Consider the last two years: The company rode Call of Duty's potency to new heights following the release of "Call of Duty Mobile" in 2019 -- downloaded by over 650 million users globally, according to Activision -- and the free-to-play battle royale "Warzone" in the spring of 2020. But by last winter the company was dogged by fallout from a sexual discrimination and harassment lawsuit filed that summer by the state of California against Activision Blizzard, the parent company of Activision and the studios that develop Call of Duty. The franchise's annual installment, the World War II-based "Vanguard," also fell short of sales expectations and stock prices plunged from a high point of $103 per share in February 2021 to $56.94 on Dec. 1 that same year. The company announced the following month it would be acquired by Microsoft.

Melinda Snodgrass is the novelist and screenwriter best known for her classic Star Trek: The Next Generation script "The Measure of a Man." Her latest novel, Lucifer's War, pits an unlikely band of heroes against a horde of Lovecraftian monsters that have been spreading fear and ignorance throughout human history. "It's unbelievable now, the kind of nonsense people are accepting, that's being pushed on them by social media," Snodgrass says in Episode 529 of the Geek's Guide to the Galaxy podcast. "I really wanted to make a stand for science and rationality, as opposed to magic and superstition." The book is set in Snodgrass' home state of New Mexico, a place where science and superstition clash in a particularly striking way. "It's a very weird place, where you have Los Alamos laboratory, Sandia laboratories, high-tech, high-energy centers," Snodgrass says, "Some of the finest scientific minds in the world come here to lecture and study and commune with each other, and then on the other side you have people who will balance your aura and sell you a crystal to deal with your cancer."

Australian surf lifesavers are increasingly using drones to spot sharks at the beach before they get too close to swimmers. But just how reliable are they? Discerning whether that dark splodge in the water is a shark or just, say, seaweed isn't always straightforward and, in reasonable conditions, drone pilots generally make the right call only 60% of the time. While this has implications for public safety, it can also lead to unnecessary beach closures and public alarm. Engineers are trying to boost the accuracy of these shark-spotting drones with artificial intelligence (AI).

Will artificial intelligence soon outsmart human beings, and if so, what will become of us? The great computer scientist Alan Turing argued in the early 1950s that we were probably going to see our intellectual capacities surpassed by computers sooner or later. He thought it was probable "that at the end of the [20th] century it will be possible to program a machine to answer questions in such a way that it will be extremely difficult to guess whether the answers are being given by a man or by the machine." "Machines can be constructed," he said, "which will simulate the behavior of the human mind very closely" because "if it is accepted that real brains, as found in animals, and particularly in men, are a sort of machine it will follow that our digital computer, suitably programmed, will behave like a brain." Other early AI pioneers anticipated even more rapid developments. Herbert Simon thought in 1965 that "machines will be capable, within twenty years, of doing any work a man can do," and Marvin Minsky said two years later that it would only take a "generation" to "solve" the problem of artificial intelligence. Things have taken a bit longer than that, and theorists in the field of AI have become somewhat notorious for making promises that we might call "Friedmanesque." But there are still those who think we have reason to fear that AI will surpass human intelligence in the near future, and, in fact, that an AI-driven cataclysm may be coming. Elon Musk--who, it should be noted, does not have a good track record when it comes to predicting the future--has warned that "robots will be able to do everything better than us," and "if AI has a goal and humanity just happens to be in the way, it will destroy humanity as a matter of course without even thinking about it." He is not alone in spinning apocalyptic stories about a coming "superintelligence" that could literally exterminate the entire human race.

As part of Department of Transportation's plans to modernize the U.S.'s highway infrastructure, the agency issued a new contract opportunity seeking artificial intelligence and data analytics-based solutions. A program under the agency's Federal Highway Administration called for proposals featuring artificial intelligence technology to improve the current national highway design system. The technology developed within this contract will impact the planning, construction and maintenance of the nation's highways. A spokesperson for the FHWA informed Nextgov the projects' goal is to successfully transform highway transportation with AI technology, and that, following the projects' individual outcomes, officials will decide how to implement it across the transportation sector. "With the growing number of maturing and commercial applications, there still is a need for early state research to support emerging advances in AI that can solve even more complex questions in highway transportation," the RFI notes.

Reply is one of the leading full-service providers for Digital Experience Services (DXS) in the new study "The Market for Digital Experience Services in Germany 2022" released by the market research company Lünendonk. The assessment includes the revenues generated in 2021 on three main categories – i.e., Digital Consulting Services, Digital Agency Services and Digital Technology Services – as well as the evaluation received by providers and customers of Digital Experience Services. According to the Lünendonk study, digital experience services are gaining increasing importance. In fact, the revenue in the digital experience services segment has considerably expanded in the last two years and is forecast to grow by 17.8 percent in 2023. Next-gen AI-On-Demand Platform: European Commission Pumps in $9.15 Million to Develop Next-gen AI-On-Demand Platform The user companies interviewed by Lünendonk confirmed that the investments in digital experience services of the past years are showing beneficial results and many are planning to invest further on cybersecurity, artificial intelligence (AI), cloud native and the development of data platforms. Even the metaverse, for which not all companies have already identified use cases for, it is also gaining higher consideration.

SparkCognition Government Systems (SGS) is the first full-spectrum artificial intelligence (AI) company devoted entirely to the government and national defense mission. By developing and operationalizing next-generation AI-powered solutions, SGS enables government organizations to meet the needs of their most pressing national security missions. Using technologies built in the United States, SGS advances government operations by analyzing complex data to inform and accelerate intelligent decisions, applying predictive and prescriptive analytics to improve logistics and readiness, deploying autonomy technology for unmanned systems, using natural language processing for large scale processing of unstructured data, and more. The DevSecOps Engineer is responsible for maintaining the security, technology, wellness, and integrity of SGS. The ideal candidate will assist SGS' engineering team in building a comprehensive software'factory' in addition to instituting a fully integrated and secure systems architecture available to SGS and its clients.

Argonne researchers have created an automatic technique that can fill in gaps in X-ray data. Putting together a jigsaw puzzle is a great activity for a rainy Sunday afternoon. But the somewhat more difficult process of quickly assembling 3D scientific jigsaw puzzles--atomic structures of different materials--has recently gotten a lot easier, thanks to new research that pairs high-powered X-ray beams with advanced computing methodologies. Researchers at the U.S. Department of Energy's (DOE) Argonne National Laboratory have developed a new technique that accelerates the solving of material structures from patterns uncovered in X-ray experiments. The technique allows researchers to study certain properties, such as corrosion or battery charging and discharging, in real time.

Prior work on ideology prediction has largely focused on single modalities, i.e., text or images. In this work, we introduce the task of multimodal ideology prediction, where a model predicts binary or five-point scale ideological leanings, given a text-image pair with political content. We first collect five new large-scale datasets with English documents and images along with their ideological leanings, covering news articles from a wide range of US mainstream media and social media posts from Reddit and Twitter. We conduct in-depth analyses of news articles and reveal differences in image content and usage across the political spectrum. Furthermore, we perform extensive experiments and ablation studies, demonstrating the effectiveness of targeted pretraining objectives on different model components. Our best-performing model, a late-fusion architecture pretrained with a triplet objective over multimodal content, outperforms the state-of-the-art text-only model by almost 4% and a strong multimodal baseline with no pretraining by over 3%.

The goal of the Mars Sample Return campaign is to collect soil samples from the surface of Mars and return them to Earth for further study. The samples will be acquired and stored in metal tubes by the Perseverance rover and deposited on the Martian surface. As part of this campaign, it is expected that the Sample Fetch Rover will be in charge of localizing and gathering up to 35 sample tubes over 150 Martian sols. Autonomous capabilities are critical for the success of the overall campaign and for the Sample Fetch Rover in particular. This work proposes a novel system architecture for the autonomous detection and pose estimation of the sample tubes. For the detection stage, a Deep Neural Network and transfer learning from a synthetic dataset are proposed. The dataset is created from photorealistic 3D simulations of Martian scenarios. Additionally, the sample tubes poses are estimated using Computer Vision techniques such as contour detection and line fitting on the detected area. Finally, laboratory tests of the Sample Localization procedure are performed using the ExoMars Testing Rover on a Mars-like testbed. These tests validate the proposed approach in different hardware architectures, providing promising results related to the sample detection and pose estimation.