reinforcement learning. This family of algorithms, loosely based on the human brain’s workings, has triumphed over its biological neural inspirations in games such as Chess, Go, and nearly the entire Atari catalog.
