The deployment of face recognition systems has gained popularity in various application scenarios, such as border control initiatives like the European Entry-Exit System (EES) [Eu19]. In particular, the EES will be used as a central system for collecting and querying traveller data to the Schengen area at all border crossing points to facilitate the cooperation of visa and law enforcement authorities. The biometric performance of a system deployed in such sensitive environments must comply with high standards, such as those defined in the best practices for automated border control of the European Border and Coast Guard Agency (Frontex) [Fr15]. At the same time, the European General Data Protection Law complicates the processing of biometric data to avoid privacy leakages. Without an appropriate performance testing strategy, the risk of security lapses increases significantly and allows for the discriminatory treatment of travellers due to algorithmic or dataset bias. One solution to the lack of available test data includes the generation of synthetic data samples. However, in order to conduct reliable biometric performance tests, the synthetic samples must be as similar as possible to data collected in operational environments.

Research and development in hypersonics have progressed significantly in recent years, with various military and commercial applications being demonstrated increasingly. Public and private organizations in several countries have been investing in hypersonics, with the aim to overtake their competitors and secure/improve strategic advantage and deterrence. For these organizations, being able to identify emerging technologies in a timely and reliable manner is paramount. Recent advances in information technology have made it possible to analyze large amounts of data, extract hidden patterns, and provide decision-makers with new insights. In this study, we focus on scientific publications about hypersonics within the period of 2000-2020, and employ natural language processing and machine learning to characterize the research landscape by identifying 12 key latent research themes and analyzing their temporal evolution. Our publication similarity analysis revealed patterns that are indicative of cycles during two decades of research. The study offers a comprehensive analysis of the research field and the fact that the research themes are algorithmically extracted removes subjectivity from the exercise and enables consistent comparisons between topics and between time intervals.

The era of artificial intelligence chatbots has opened wide in Korea. On the 10th, the domestic media introduced an artificial intelligence robot that helps the elderly. The human care robot developed by the Intelligent Robotics Research Division of the Electronics and Telecommunications Research Institute (ETRI) is the main character. The Electronics and Telecommunications Research Institute (ETRI) said, "We have developed a robot artificial intelligence technology that understands the elderly, responds emotionally, and provides personalized services tailored to the situation." According to ETRI, the development of human care service robots requires data to recognize people from the robot's point of view and artificial intelligence technology necessary for deep learning.

The Department of Defense (DoD) has awarded BlueHalo Titan Defense a $24M contract to procure multiple Titan C-UAS systems. Titan, BlueHalo's AI/ML-powered RF-based Counter-Unmanned Aerial System (C-UAS) solution, is the DoD's recent selection as a Program of Record (POR) capability. Incorporation into the POR and this subsequent award serves as a milestone achievement for the Titan system after providing uncompromised C-UAS force protection to America's servicemen and women abroad in all Combatant Commands, as well as critical homeland defense in the United States for over five years. The undisclosed government customer will use Titan systems for pre-deployment activities, mobile security, fixed site protection, and dismounted operations while deployed. "Titan acts as a force multiplier for our troops," said Jonathan Moneymaker, BlueHalo's Chief Executive Officer.

Artificial intelligence (AI) is often touted as the cure-all for financial services firms' ability to deal with the looming data onslaught stemming from environmental, social & governance (ESG) regulation. Yet ESG also poses an existential threat to the financial services industry's use of AI The European Union's Sustainable Finance Disclosure Regulation has required asset management firms to begin collecting millions of data points from the companies in which they invest, and the forthcoming Corporate Sustainable Reporting Directive will only add to the volume of data points. Further, there is the data being collected under the Task Force on Climate-Related Financial Disclosures (TCFD) initiative and the International Sustainability Standards Board's plans to create a baseline for ESG reporting. Taken all together and it becomes clear that AI-enabled systems will be essential to firms' efforts to make sense of -- and profit from -- all these requirements. The carbon footprint from storing and processing data is enormous and growing, algorithms have already been shown to discriminate against certain groups in the population, and a lack of technology skills in both senior management ranks and the general workforce leave firms vulnerable to mistakes.

The Russian Embassy in Beijing has pulled down a controversial post on Weibo, praising China's top drone maker DJI for its products, which allegedly helped Kremlin in "modern warfare." The post went missing after DJI rebuffed the claim, stating its drones were not meant for military specifications. The embassy's post on Weibo cited a report from Russian state media Sputnik, based on a new book by Army General Yuri Baluyevsky, the former Chief of the General Staff of the Armed Forces of the Russian Federation, according to South China Morning Post. In his book, Baluyevsky said Chinese commercial drones have brought "a real revolution" to traditional artillery weapons. "When drones hover over a target area to guide the artillery, its pinpoint accuracy and efficiency are comparable to precision-guided missiles, according to the Russian embassy's Weibo post quoting Baluyevsky. "The Mavic quadcopter drone made by China's DJI has become a true symbol of modern warfare," he said. However, the post soon snowballed into a major controversy, as many netizens called out Russian Embassy for uploading something with "malicious intent." "What do you want by saying this?

Now Roscosmos, Russia's space agency, has shared a model of the country's future station, as it prepares to move out of the International Space Station. Nicknamed ROSS by state-controlled media, it would launch in two phases, starting with four modules and expanding to six with a service platform. The design would accommodate four people in rotating tours and reportedly offer better monitoring of Earth than Russia gets from the ISS today. State media claim the first phase will launch between 2025 and 2030, with Russia expected to leave the ISS in 2024. It announced its departure from the ISS in July in response to sanctions and other measures following Russia's invasion of Ukraine in February. Apple's M2-powered MacBook Air is $100 off at Amazon Tesla's Shanghai Gigafactory made its 1 millionth car Samsung has gone all-out on its next-generation monitor.

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Neuromorphic computing company GrAI Matter has $1 million in pre–orders for its GrAI VIP chip, the company told EE Times. The startup has engagement to date from companies across consumer Tier-1s, module makers (including ADLink, Framos, and ERM), U.S. and French government research, automotive Tier-1s and system integrators, white box suppliers, and distributors. As with previous generations of the company's Neuron Flow core, the company's approach for its GrAI VIP chip uses concepts from event–based sensing and sparsity to process image data efficiently. This means using a stateful neuron design (one that remembers the past) to process only information that has changed between one frame of a video and the next, which helps avoid processing unchanged parts of the frames over and over again. Combine this with a near–memory compute/dataflow architecture and the result is low–latency, low–power, real–time computer vision.

Philosopher William MacAskill coined the term "longtermism" to convey the idea that humans have a moral responsibility to protect the future of humanity, prevent it from going extinct and create a better future for many generations to come. He outlines this concept in his new book, What We Owe the Future. Philosopher William MacAskill coined the term "longtermism" to convey the idea that humans have a moral responsibility to protect the future of humanity, prevent it from going extinct and create a better future for many generations to come. He outlines this concept in his new book, What We Owe the Future. Let's say you're hiking, and you drop a piece of glass on the trail.