A year ago, NOV Inc. was in the middle of evaluating a new security product to help with securing its globally distributed workforce, spread across more than 60 countries. The oilfield equipment maker was considering deploying an extended detection and response (XDR) solution from SentinelOne -- and as part of the evaluation, NOV deployed the XDR platform across a company it had recently acquired. "Immediately" after deployment, SentinelOne's Singularity XDR detected and halted a cyberattack in progress against the acquired company, said NOV chief information security officer John McLeod -- and then remediated the attack, as well. "This was all done during the pandemic lockdown, in a country on the other side of the globe, where we didn't speak the same language," McLeod said in an email. Perhaps unsurprisingly, NOV ended up becoming a customer.

The teams most impacted by these decisions are Gambit Esports and Virtus.pro. Gambit is owned by the telecommunications company Mobile TeleSystems, whose largest shareholder is a company headed by the Russian billionaire Vladimir Yevtushenkov. On Feb. 24, Yevtushenkov was present at a Kremlin meeting between Putin and representatives of Russian big business. Virtus.pro shares a connection with the Russian insurance firm SOGAZ, which fell under European Union sanctions following the invasion.

NASA has just announced the projects that will be getting money from its NASA Innovative Advanced Concepts (NIAC) programme, which aims to support ideas for game-changing mission designs and never-before-seen space exploration tech. Here we look at five of the concepts and how they will be used. Astronauts venturing to the moon or Mars in the future are likely to face a barrage of hazardous space radiation during their trips, including high-energy particles and nuclei known as cosmic rays. To protect crews, one NIAC study is exploring the idea of what the project's lead, Elena D'Onghia at the University of Wisconsin-Madison, calls a "deployable magnetic shield device". The CREW HaT system would consist of a ring of electrical coils positioned on arms roughly 5 metres from the spacecraft's main body.

The European AI Act, a proposed European law on artificial intelligence is the first law on AI by a major regulator. It lays down harmonised rules for the EU. The European Commission unveiled this new proposal for an EU regulatory framework in April 2021. "As expected, the debate around this legislation has already started. On the positive side, this regulation may become the global standard, in the same way GDPR has become. It may also make AI systems more trustworthy and offer extra protections to the public. On the other side, it may stifle innovation, add more costs and red tape, which may hinder start-ups from entering the market. We will hear more on this around the world before it becomes law, currently expected in 2023. With the rise of Industry 4.0 the approach to producing goods and services has triggered a trend in the current manufacturing industry that focuses on automation of processes and data exchange. The approach integrates the Internet of Things (IoT), cyber-enhanced systems and cloud computing and relies heavily on the timely availability of data about every aspect and stage of the production/creation process. The IoT is not something you will experience as such itself. What you will see is that more and more objects become connected. If you are manufacturing products, you will be negotiating with providers of connectivity and in the very near future with any tiny part of the artefact that you are intending to build. It becomes very important to know the origin of these artefacts. We are in the middle of a manufacturing revolution, a five-year cycle as we can see from what happened to the products itself in the supply chain. In the 2013 Introduction to the Springer book Enabling Things to Talk Prof. Dr. Michael ten Hompel, Managing Director at Fraunhofer-Institut for "Materialfluss und Logistik", describes the consequences for something as "solid" as logistics: "The logical consequence of the Internet of Things is not just a new philosophy of how we can control our production and logistics.

AI is a buzzword that gets thrown around a lot in cybersecurity -- often, it seems, to obscure and impress, rather than to clarify how products and services work. This is unfortunate, because beyond the hype, artificial intelligence's role in cybersecurity is becoming increasingly indispensable. While AI won't solve all problems, it provides a growing toolbox for accelerating security workflows and better detecting threats. In fact, there are several ways in which AI is already revolutionizing cybersecurity. Pattern Matching and Threat Detection Until the past half decade or so, most cyber-threat detection was performed using small, handwritten pattern-matching programs (called signatures, rules, or indicators of compromise).

On behalf of the Metropolis of Reno and the Reno Hearth Division (RFD), Iris Automation has been granted approval from the Federal Aviation Administration (FAA) to fly a small drone autonomously past the pilot's visible line of sight (BVLOS), with out the help of any observers or further ground-based detection gear. Testing will start over unpopulated areas earlier than shifting to city areas. The BVLOS waiver covers a rural, unpopulated space south of Reno and was submitted by Iris Automation for using its Casia X detect and keep away from resolution. "That is an thrilling venture, working with the BEYOND program and the most recent applied sciences to open the skies each for our group and the broader public," mentioned Reno Mayor Hillary Schieve. "It's a novel teaming of private and non-private pursuits to attain breakthrough operations for a variety of cost-effective, public-facing companies. Autonomous flying will profit each member of our group and drive long run financial advantages together with job creation, value financial savings and extra environment friendly companies. We intend this to be our first of many waivers as a part of this collaboration. We're proud to be main the way in which on this unbelievable area--and with a neighborhood BEYOND participant too--and excited to see our companions shifting to this subsequent step within the course of."

The world, as we know it, is rapidly digitising through breakthrough advancements in artificial intelligence (AI). Data sciences and AI are indeed the new reality and no longer a work of fiction as perceived in sci-fi movies. The increasing prevalence of data is driving businesses to develop and use AI to remain competitive in the market. Recent developments in machine learning have in fact elevated algorithms to a new level, enabling machines to analyse, act and learn with a human-like level of intelligence. This characteristic of automated systems has drawn interest from global antitrust regulators as it enables businesses to achieve collusive outcomes without requiring an agreement in the traditional antitrust sense.

LONDON (AP) — Risky uses of artificial intelligence that threaten people’s safety or rights such as live facial scanning should be banned or tightly controlled, European Union officials said Wednesday as they outlined an ambitious package of proposed regulations to rein in the rapidly expanding technology. The draft regulations from the EU's executive commission include rules for applications deemed high risk such as AI systems to filter out school, job or loan applicants. They would also ban artificial intelligence outright in a few cases considered too risky, such as government “social scoring” systems that judge people based on their behavior. The proposals are the 27-nation bloc’s latest move to maintain its role as the world’s standard-bearer for technology regulation, as it tries to keep up with the world's two big tech superpowers, the U.S. and China. EU officials say they are taking a four-level “risk-based approach” that seeks to balance important rights such as privacy against the need to encourage innovation.

Machine learning classifiers with high test accuracy often perform poorly under adversarial attacks. It is commonly believed that adversarial training alleviates this issue. In this paper, we demonstrate that, surprisingly, the opposite may be true -- Even though adversarial training helps when enough data is available, it may hurt robust generalization in the small sample size regime. We first prove this phenomenon for a high-dimensional linear classification setting with noiseless observations. Our proof provides explanatory insights that may also transfer to feature learning models. Further, we observe in experiments on standard image datasets that the same behavior occurs for perceptible attacks that effectively reduce class information such as mask attacks and object corruptions.

Geoffrey Hinton is a legendary computer scientist . . . Naturally, people paid attention when Hinton declared in 2016, "We should stop training radiologists now, it's just completely obvious within five years deep learning is going to do better than radiologists." The US Food and Drug Administration (FDA) approved the first AI algorithm for medical imaging that year and there are now more than 80 approved algorithms in the US and a similar number in Europe. Yet, the number of radiologists working in the US has gone up, not down, increasing by about 7% between 2015 and 2019. Indeed, there is now a shortage of radiologists that is predicted to increase over the next decade.