Follow this author to personalize your feed and get instant alerts. Follow Go to your personalized feed WHY FOLLOW? Smart Alerts: Get notified about major news as it happens. Mandel is a senior editor at TIME. This year, the U.N. issued its landmark Global Water Bankruptcy report, authored by Kaveh Madani, who is known for coining the concept of "water bankruptcy."

The Dell Laptop Buying Guide UK: Which Dell Laptop Should You Buy? When you purchase through links in our articles, we may earn a small commission. The MSI Pro Max Edge AI+ stands out with its minimalist 4L aluminum chassis and proprietary Frozr AI Pro cooling system. The MSI Pro Max Edge AI+ is a powerful compact workstation for local AI and large-scale media projects. The integrated power supply keeps the setup tidy. In the benchmark test carried out, the cooling system operated without thermal throttling. Weaknesses include the soldered-in RAM and the lack of OCuLink. The high price is an even greater drawback.

You open FoodNeverComes, pick from 22 cuisines and start scrolling. You add a few dishes, watch the total climb and hit checkout. A tracker says a rider is on the way. Then you get a dummy AI-generated call from inside the site. He is outside your building, he says, but cannot find your street or door.

Can you eat too much sugar free candy? But it'll probably just send you running to the bathroom. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Sugar-free candy generally replaces sugar with either artificial sweeteners or sugar alcohols. Breakthroughs, discoveries, and DIY tips sent six days a week.

A recent study tracked hundreds of soccer fans until their favorite team reached the final of a tournament. Their stress levels skyrocketed, and their heart rates jumped too. You might think you are, but your body is going to have to be prepared to put in some work--especially if your favorite team makes it. Research shows that watching high-pressure matches can raise your heart rate, increase your stress levels, and put extra strain on your cardiovascular system. According to a recent study from researchers at Bielefeld University in Germany, fans' physiological stress increases by about 41 percent during a soccer final compared to a normal day.

Spiking Neural Networks (SNNs) often rely on rate coding, where high-precision inference depends on long time-steps, leading to significant latency and energy cost--especially for ANN-to-SNN conversions. To address this, we propose Adaptive Fission, a post-training encoding technique that selectively splits highsensitivity neurons into groups with varying scales and weights. This enables neuron-specific, on-demand precision and threshold allocation while introducing minimal spatial overhead. As a generalized form of population coding, it seamlessly applies to a wide range of pretrained SNN architectures without requiring additional training or fine-tuning. Experiments on neuromorphic hardware demonstrate up to 80% reductions in latency and power consumption without degrading accuracy.

Auditory attention detection (AAD) aims to decode listeners' focus in complex auditory environments from electroencephalography (EEG) recordings, which is crucial for developing neuro-steered hearing devices. Despite recent advancements, EEG-based AAD remains hindered by the absence of synergistic frameworks that can fully leverage complementary EEG features under energy-efficiency constraints. We propose S2M-Former, a novel spiking symmetric mixing framework to address this limitation through two key innovations: i) Presenting a spike-driven symmetric architecture composed of parallel spatial and frequency branches with mirrored modular design, leveraging biologically plausible token-channel mixers to enhance complementary learning across branches; ii) Introducing lightweight 1D token sequences to replace conventional 3D operations, reducing parameters by 14.7 . The brain-inspired spiking architecture further reduces power consumption, achieving a 5.8 energy reduction compared to recent ANN methods, while also surpassing existing SNN baselines in terms of parameter efficiency and performance. Comprehensive experiments on three AAD benchmarks (KUL, DTU and AV-GC-AAD) across three settings (within-trial, cross-trial and cross-subject) demonstrate that S2M-Former achieves comparable state-of-the-art (SOTA) decoding accuracy, making it a promising low-power, high-performance solution for AAD tasks.

Artificial intelligence (AI) has become a powerful tool for economic research, enabling large-scale simulation and policy optimization. However, applying AI effectively requires simulation platforms for scalable training and evaluation--yet existing environments remain limited to simplified, narrowly scoped tasks, falling short of capturing complex economic challenges such as demographic shifts, multigovernment coordination, and large-scale agent interactions. To address this gap, we introduce EconGym, a scalable and modular testbed that connects diverse economic tasks with AI algorithms. Grounded in rigorous economic modeling, EconGym implements 11 heterogeneous role types (e.g., households, firms, banks, governments), their interaction mechanisms, and agent models with well-defined observations, actions, and rewards. Users can flexibly compose economic roles with diverse agent algorithms to simulate rich multi-agent trajectories across 25+ economic tasks for AI-driven policy learning and analysis. Experiments show that EconGym supports diverse and cross-domain tasks--such as coordinating fiscal, pension, and monetary policies--and enables benchmarking across AI, economic methods, and hybrids. Results indicate that richer task composition and algorithm diversity expand the policy space, while AI agents guided by classical economic methods perform best in complex settings.

Venues hosting the 2026 World Cup must meet high standards to obtain environmental certifications, but FIFA also requires that they use natural grass, which is water-intensive to maintain. Estadio Banorte, formerly called Azteca stadium, in Mexico City. Because of their scale, soccer stadiums require a fair amount of energy and water. In that time, they also generate large volumes of waste, mainly plastics and food trash. For the 2026 World Cup, the first to be held in three countries in 16 different stadiums, FIFA maintained the requirement that the venues must have LEED environmental certifications, which measure performance in water, energy, and waste management.

Capped-usage SaaS products -- LLM subscriptions such as Claude Code and ChatGPT, cloud platforms such as Vercel and Cloudflare Workers, corporate benefit platforms, identity-verification services with liability transfer -- share a structural signature with insurance products: a fixed premium decoupled from realized consumption, stochastic per-user demand with heavy-tailed severity, a non-fungible cap that resets on a fixed schedule, and a portfolio-level exposure that requires reserve adequacy under tail risk. We argue that this is not an analogy. It is the same operational problem actuarial science has been tooled for decades to address, restated with new dependent variables (tokens, bandwidth bytes, function-invocations, gym check-ins) in place of medical claims. This paper proposes a modeling framework for capped-usage SaaS pricing built from frequency-severity decomposition, premium calculation principles, and Monte Carlo reserve adequacy. We map the framework to publicly observable subscription tiers in two domains (LLM services and cloud platforms), ground it in canonical health-insurance economics (Arrow 1963; Pauly 1968; Manning et al. 1987; Brot-Goldberg et al. 2017), and demonstrate divergence from traditional unit economics through a worked example. The contribution is operational rather than theoretical: not a new theorem, but vocabulary and tools currently absent from cs.LG/stat.ML practice.