'AI FOR SPIES': U.S. intelligence agencies will soon be using a secretive generative artificial intelligence (AI) platform from Microsoft that will let America's spies safely use AI models in the process of analyzing sensitive data. Sheryl Crow speaks onstage during Grammys On The Hill on April 30, 2024 in Washington, D.C. (Leigh Vogel/Getty Images for The Recording Academy) 'ACT NOW': Sheryl Crow is calling on Congress to "act now" about artificial intelligence in the music industry and beyond. CHIP RESTRICTIONS: The U.S. on Tuesday revoked some of Intel and Qualcomm's licenses to export to China over national security concerns, a move that the Chinese government complained was unnecessary and excessive. Commerce Secretary Gina Raimondo attends an event in Bangkok, Thailand, March 13, 2024. DOWN LOW: The use of generative artificial intelligence tools by employees in the workplace is booming, but most of the workers who are utilizing the new technology have reservations about admitting it, new data indicates.

Fox News White House correspondent Jacqui Heinrich has the latest on the countries' alliance amid Chinese tensions on'Special Report.' Japan's defense chief Friday called for the bolstering of its anti-drone capability after a drone footage posted on Chinese social media showed a Japanese aircraft carrier docked at a restricted navy port west of Tokyo. Defense Minister Minoru Kihara called it a serious security threat. Kihara's acknowledgement of the vulnerability comes more than a month after a video filmed by a drone showed JS Izumo, one of two Japanese helicopter carriers, being retrofitted to carry stealth fighters to strengthen Japan's counter-strike capability in the face of China's assertive military actions in the Indo-Pacific. The footage, also showing plants, buildings and other facility at the Japan Maritime Self-Defense Force's Yokosuka naval base was posted on a Chinese social media site in March, prompting investigation by ministry officials.

No one can make that choice for you. But I can say with confidence born of experience that such choices can be more easily made if workers know what exactly the companies they work for are doing with militaries at home and abroad. And I also know this: those same companies themselves will never reveal this information unless they are forced to do so--or someone does it for them. For those who doubt that workers can make a difference in how trillion-dollar companies pursue their interests, I'm here to remind you that we've done it before. In 2017, I played a part in the successful #CancelMaven campaign that got Google to end its participation in Project Maven, a contract with the US Department of Defense to equip US military drones with artificial intelligence.

If the idea of building a train on the moon sounds like something from the pages of a sci-fi novel, you wouldn't be alone. But the moon train is actually just one of six'science fiction-like concepts' to receive new funding from NASA's Innovative Advanced Concepts program. Flexible Levitation on a Track, or FLOAT, plans to use levitating magnetic robots to transport up to 100 tonnes of materials on the lunar surface every day. According to the team behind the Scalextric-like project, this would provide a reliable and autonomous way of moving resources mined on the moon. Project leader Dr Ethan Schaler, a robotics engineer at NASA's Jet Propulsion Laboratory, says: 'A durable, long-life robotic transport system will be critical to the daily operations of a sustainable lunar base in the 2030's'.

Apple has apologized for its Crush! AdAge reports Apple said the video "missed the mark," and it has scrapped plans to run the commercial on TV. The video shows a series of musical instruments and other tools for human expression, including a guitar, drums, trumpet, amplifiers, record player, TV and much more being crushed to "All I Ever Need Is You" by Sonny and Cher. The crusher pulls up to reveal an iPad. Tonally, you could see how it could be misconstrued.

Footage of a Japanese naval destroyer that circulated on Chinese social media is likely genuine, Tokyo's Defense Ministry said Thursday, after initial speculation the video may have been generated by artificial intelligence. No obvious military activity can be seen in the clip, which appears to show the docked Izumo helicopter carrier. According to officials, footage "purportedly shot by a drone" was first uploaded to Chinese video-sharing platform Bilibili on March 26.

This paper critically analyses the "attention economy" within the framework of cognitive science and techno-political economics, as applied to both human and machine interactions. We explore how current business models, particularly in digital platform capitalism, harness user engagement by strategically shaping attentional patterns. These platforms utilize advanced AI and massive data analytics to enhance user engagement, creating a cycle of attention capture and data extraction. We review contemporary (neuro)cognitive theories of attention and platform engagement design techniques and criticize classical cognitivist and behaviourist theories for their inadequacies in addressing the potential harms of such engagement on user autonomy and wellbeing. 4E approaches to cognitive science, instead, emphasizing the embodied, extended, enactive, and ecological aspects of cognition, offer us an intrinsic normative standpoint and a more integrated understanding of how attentional patterns are actively constituted by adaptive digital environments. By examining the precarious nature of habit formation in digital contexts, we reveal the techno-economic underpinnings that threaten personal autonomy by disaggregating habits away from the individual, into an AI managed collection of behavioural patterns. Our current predicament suggests the necessity of a paradigm shift towards an ecology of attention. This shift aims to foster environments that respect and preserve human cognitive and social capacities, countering the exploitative tendencies of cognitive capitalism.

Model attribution is a popular tool to explain the rationales behind model predictions. However, recent work suggests that the attributions are vulnerable to minute perturbations, which can be added to input samples to fool the attributions while maintaining the prediction outputs. Although empirical studies have shown positive performance via adversarial training, an effective certified defense method is eminently needed to understand the robustness of attributions. In this work, we propose to use uniform smoothing technique that augments the vanilla attributions by noises uniformly sampled from a certain space. It is proved that, for all perturbations within the attack region, the cosine similarity between uniformly smoothed attribution of perturbed sample and the unperturbed sample is guaranteed to be lower bounded. We also derive alternative formulations of the certification that is equivalent to the original one and provides the maximum size of perturbation or the minimum smoothing radius such that the attribution can not be perturbed. We evaluate the proposed method on three datasets and show that the proposed method can effectively protect the attributions from attacks, regardless of the architecture of networks, training schemes and the size of the datasets.

In the realm of time series analysis, accurately measuring similarity is crucial for applications such as forecasting, anomaly detection, and clustering. However, existing metrics often fail to capture the complex, multidimensional nature of time series data, limiting their effectiveness and application. This paper introduces the Structured Similarity Index Measure for Time Series (TS3IM), a novel approach inspired by the success of the Structural Similarity Index Measure (SSIM) in image analysis, tailored to address these limitations by assessing structural similarity in time series. TS3IM evaluates multiple dimensions of similarity-trend, variability, and structural integrity-offering a more nuanced and comprehensive measure. This metric represents a significant leap forward, providing a robust tool for analyzing temporal data and offering more accurate and comprehensive sequence analysis and decision support in fields such as monitoring power consumption, analyzing traffic flow, and adversarial recognition. Our extensive experimental results also show that compared with traditional methods that rely heavily on computational correlation, TS3IM is 1.87 times more similar to Dynamic Time Warping (DTW) in evaluation results and improves by more than 50% in adversarial recognition.

Digital technologies have positively transformed society, but they have also led to undesirable consequences not anticipated at the time of design or development. We posit that insights into past undesirable consequences can help researchers and practitioners gain awareness and anticipate potential adverse effects. To test this assumption, we introduce BLIP, a system that extracts real-world undesirable consequences of technology from online articles, summarizes and categorizes them, and presents them in an interactive, web-based interface. In two user studies with 15 researchers in various computer science disciplines, we found that BLIP substantially increased the number and diversity of undesirable consequences they could list in comparison to relying on prior knowledge or searching online. Moreover, BLIP helped them identify undesirable consequences relevant to their ongoing projects, made them aware of undesirable consequences they "had never considered," and inspired them to reflect on their own experiences with technology.