Research being conducted by the U.S. Army Combat Capabilities Development Command (DEVCOM) is focused on a new machine learning approach that could improve radar performance in congested environments. Researchers from DEVCOM, Army Research Laboratory, and Virginia Tech have developed an automatic way for radars to operate in congested and limited-spectrum environments created by commercial 4G LTE and future 5G communications systems. The researchers claim they examined how future Department of Defense radar systems will share the spectrum with commercial communications systems. The team used machine learning to learn the behavior of ever-changing interference in the spectrum and find clean spectrum to maximize the radar performance. Once clean spectrum is identified, waveforms can be modified to best fit into the spectrum.

Cardio-focused digital health company AliveCor landed FDA clearance for its new suite of interpretive ECG algorithms, dubbed the Kardia AI V2. This news comes just days after the company announced a $65 million Series E funding round. The new clearance will is able to capture sinus rhythm with premature ventricular contractions, sinus rhythm with supraventricular ectopy and a sinus rhythm with wide QRS. The algorithm works on AliveCor's KardiaMobile and KardiaMobile 6L devices, which even before this latest FDA clearance, have been able to take 30-second ECGs, and are hooked up to a corresponding app. According to the company's release, the algorithm will also reduce the number of unclassified readings, and has improved sensitivity and specificity on the company's normal and atrial fibrillation algorithms. Users will also have new visualization tools that let them see heart beat average, PVC identification and tachogram.

It's (mostly) true that Data Scientists do not care about infrastructure. Indeed, even though DevOps is a very interesting field, most of them are not exactly eager to start a VM, allocate the needed resources, configure the network, ssh into the machine, build a docker image and launch a Jupyter Notebook server. To cut to the chase, in this story, we create a ready to use, GPU accelerated Deep Learning environment, that has already TensorFlow and PyTorch installed. To do that we need to create the Dockerfile that describes the environment, build it and use it as the image of the Notebook server inside a Kubeflow instance. So, without further ado let's see the Dockerfile and walk through it step by step.

To think otherwise is to engage in what the physicist Max Tegmark calls "carbon chauvinism." In November, the Massachusetts Institute of Technology, where Dr. Tegmark is a professor, cashed a check from the National Science Foundation, and opened the metaphorical doors of the new Institute for Artificial Intelligence and Fundamental Interactions. The institute is one of seven set up by the foundation and the U.S. Department of Agriculture as part of a nationwide effort to galvanize work in artificial intelligence. Each receives $20 million over five years. The M.I.T.-based institute, directed by Jesse Thaler, a particle physicist, is the only one specifically devoted to physics.

Saudi Arabia is planning to invest more than 20 billion riyals ($5.3 billion) in artificial intelligence by 2030, Chairman of the Saudi Data and Artificial Intelligence Authority (SDAIA) Abdullah Bin Sharaf Al-Ghamdi announced yesterday. "We aim to train 20,000 specialists in artificial intelligence by 2030," Al-Ghamdi told reporters on the sidelines of the media centre program of the G20 summit, which is currently being held in the kingdom's capital city of Riyadh. The Saudi official pointed out that the kingdom was the third country in the world to use technology to combat the coronavirus, stressing that artificial intelligence was a: "Source of savings and an additional source of income worth investing." This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

FireEye Inc., a provider of managed security services augmented by machine learning algorithms, has acquired Respond Software, a provider of a platform that automates security incident investigations, for $186 million. Peter Bailey, executive vice president and COO for FireEye, said the acquisition of Respond Software adds eXtended Detection and Response (XDR) capabilities to better leverage the expertise of both the FireEye platform and security professionals who use it to manage security on behalf of customers. XDR is designed to make it easier to correlate events across endpoints and network traffic flows to identify cybersecurity threats more accurately. Respond Software will also be integrated into the portfolio of services that FireEye makes available via Mandiant Solutions, an arm of the company that focuses on threat intelligence and security posture assessments. The Respond Analyst XDR engine leverages cloud-based data science models that ingest data from a range of security technologies in real-time.

SpaceX has reused a Falcon 9 rocket for a record breaking seventh time during its most recent mission to put another 60 Starlink satellites into orbit. It comes as the Elon Musk-owned space launch firm is preparing for the first high altitude test flight of its mammoth Starship prototype spaceship - dubbed SN8. Launched from Cape Canaveral in Florida at 02:13 GMT this morning, the Falcon 9 flight was the seventh time that particular first stage booster had been used. This beat the previous record for a booster of six trips and helps Musk in his mission to bring down the cost of launching payloads from the Earth by reusing equipment. SpaceX was able to recover the booster from the Atlantic Ocean using a drone flight - which means it may be able to fly for an eighth time in the future.

EASA envisions three stages of AI's rollout in aviation: systems that will assist pilots (2022–2025); human-machine collaboration in flying an aircraft, such as a "virtual" first officer (2025–2030); and autonomous commercial air transport, or, more colloquially, pilotless airliners that fly themselves (2035 and beyond). EASA broadly defines AI as "any technology that appears to emulate the performance of a human." Ultimately, the widespread deployment of AI in aviation comes down to a matter of trust, EASA stated. "A European ethical approach to AI is central to strengthen citizens' trust in the digital development and aims at building a competitive advantage for European companies," according to the EASA roadmap. "Only if AI is developed and used in a way that respects widely shared ethical values can it be considered trustworthy. Therefore, there is a need for ethical guidelines that build on the existing regulatory framework. In June 2018, the [European] Commission set up a High-Level Expert Group on Artificial Intelligence (AI HLEG), the general objective of which was to support the implementation of the European strategy on AI. This includes the elaboration of recommendations on future-related policy development and on ethical, legal and societal issues related to AI, including socio-economic challenges. In April 2019, the AI HLEG proposed the following seven key requirements for trustworthy AI, which were published in its report on Ethics Guidelines on Trustworthy Artificial Intelligence."

Quantum computing--considered to be the next generation of high-performance computing--is a rapidly-changing field that receives equal parts attention in academia and in enterprise research labs. Honeywell, IBM, and Intel are independently developing their own implementations of quantum systems, as are startups such as D-Wave Systems. In late 2018, President Donald Trump signed the National Quantum Initiative Act that provides $1.2 billion for quantum research and development. TechRepublic's cheat sheet for quantum computing is positioned both as an easily digestible introduction to a new paradigm of computing, as well as a living guide that will be updated periodically to keep IT leaders informed on advances in the science and commercialization of quantum computing. SEE: The CIO's guide to quantum computing (ZDNet/TechRepublic special feature) Download the free PDF version (TechRepublic) SEE: All of TechRepublic's cheat sheets and smart person's guides Quantum computing is an emerging technology that attempts to overcome limitations inherent to traditional, transistor-based computers. Transistor-based computers rely on the encoding of data in binary bits--either 0 or 1. Quantum computers utilize qubits, which have different operational properties.

"In JAIC 1.0, we helped jumpstart AI in the DOD through Pathfinder projects we called mission initiatives," said Marine Corps Lt. Gen. Michael S. Groen, …