The information war will be fought through chatbots. Hours before President Donald Trump announced Nicolás Maduro's capture, on Saturday morning, people had questions for Grok, Elon Musk's chatbot. Footage was circulating on X of explosions in Venezuela, and some users assumed the United States was responsible: "Hey @grok why is Trump sending US airstrikes to bomb Venezuela. Do you think they deserve it or not?"one "@grok what is the reason why America is bombing Venezuela," another asked.

Amazon announced at CES 2026 that Alexa+ for web will come to Early Access customers first. You no longer need an Amazon device to summon Alexa since the AI assistant will be available on the Alexa.com Amazon will roll out the web client to its Alexa+ Early Access customers first, still featuring the company's new and improved AI assistant that was announced in February. The web model won't be much different from the existing Alexa+ that's already available on Echo devices, Fire TV and Fire tablets. However, instead of buying into the Amazon ecosystem, Early Access customers can use any web browser to get Alexa+'s help with everything from basic questions to complex tasks, like controlling your smart home devices, customizing a recipe to account for dietary restrictions or making restaurant reservations if you don't feel like cooking. The Alexa+ web version will also feature a navigation sidebar that will be home to your most-used Alexa features.

Religious communities around the US are getting hit with AI depictions of their leaders sharing incendiary sermons and asking for donations. Father Mike Schmitz, a Catholic priest and podcaster, addressed his congregation of more than 1.2 million YouTube subscribers in November with an unusual kind of homily. You couldn't always trust the words coming out of his mouth, Schmitz said, because sometimes they weren't really his words--or his mouth. Schmitz had become the target of AI-generated impersonation scams . "You're being watched by a demonic human," said the fake Schmitz in one video that the real Schmitz, wearing an L.L. Bean jacket over his clerical suit, included in his public service announcement as an example.

Our AI writers make their big bets for the coming year--here are five hot trends to watch. In an industry in constant flux, sticking your neck out to predict what's coming next may seem reckless. But for the last few years we've done just that--and we're doing it again. How did we do last time? Here are our big bets for the next 12 months. The last year shaped up as a big one for Chinese open-source models.

And yes, there are more traditional OLED TVs too. LG usually announces its CES TV lineup well ahead of the show, but this year the company had a surprise at CES 2026: The return of its ultra-thin Wallpaper TV . We got a chance to check out the Wallpaper TV in action during a CES preview event, as well as the previously announced Gallery and Micro RGB sets. LG still has its typically OLED and LED sets around, but it's clear that 2026 will be filled with intriguing TVs for a variety of consumers. If money were no object, I'd want a 100-inch LG Wallpaper TV in my family room immediately. It looks shockingly thin in person -- almost as if it's some sort of sci-fi prop -- and it delivers the rich colors and dark levels we expect from OLED.

The OLED evo W6 is a little thicker at 9mm, but it's been updated with a wireless receiver that can transmit signals up to 30 feet away. It's been nearly 10 years since LG first introduced its Wallpaper TV that was so thin that the mounting process felt like applying wallpaper. After eventually discontinuing the ultra-thin TVs in 2020, LG is finally reviving the Wallpaper TV series with the OLED evo W6 that will make its debut at CES 2026. LG is marketing the updated Wallpaper TV as the world's thinnest OLED that's truly wireless, making some major upgrades to the original. Instead of the companion soundbar that housed all the ports, LG designed the Zero Connect Box that hosts all the inputs and can transmit from up to roughly 32 feet away.

When you purchase through links in our articles, we may earn a small commission. Boasting edge AI plus Google Gemini processing in the cloud, each of the Xthings Ulticam products will support Matter. Xthings is expanding its Ulticam smart camera series with a fresh slate of models designed to boost security coverage and cut down on noisy low-value alerts. Among the highlights are a long-range camera system built on Wi-Fi HaLow, a powerful floodlight camera, a wire-free model with always-on video, and an upgraded flagship indoor/outdoor camera that integrates both on-device and cloud AI. The company says its new cameras are built around what it calls Intelligent Vision, a blend of object detection on the device (powered by onboard AI) at the edge of a user's network, and cloud-based contextual and threat analysis powered by Google Gemini.

They're earbuds built for the voice command age. There's a good chance you spend more time talking to your phone's virtual assistant, or dictating text with your voice, instead of actually calling people these days. But, as convenient as voice input can be, you don't want to be the obnoxious person shouting commands to Siri or ChatGPT in a quiet library. And you probably won't have much luck dictating an email in a room with toddlers screaming and Peppa Pig blaring on the TV. At CES 2026, the startup Subtle is unveiling its solution to those issues: Voicebuds.

We derive an estimator of the spectral density of a functional time series that is the output of a multilayer perceptron neural network. The estimator is motivated by difficulties with the computation of existing spectral density estimators for time series of functions defined on very large grids that arise, for example, in climate compute models and medical scans. Existing estimators use autocovariance kernels represented as large $G \times G$ matrices, where $G$ is the number of grid points on which the functions are evaluated. In many recent applications, functions are defined on 2D and 3D domains, and $G$ can be of the order $G \sim 10^5$, making the evaluation of the autocovariance kernels computationally intensive or even impossible. We use the theory of spectral functional principal components to derive our deep learning estimator and prove that it is a universal approximator to the spectral density under general assumptions. Our estimator can be trained without computing the autocovariance kernels and it can be parallelized to provide the estimates much faster than existing approaches. We validate its performance by simulations and an application to fMRI images.

While modern multivariate forecasters such as Transformers and GNNs achieve strong benchmark performance, they often suffer from systematic errors at specific variables or horizons and, critically, lack guarantees against performance degradation in deployment. Existing post-hoc residual correction methods attempt to fix these errors, but are inherently greedy: although they may improve average accuracy, they can also "help in the wrong way" by overcorrecting reliable predictions and causing local failures in unseen scenarios. To address this critical "safety gap," we propose CRC (Causality-inspired Safe Residual Correction), a plug-and-play framework explicitly designed to ensure non-degradation. CRC follows a divide-and-conquer philosophy: it employs a causality-inspired encoder to expose direction-aware structure by decoupling self- and cross-variable dynamics, and a hybrid corrector to model residual errors. Crucially, the correction process is governed by a strict four-fold safety mechanism that prevents harmful updates. Experiments across multiple datasets and forecasting backbones show that CRC consistently improves accuracy, while an in-depth ablation study confirms that its core safety mechanisms ensure exceptionally high non-degradation rates (NDR), making CRC a correction framework suited for safe and reliable deployment.