We keep hearing about how AI is going to steal women's jobs, proliferate racial bias, make the rich richer and the poor poorer. And if we focus solely on that fear, it very well might. As the founder of Girls Who Code, I know as well as anyone the risks technology poses to the most vulnerable among us. But I've also seen how, when we're distracted by doomsday, we miss incredible opportunities to help those same communities. That's why I believe the next generation of AI will close inequality gaps--if we stop fixating on how it will widen them.

In the early 1950s, a huge hole was dug into the Cumbrian coast and lined with concrete. Roughly the length of three Olympic swimming pools and known as B30, it was built to hold skip loads of spent nuclear fuel. Those highly radioactive rods came from the 26 Magnox nuclear reactors that helped keep Britain's lights on between 1956 and 2015. When B30 was first put to work, it was designed to keep the fuel rods submerged for only three months before reprocessing work was carried out. But when 1970s miners' strikes shut down coal power stations and forced greater reliance on nuclear plants, more spent fuel than could be quickly reprocessed was generated.

A day earlier than teased, Rockstar has released the first official trailer of Grand Theft Auto VI, the next installment in arguably the biggest AAA game series. As indicated by a recent teaser image, GTA VI will be set in Leonida, Rockstar's take on Florida, and largely centered on Vice City, the series' stand in for Miami. The game will have a playable female character for the first time in the modern incarnation of the franchise, and we get swampy areas, inspired by Florida's National Park, and almost as swampy strip clubs. It is GTA, after all. The game will launch in 2025.

AI development and concerns about its safety continue to grow at a rapid pace with little regulation in place. The latest industry-based solution to this comes courtesy of IBM and Meta, which have announced the creation of the AI Alliance. Its mission centers on "fostering an open community and enabling developers and researchers to accelerate responsible innovation in AI while ensuring scientific rigor, trust, safety, security, diversity and economic competitiveness." Part of this work will involve efforts to expand the number of open-source AI models -- ones with public source code -- which runs counter to the private models of companies like OpenAI and Google. Open-sourcing is a key pillar of the AI Alliance.

The deputy commander of Russia's 14th Army Corps, Major-General Vladimir Zavadsky, has been killed in Ukraine, a top regional official confirmed. Zavadsky died "at a combat post in the special operation zone", Alexander Gusev, the governor of Russia's Voronezh region, said on Monday without providing any further details. The "special military operation" is the term Russia uses to describe the war in Ukraine, which it launched in February 2022. Gusev paid tribute to Zavadsky, calling him "a courageous officer, a real general and a worthy man". Zavadsky's death marked the seventh major-general confirmed dead by Russia, making him the 12th senior officer reported deceased since the onset of the war, investigative news outlet iStories reported. Meanwhile, on Tuesday, Ukrainian authorities reported that their military successfully downed 10 out of 17 attack drones launched by Russia overnight.

A Nigerian military attack that used drones to target rebels instead killed at least 85 civilians gathered for a religious celebration, authorities said Monday. The attack was the latest in recent errant bombings of residents in Nigeria's troubled regions; between February 2014 when a Nigerian military aircraft dropped a bomb on Daglun in Borno state killing 20 civilians and September 2022, there were at least 14 documented incidences of such bombings in residential areas. The attack on Sunday night in Tudun Biri village of Kaduna state's Igabi council area took place as Muslims gathered there to observe the holiday celebrating the birthday of the Prophet Muhammad. Kaduna Governor Uba Sani said civilians were "mistakenly killed and many others were wounded" by a drone "targeting terrorists and bandits". The National Emergency Management Agency said in a statement on Tuesday that "85 dead bodies have so far been buried while search is still ongoing".

Doctors believe Artificial Intelligence is now saving lives, after a major advancement in breast cancer screenings. A.I. is detecting early signs of the disease, in some cases years before doctors would find the cancer on a traditional scan. In an audacious move, the White House recently issued a staggering 111-page executive order on Artificial Intelligence. Typically, executive orders are concise directives, prompting federal agencies to craft specific, detailed regulations. However, this sweeping document reflects the worldview that AI isn't just a technological advancement; it's an existential societal threat and only the government holds the keys to our technological salvation.

This paper presents an automated machine learning framework designed to assist hydrologists in detecting anomalies in time series data generated by sensors in a research watershed in the northeastern United States critical zone. The framework specifically focuses on identifying peak-pattern anomalies, which may arise from sensor malfunctions or natural phenomena. However, the use of classification methods for anomaly detection poses challenges, such as the requirement for labeled data as ground truth and the selection of the most suitable deep learning model for the given task and dataset. To address these challenges, our framework generates labeled datasets by injecting synthetic peak patterns into synthetically generated time series data and incorporates an automated hyperparameter optimization mechanism. This mechanism generates an optimized model instance with the best architectural and training parameters from a pool of five selected models, namely Temporal Convolutional Network (TCN), InceptionTime, MiniRocket, Residual Networks (ResNet), and Long Short-Term Memory (LSTM). The selection is based on the user's preferences regarding anomaly detection accuracy and computational cost. The framework employs Time-series Generative Adversarial Networks (TimeGAN) as the synthetic dataset generator. The generated model instances are evaluated using a combination of accuracy and computational cost metrics, including training time and memory, during the anomaly detection process. Performance evaluation of the framework was conducted using a dataset from a watershed, demonstrating consistent selection of the most fitting model instance that satisfies the user's preferences.

Urban Air Mobility (UAM) represents a promising solution for future transportation. In this study, we introduce VertiSim, an advanced event-driven simulator developed to evaluate e-VTOL transportation networks. Uniquely, VertiSim simultaneously models passenger, aircraft, and energy flows, reflecting the interrelated complexities of UAM systems. We utilized VertiSim to assess 19 operational scenarios serving a daily demand for 2,834 passengers with varying fleet sizes and vertiport distances. The study aims to support stakeholders in making informed decisions about fleet size, network design, and infrastructure development by understanding tradeoffs in passenger delay time, operational costs, and fleet utilization. Our simulations, guided by a heuristic dispatch and charge policy, indicate that fleet size significantly influences passenger delay and energy consumption within UAM networks. We find that increasing the fleet size can reduce average passenger delays, but this comes at the cost of higher operational expenses due to an increase in the number of repositioning flights. Additionally, our analysis highlights how vertiport distances impact fleet utilization: longer distances result in reduced total idle time and increased cruise and charge times, leading to more efficient fleet utilization but also longer passenger delays. These findings are important for UAM network planning, especially in balancing fleet size with vertiport capacity and operational costs. Simulator demo is available at: https://tinyurl.com/vertisim-vis

Perception, Planning, and Control form the essential components of autonomy in advanced air mobility. This work advances the holistic integration of these components to enhance the performance and robustness of the complete cyber-physical system. We adapt Perception Simplex, a system for verifiable collision avoidance amidst obstacle detection faults, to the vertical landing maneuver for autonomous air mobility vehicles. We improve upon this system by replacing static assumptions of control capabilities with dynamic confirmation, i.e., real-time confirmation of control limitations of the system, ensuring reliable fulfillment of safety maneuvers and overrides, without dependence on overly pessimistic assumptions. Parameters defining control system capabilities and limitations, e.g., maximum deceleration, are continuously tracked within the system and used to make safety-critical decisions. We apply these techniques to propose a verifiable collision avoidance solution for autonomous aerial mobility vehicles operating in cluttered and potentially unsafe environments.