Retail
Our Favorite Earbuds for Working Out Are Cheaper Than Ever
The Beats Powerbeats Pro 2 are $50 off on Amazon. All products featured on WIRED are independently selected by our editors. However, we may receive compensation from retailers and/or from purchases of products through these links. Beats has been a household name in headphones for years, known for punchy bass and bold styling. The Powerbeats Pro 2 (9/10, WIRED Recommends) use ergonomic over-ear hooks to stay absolutely secure in your ears when you're running, lifting, or just walking the dog.
Fall is perfect for putting out bird feeders and Amazon has a bunch on clearance
Birds can use a snack during the fall migration season and Amazon has a ton of great feeders on clearance. We may earn revenue from the products available on this page and participate in affiliate programs. If you're in the US right now, you're probably starting to get into the fall mood. So are the birds, which means they would really appreciate a snack from a well-stocked bird feeder . While there are some great smart bird feeders out there with built-in cameras, you could also get a ton of enjoyment out of a basic model.
Sainsbury's to trial facial recognition to catch shoplifters
Madeleine Stone, senior advocacy officer at privacy group BigBrotherWatch, said: "Sainsbury's decision to trial Orwellian facial recognition technology in its shops is deeply disproportionate and chilling. "Sainsbury's should abandon this trial and the government must urgently step in to prevent the unchecked spread of this invasive technology." Sainsbury's said incidents of theft, abuse and threatening behaviour "continue to rise" despite working with the police and government, adding that it is "affecting Sainsbury's teams across the UK daily". Mr Roberts, boss of the supermarket chain,added: "We have listened to the deep concerns our colleagues and customers have and they're right to expect us to act. "We understand that facial recognition technology can raise valid questions about data and privacy."
A Retail-Corpus for Aspect-Based Sentiment Analysis with Large Language Models
Silcenco, Oleg, Machad, Marcos R., Ugulino, Wallace C., Braun, Daniel
Aspect-based sentiment analysis enhances sentiment detection by associating it with specific aspects, offering deeper insights than traditional sentiment analysis. This study introduces a manually annotated dataset of 10,814 multilingual customer reviews covering brick-and-mortar retail stores, labeled with eight aspect categories and their sentiment. Using this dataset, the performance of GPT-4 and LLaMA-3 in aspect based sentiment analysis is evaluated to establish a baseline for the newly introduced data. The results show both models achieving over 85% accuracy, while GPT-4 outperforms LLaMA-3 overall with regard to all relevant metrics.
DecoMind: A Generative AI System for Personalized Interior Design Layouts
Alshehri, Reema, Alotaibi, Rawan, Almasri, Leen, Altaweel, Rawan
--This paper introduces a system for generating interior design layouts based on user inputs, such as room type, style, and furniture preferences. CLIP extracts relevant furniture from a dataset, and a layout that contains furniture and a prompt are fed to the Stable Diffusion with ControlNet to generate a design that incorporates the selected furniture. The design is then evaluated by classifiers to ensure alignment with the user's inputs, offering an automated solution for realistic interior design. I. Introduction Interior design has become increasingly popular as people seek more comfort and personalization in their living spaces. While hiring professional designers is common for full-home projects, redesigning a single room--such as a bedroom--may not justify the cost or effort involved in hiring such services.Additionally, many individuals who prefer to furnish their rooms using items from specific stores like IKEA often feel uncertain about whether suggested furniture--based on their selected categories (e.g., sofa, table)--will suit the room's size, layout, and style.
15 Best White Noise Machines (2025): Lectrofan, Snooz, Hatch, and More
The Best White-Noise Machines for a Blissful Night's Sleep Help the whole family catch more Z's with soothing background noise from our favorite sound machines. The Best White noise machine isn't a complex device, even as companies constantly add more bells and whistles. Nowadays, they come in all shapes and sizes, outfitted with the capacity to play other noise frequencies and nature sounds while at home or in a more portable, on-the-go form. They're not just for kids or babies anymore--if you're like us, trying to drown out your internal monologue so that you can finally drift off, this is the article for you. But if you're building up your arsenal of sleep gadgets, with a white noise machine among them, we've tried out everything from the best sleep trackers, best sunrise alarm clocks, the best mattresses, and the best extreme alarm clocks . We've got a directory where you can find all of our Sleep content. If you're buying for a child, keep sound machines to no more than 50 decibels and farther than 200 centimeters (6.5 feet) from where your baby sleeps.
Consumer Autonomy or Illusion? Rethinking Consumer Agency in the Age of Algorithms
Nokhiz, Pegah, Ruwanpathirana, Aravinda Kanchana
Consumer agency in the digital age is increasingly constrained by systemic barriers and algorithmic manipulation, raising concerns about the authenticity of consumption choices. Nowadays, financial decisions are shaped by external pressures like obligatory consumption, algorithmic persuasion, and unstable work schedules that erode financial autonomy. Obligatory consumption (like hidden fees) is intensified by digital ecosystems. Algorithmic tactics like personalized recommendations lead to impulsive purchases. Unstable work schedules also undermine financial planning. Thus, it is important to study how these factors impact consumption agency. To do so, we examine formal models grounded in discounted consumption with constraints that bound agency. We construct analytical scenarios in which consumers face obligatory payments, algorithm-influenced impulsive expenses, or unpredictable income due to temporal instability. Using this framework, we demonstrate that even rational, utility-maximizing agents can experience early financial ruin when agency is limited across structural, behavioral, or temporal dimensions and how diminished autonomy impacts long-term financial well-being. Our central argument is that consumer agency must be treated as a value (not a given) requiring active cultivation, especially in digital ecosystems. The connection between our formal modeling and this argument allows us to indicate that limitations on agency (whether structural, behavioral, or temporal) can be rigorously linked to measurable risks like financial instability. This connection is also a basis for normative claims about consumption as a value, by anchoring them in a formally grounded analysis of consumer behavior. As solutions, we study systemic interventions and consumer education to support value deliberation and informed choices. We formally demonstrate how these measures strengthen agency.
Bayesian Models for Joint Selection of Features and Auto-Regressive Lags: Theory and Applications in Environmental and Financial Forecasting
Manna, Alokesh, Ghosh, Sujit K.
We develop a Bayesian framework for variable selection in linear regression with autocorrelated errors, accommodating lagged covariates and autoregressive structures. This setting occurs in time series applications where responses depend on contemporaneous or past explanatory variables and persistent stochastic shocks, including financial modeling, hydrological forecasting, and meteorological applications requiring temporal dependency capture. Our methodology uses hierarchical Bayesian models with spike-and-slab priors to simultaneously select relevant covariates and lagged error terms. We propose an efficient two-stage MCMC algorithm separating sampling of variable inclusion indicators and model parameters to address high-dimensional computational challenges. Theoretical analysis establishes posterior selection consistency under mild conditions, even when candidate predictors grow exponentially with sample size, common in modern time series with many potential lagged variables. Through simulations and real applications (groundwater depth prediction, S&P 500 log returns modeling), we demonstrate substantial gains in variable selection accuracy and predictive performance. Compared to existing methods, our framework achieves lower MSPE, improved true model component identification, and greater robustness with autocorrelated noise, underscoring practical utility for model interpretation and forecasting in autoregressive settings.
Make birdwatching easy and save 50 with this Onlyfly smart bird feeder camera from Amazon
If pop culture is to be believed, there's an age where birdwatching becomes extremely appealing. It's a slow-burn hobby that rewards patience and a knack for observation (think Detective Cordelia Cupp in "The Residence"). But if you can't tell a Yellow-throated Longclaw from an Eastern Meadowlark, you might need a little help from an AI-powered identification system and an always-on backyard camera. Amazon's running a limited-time sale (or until stock flies away) on smart bird feeders with built-in 2K cameras and AI bird recognition, which give you the thrill of birdwatching at home without the binocular neck strain or standing around. This solar-powered 2K camera with AI recognition is basically a paparazzi setup for your native species, capturing pictures and video automatically.