With each passing year, the phrase "Black Friday" becomes more of a misnomer. What was once a day of post-Thanksgiving special offers has become a month of sales promotions from retailers across the web. It's happening again in 2023: Target and Best Buy are already advertising their early Black Friday deals; Amazon is price matching many of those discounts and has its own "Holiday Deals" landing page; and Walmart says it'll kick off its first wave of Black Friday deals on November 8. Many other shops and manufacturers have (or will soon have) early deals as well. This barrage of sales promos can be aggravating, but it also presents a good opportunity to get your holiday shopping done at something closer to your own pace. To help, we've rounded up the best early Black Friday deals we can find below. There's always a chance we get bigger discounts on November 24, but we're already seeing all-time lows on Apple's AirPods Pro, Google's Pixel 7a, Amazon's Echo Show 5, LG's A2 OLED TV and other gadgets we like.

Amazon bundle deals are a relatively common occurrence, but the latest one is a pairing we'd never expect: Ahead of Black Friday, Prime Members can get the Fire TV Stick 4K Max and Blink Video Doorbell as a pair for $65. The Blink Video Doorbell is $60 on its own, so for another five bucks, you're getting the Fire TV Stick 4K Max -- not a bad deal. The 4K Max is having its own sale right now, with a 25 percent discount bringing its price to $45 from $60. So, even if you factor in the sale, you're saving $40 overall, a nice steal. While the only two things these items might seem to have in common is Amazon's ownership, if we think really hard, we can connect them. Well, not having to get up to check who's at the door while using your streaming device is good for starters.

The recent M5 competition has advanced the state-of-the-art in retail forecasting. However, we notice important differences between the competition challenge and the challenges we face in a large e-commerce company. The datasets in our scenario are larger (hundreds of thousands of time series), and e-commerce can afford to have a larger assortment than brick-and-mortar retailers, leading to more intermittent data. To scale to larger dataset sizes with feasible computational effort, firstly, we investigate a two-layer hierarchy and propose a top-down approach to forecasting at an aggregated level with less amount of series and intermittency, and then disaggregating to obtain the decision-level forecasts. Probabilistic forecasts are generated under distributional assumptions. Secondly, direct training at the lower level with subsamples can also be an alternative way of scaling. Performance of modelling with subsets is evaluated with the main dataset. Apart from a proprietary dataset, the proposed scalable methods are evaluated using the Favorita dataset and the M5 dataset. We are able to show the differences in characteristics of the e-commerce and brick-and-mortar retail datasets. Notably, our top-down forecasting framework enters the top 50 of the original M5 competition, even with models trained at a higher level under a much simpler setting.

Now, it can get that job done for cheaper, as the Roomba 694 is on sale for $159 as part of an early Black Friday deal on Amazon. This is a record-low price for the gadget, with the discount slashing $115 off the MSRP. If you've been curious about hiring a robot helper to sweep the floors, but were waiting for a good deal, now might be a great time to jump on board. After all, the Roomba 694 sits at the top of our list of the best budget robot vacuums in the world. This little jobby might be low in price, but it's high in functionality.

Some of Britain's biggest retailers, including Tesco, John Lewis and Sainsbury's, have been urged to pull out of a new policing strategy amid warnings it risks wrongly criminalising people of colour, women and LGBTQ people. A coalition of 14 human rights groups has written to the main retailers – also including Marks & Spencer, the Co-op, Next, Boots and Primark – saying that their participation in a new government-backed scheme that relies heavily on facial recognition technology to combat shoplifting will "amplify existing inequalities in the criminal justice system". The letter, from Liberty, Amnesty International and Big Brother Watch, among others, questions the unchecked rollout of a technology that has provoked fierce criticism over its impact on privacy and human rights at a time when the European Union is seeking to ban the technology in public spaces through proposed legislation. "Facial recognition technology notoriously misidentifies people of colour, women and LGBTQ people, meaning that already marginalised groups are more likely to be subject to an invasive stop by police, or at increased risk of physical surveillance, monitoring and harassment by workers in your stores," the letter states.Its authors also express dismay that the move will "reverse steps" that big retailers introduced during the Black Lives Matter movement, including high-profile commitments to be champions of diversity, equality and inclusion. Meanwhile, concerns over the broadening use of facial recognition technology have further intensified after the emergence of details of a police watchlist used to justify the contentious decision to use biometric surveillance at July's Formula One British Grand Prix at Silverstone.

Black Friday seems to start earlier and earlier each year in its relentless march across the American calendar. Retailers and manufacturers have traditionally buttoned themselves down and steeled themselves for Black Friday by skimping on deals in the weeks before the big event, but some have snuck in early Black Friday deals on a few of our most recommended products. From Sonos to Apollo to Samsung, there's enough here to whet your whistle if you can't wait--or if you just want to stealthily beat the crowds. We rounded up several other sales earlier this week that are still running, including deals on Chromebooks as well as discounted Arlo security cameras and video doorbells. Special offer for Gear readers: Get WIRED for just $5 ($25 off).

Amazon is rolling out a new beta feature that lets advertisers create AI-generated image backgrounds for products. The company describes it as "a generative AI solution designed to remove creative barriers" while boosting ad performance. "It's a perfect use for generative AI -- less effort and better outcomes," Colleen Aubrey, senior vice president of Amazon Ads Products and Technology, wrote Wednesday in an announcement blog post. The company views the feature as an ideal alternative to product shots in front of generic white backgrounds (or bad Photoshop jobs). Amazon says the process is easy and requires no technical expertise.

Jeff Bezos likes to surprise. Roaming Amazon's global headquarters in 2013, the tycoon promised a television crew half his fortune if they could guess his company's latest innovation. "Oh my God," one of his wide-eyed guests exclaimed, as they caught sight of autonomous delivery drones. Bezos, a self-declared optimist, suggested it could happen by 2017, or maybe 2018. "I know this looks like science fiction. It's not," he told 60 Minutes on CBS in 2013.

Tracking of inventory and rearrangement of misplaced items are some of the most labor-intensive tasks in a retail environment. While there have been attempts at using vision-based techniques for these tasks, they mostly use planogram compliance for detection of any anomalies, a technique that has been found lacking in robustness and scalability. Moreover, existing systems rely on human intervention to perform corrective actions after detection. In this paper, we present Co-AD, a Concept-based Anomaly Detection approach using a Vision Transformer (ViT) that is able to flag misplaced objects without using a prior knowledge base such as a planogram. It uses an auto-encoder architecture followed by outlier detection in the latent space. Co-AD has a peak success rate of 89.90% on anomaly detection image sets of retail objects drawn from the RP2K dataset, compared to 80.81% on the best-performing baseline of a standard ViT auto-encoder. To demonstrate its utility, we describe a robotic mobile manipulation pipeline to autonomously correct the anomalies flagged by Co-AD. This work is ultimately aimed towards developing autonomous mobile robot solutions that reduce the need for human intervention in retail store management.

Supply chain management (SCM) has been recognized as an important discipline with applications to many industries, where the two-echelon stochastic inventory model, involving one downstream retailer and one upstream supplier, plays a fundamental role for developing firms' SCM strategies. In this work, we aim at designing online learning algorithms for this problem with an unknown demand distribution, which brings distinct features as compared to classic online optimization problems. Specifically, we consider the two-echelon supply chain model introduced in [Cachon and Zipkin, 1999] under two different settings: the centralized setting, where a planner decides both agents' strategy simultaneously, and the decentralized setting, where two agents decide their strategy independently and selfishly. We design algorithms that achieve favorable guarantees for both regret and convergence to the optimal inventory decision in both settings, and additionally for individual regret in the decentralized setting. Our algorithms are based on Online Gradient Descent and Online Newton Step, together with several new ingredients specifically designed for our problem. We also implement our algorithms and show their empirical effectiveness.