With plans to send humans to the Moon and further, the supply of resources like oxygen, water, fuel, etc., can be satiated by performing In-Situ Resource Utilization (ISRU), where resources from the extra-terrestrial body are extracted to be utilized. These ISRU missions can be carried out by a Multi-Robot System (MRS). In this research, a high-level auction- based Multi-Robot Task Allocation (MRTA) system is developed for coordinating tasks amongst multiple robots with distinct capabilities. A hierarchical decentralized coordination architecture is implemented in this research to allocate the tasks amongst the robots for achieving intentional cooperation in the Multi-Robot System (MRS). 3 different policies are formulated that govern how robots should act in the multiple auction situations of the auction-based task allocation system proposed in this research, and their performance is evaluated in a 2D simulation called pyrobosim using ROS2. The decentralized coordination architecture and the auction-based MRTA make the MRS highly scalable, reliable, flexible, and robust.

We conducted an in-person ethnography in India and the US to investigate how young people (18-24) trusted online content, with a focus on generative AI (GenAI). We had four key findings about how young people use GenAI and determine what to trust online. First, when online, we found participants fluidly shifted between mindsets and emotional states, which we term "information modes." Second, these information modes shaped how and why participants trust GenAI and how they applied literacy skills. In the modes where they spent most of their time, they eschewed literacy skills. Third, with the advent of GenAI, participants imported existing trust heuristics from familiar online contexts into their interactions with GenAI. Fourth, although study participants had reservations about GenAI, they saw it as a requisite tool to adopt to keep up with the times. Participants valued efficiency above all else, and used GenAI to further their goals quickly at the expense of accuracy. Our findings suggest that young people spend the majority of their time online not concerned with truth because they are seeking only to pass the time. As a result, literacy interventions should be designed to intervene at the right time, to match users' distinct information modes, and to work with their existing fact-checking practices.

Operator learning is a variant of machine learning that is designed to approximate maps between function spaces from data. The Fourier Neural Operator (FNO) is a common model architecture used for operator learning. The FNO combines pointwise linear and nonlinear operations in physical space with pointwise linear operations in Fourier space, leading to a parameterized map acting between function spaces. Although FNOs formally involve convolutions of functions on a continuum, in practice the computations are performed on a discretized grid, allowing efficient implementation via the FFT. In this paper, the aliasing error that results from such a discretization is quantified and algebraic rates of convergence in terms of the grid resolution are obtained as a function of the regularity of the input. Numerical experiments that validate the theory and describe model stability are performed.

Scour around bridge piers is a critical challenge for infrastructures around the world. In the absence of analytical models and due to the complexity of the scour process, it is difficult for current empirical methods to achieve accurate predictions. In this paper, we exploit the power of deep learning algorithms to forecast the scour depth variations around bridge piers based on historical sensor monitoring data, including riverbed elevation, flow elevation, and flow velocity. We investigated the performance of Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) models for real-time scour forecasting using data collected from bridges in Alaska and Oregon from 2006 to 2021. The LSTM models achieved mean absolute error (MAE) ranging from 0.1m to 0.5m for predicting bed level variations a week in advance, showing a reasonable performance. The Fully Convolutional Network (FCN) variant of CNN outperformed other CNN configurations, showing a comparable performance to LSTMs with significantly lower computational costs. We explored various innovative random-search heuristics for hyperparameter tuning and model optimisation which resulted in reduced computational cost compared to grid-search method. The impact of different combinations of sensor features on scour prediction showed the significance of the historical time series of scour for predicting upcoming events. Overall, this study provides a greater understanding of the potential of Deep Learning algorithms for real-time scour prediction and early warning for bridges with distinct geology, geomorphology and flow characteristics.

The United States Department of Defense has acknowledged that a drone strike in Syria, initially said to have successfully targeted an al-Qaeda leader, actually killed a farmer. The Pentagon stated on Thursday that the drone strike on May 3, 2023, killed a 56-year-old shepherd named Lutfi Hasan Masto, whom they initially misidentified as a senior member of al-Qaeda. US Central Command, which oversees military activities in the Middle East, wrote that it "acknowledges and regrets the civilian harm that resulted from the airstrike". A year ago a US strike in Syria killed a'senior Al-Qaeda leader' The US military has now officially accepted it was a mistake, blaming'confirmation bias'https://t.co/WG9Mf0Rdq2 The killing of Masto is the latest incident to raise questions about the impact of US drone warfare on civilians, who often pay the price for botched strikes.

Apple released its earnings report on Thursday, revealing a drop in overall revenue fueled by slackening iPhone sales. Earnings exceeded market expectations, however, and Apple's shares rose in after-hours trading. Tim Cook, Apple's chief executive, said in a statement released before the call that "Apple is reporting revenue of 90.8bn for the March quarter, including an all-time revenue record in services". The iPhone maker reported revenue of 90.8bn, down 4% year-over-year, but surpassing anticipated earnings of 90.1bn. It declared 0.25 in cash dividend for each share, an increase of 4%.

Philosopher Nick Bostrom is surprisingly cheerful for someone who has spent so much time worrying about ways that humanity might destroy itself. In photographs he often looks deadly serious, perhaps appropriately haunted by the existential dangers roaming around his brain. When we talk over Zoom, he looks relaxed and is smiling. Bostrom has made it his life's work to ponder far-off technological advancement and existential risks to humanity. With the publication of his last book, Superintelligence: Paths, Dangers, Strategies, in 2014, Bostrom drew public attention to what was then a fringe idea--that AI would advance to a point where it might turn against and delete humanity. To many in and outside of AI research the idea seemed fanciful, but influential figures including Elon Musk cited Bostrom's writing.

A State Department official is pushing Thursday for China and Russia to declare that only humans – and not artificial intelligence – will make decisions on deploying nuclear weapons. Paul Dean, an official in the State Department's Bureau of Arms Control, Deterrence, and Stability, said during a press briefing that the U.S. has already made "a very clear and strong commitment that in cases of nuclear employment, that decision would only be made by a human being. "We would never defer a decision on nuclear employment to AI. We strongly stand by that statement and we've made it publicly with our colleagues in the UK and France," he continued. "We would welcome a similar statement by China and the Russian Federation," Dean added, noting that "we think it's an extremely important norm of responsible behavior." Chinese President Xi Jinping and Russian President Vladimir Putin shake hands in Moscow, Russia, in March 2023. The State Department has said that Secretary of State Blinken and Chinese Foreign Minister Wang Yi spoke about "artificial intelligence risks and safety" during a meeting last Friday in Beijing. "I do think that there is a real opportunity right now as countries increasingly turn to artificial intelligence to establish what the rules of responsible and stabilizing behavior will look like.

Emails from the Department of Justice's antitrust case against Google revealed how Microsoft executives were alarmed by and even envious of Google's AI lead. In an email thread, CTO Kevin Scott wrote he was "very, very worried" about Google's rapidly growing AI capabilities. He said he initially dismissed the company's "game-playing stunts," likely referring to Google's AlphaGo models. The emails reference Gmail's autocomplete features, which execs called "scary good." Microsoft struggled to copy Google's BERT-large, an AI model that deciphers the meaning and context of words in a sentence.

After the spectacular fall of FTX CEO Sam Bankman-Fried, you might have expected the embattled cryptocurrency sector, and its sophisticated lobbying operations, to have ground to a halt. But if anything, both are back with a vengeance--and the regulatory post-SBF crackdown that followed has spurred the sector to potentially become a major political force in 2024. A new, unholy alliance has emerged on Capitol Hill, and it's hoping not just to recraft governmental policy around digital funny money but to push its antiregulatory agenda across a whole host of elections. To do so, the crypto industry is teaming up with the people behind the latest megahyped, bubblicious tech trend: the artificial intelligence boom. You may already have noticed crypto and tech money swishing around in the 2024 primaries.