PCWorld emphasizes that ergonomics is crucial for PC users to prevent repetitive stress injuries and chronic pain from prolonged computer use. Regular stretch breaks every 30-45 minutes and investing in ergonomic equipment like standing desks, vertical mice, and specialized keyboards can significantly reduce physical strain. Minor aches serve as early warnings of serious injuries, making proactive ergonomic solutions essential for long-term health and comfort. Do your hands, wrists, or shoulders ache after you get up from your PC? Don't ignore it. Those minor grumbles can be the early warning signs of serious repetitive stress injuries that can impact you for the rest of your life.

Meta Is Charging a Subscription for Smart Glasses Features. Now you'll need to subscribe for "expanded access" to the most advanced features. So you paid a few hundred bucks for a neat little gadget and think you're good to go. But it turns out you'll need to subscribe to a monthly plan to unlock its advanced features. That where AI-powered consumer electronics are increasingly heading, and Meta is the latest to prove it with its smart glasses .

Camera, wifi and design updates bring welcome upgrades to Ring's top model in wired or battery flavour The Guardian's journalism is independent. We will earn a commission if you buy something through an affiliate link. R ing's recent revamp of its popular video doorbells with a more modern design is led by the top-of-the-line Video Doorbell Pro 3, which gains much-needed upgrades with a 4K camera and better wifi plus new interesting AI features. The Guardian's journalism is independent. We will earn a commission if you buy something through an affiliate link.

After years of releasing smart glasses that bore the Ray-Ban or Oakley brand, Meta has finally made its own (although still in collaboration with Essilor Luxxotica). The company today unveiled a trio of AI Glasses -- the Fury, the Adventurer and the Meta Glasses by Kylie (labeled in some places as Starfire), and the first two of those styles start at $299. The variant that was co-designed with celebrity Kylie Jenner, will cost $399. At its launch event in New York City yesterday, Meta set us up with a pair of the new glasses and a companion phone, and let us roam around the venue and its demo areas somewhat freely. The company also had multiple units of the other styles around for us to pick up and try on as we liked, so I got a good sense of all the different options available.

The new Meta-branded glasses have the same camera, microphones, and chatbot as the Ray-Bans. They come in three styles, one of which was codesigned with Kylie Jenner. Smart glasses are like public transportation, according to Peter Bristol, Meta's vice president of industrial design. "People will use it when it's good enough." To reach "good enough," Meta is making its smart glasses more accessible, more customizable, and comfier to wear.

Video generation has emerged as a promising tool for world simulation, leveraging visual data to replicate real-world environments. Within this context, egocentric video generation, which centers on the human perspective, holds significant potential for enhancing applications in virtual reality, augmented reality, and gaming. However, the generation of egocentric videos presents substantial challenges due to the dynamic nature of egocentric viewpoints, the intricate diversity of actions, and the complex variety of scenes encountered. Existing datasets are inadequate for addressing these challenges effectively. To bridge this gap, we present EgoVid-5M, the first high-quality dataset specifically curated for egocentric video generation. EgoVid-5M encompasses 5 million egocentric video clips and is enriched with detailed action annotations, including 5M high-level textual descriptions and 65K fine-grained kinematic control annotations. To ensure the integrity and usability of the dataset, we implement a sophisticated data cleaning pipeline designed to maintain frame consistency, action coherence, and motion smoothness under egocentric conditions. Furthermore, we introduce EgoDreamer, which is capable of generating egocentric videos driven simultaneously by action descriptions and kinematic control signals. The EgoVid-5M dataset, associated action annotations, and all data cleansing metadata will be released for the advancement of research in egocentric video generation.

Physiological signals are often corrupted by motion artifacts, baseline drift, and other low-SNR disturbances, which pose significant challenges for analysis. Additionally, these signals exhibit strong non-stationarity, with sharp peaks and abrupt changes that evolve continuously, making them difficult to represent using traditional time-domain or filtering methods. To address these issues, a novel waveletbased approach for physiological signal analysis is presented, aiming to capture multi-scale time-frequency features in various physiological signals. Leveraging this technique, two large-scale pretrained models specific to EMG and ECG are introduced for the first time, achieving superior performance and setting new baselines in downstream tasks. Additionally, a unified multi-modal framework is constructed by integrating pretrained EEG model, where each modality is guided through its dedicated branch and fused via learnable weighted fusion. This design effectively addresses challenges such as low signal-to-noise ratio, high inter-subject variability, and device mismatch, outperforming existing methods on multi-modal tasks. The proposed wavelet-based architecture lays a solid foundation for analysis of diverse physiological signals, while the multi-modal design points to nextgeneration physiological signal processing with potential impact on wearable health monitoring, clinical diagnostics, and broader biomedical applications.

We present 4KAgent, a unified agentic super-resolution generalist system designed to universally upscale any image to 4K resolution (and even higher, if applied iteratively). Our system can transform images from extremely low resolutions with severe degradations, for example, highly distorted inputs at 256 256, into crystal-clear, photorealistic 4K outputs.

Eye gaze offers valuable cues about attention, short-term intent, and future actions, making it a powerful signal for modeling egocentric behavior. In this work, we propose a gaze-regularized framework that enhances VLMs for two key egocentric understanding tasks: fine-grained future event prediction and current activity understanding. Unlike prior approaches that rely solely on visual inputs or use gaze as an auxiliary input signal, our method uses gaze only during training. We introduce a gaze-regularized attention mechanism that aligns model focus with human visual gaze. This design is flexible and modular, allowing it to generalize across multiple VLM architectures that utilize attention. Experimental results show that our approach improves semantic prediction scores by up to 11% for future event prediction and around 7% for current activity understanding, compared to the corresponding baseline models trained without gaze regularization.

We propose LiteReality, a novel pipeline that converts RGB-D scans of indoor environments into compact, realistic, and interactive 3D virtual replicas. LiteReality not only reconstructs scenes that visually resemble reality but also supports key features essential for graphics pipelines--such as object individuality, articulation, high-quality physically based rendering materials. At its core, LiteReality first performs scene understanding and parses the results into a coherent 3D layout and objects, with the help of a structured scene graph.