tablet
Gear News of the Week: Samsung's TriFold Sells Out in Minutes, and a Leak Teases Google's New OS
Plus: Vivaldi browser shuns AI, Samsung has a new sustainable display, and Frankfurt Airport tests Auracast for gate announcements. Samsung's first-ever Galaxy Z TriFold went on sale this past Friday, but it sold out in minutes . This folding phone differs from the 7th-generation Galaxy Z Fold7 in that its screen can expand to a whopping 10 inches, turning it into a proper tablet . That also means it commands an incredibly high price of $2,899. It's the first device of its kind here in the West, though Huawei has its own version in China.
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Get up to 90 off reMarkable E Ink tablet bundles
Apple's Siri AI will be powered by Gemini The reMarkable 2 bundle includes a Marker stylus and folio case. E Ink tablets can provide the best of both worlds, giving you a similar tactile response to writing with pen and paper while also conveniently holding all of your digital files. For example, you can get the reMarkable 2 tablet with the Marker and Book Folio for $449, instead of the usual $568. The company also sells a newer stylus called Marker Plus that lets you erase by flipping it around just like a real pencil, but that will cost you an extra $50. If you've been eyeing a dedicated writing tablet for work, school or just jotting down notes without the distraction of endless apps, this bundle deal is an ideal opportunity to pick one up.
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Aluminium OS: Everything We Know About the Chromebook Successor
Google's Chromebook Successor Is Coming. Here's Everything We Know So Far Google has officially acknowledged the upcoming merger of Android and Chromebooks, and it may be coming in 2026. It's never fun to be in last place. Google has been coasting along with its Android tablets and Chromebooks for years, playing second fiddle to the bigger players in the game. But the company has a new card up its sleeve: the upcoming merger of its two platforms into something entirely new.
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The Best Age-Tech Gadgets Tried and Tested by WIRED
As more and more age tech hits the market, I've been testing the most innovative gadgets for older folks and caregivers. Age tech is a rapidly growing category focused on remote caregiving, improving quality of life, and enabling older folks to stay in their own homes for longer. The US Census Bureau says around 16 million elders (over 65) live alone. While the majority are healthy, with family and friends nearby, many lack support and may be battling physical and mental decline. Whether you're getting older or trying to help an aging loved one, there's an increasingly diverse range of gadgetry to choose from, but as a nascent category, it's tricky to know what will help.
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Your eyes can only handle so much HDTV
More pixels doesn't always mean a better screen. Breakthroughs, discoveries, and DIY tips sent every weekday. Every year, tech and television companies boast their products' latest and greatest, highest-resolution displays. The 4K display--a screen with a horizontal display of approximately 4,000 pixels-- first became widely available around 2014. Barely a decade later, you can purchase a TV with double the resolution .
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TABLET: Table Structure Recognition using Encoder-only Transformers
To address the challenges of table structure recognition, we propose a novel Split-Merge-based top-down model optimized for large, densely populated tables. Our approach formulates row and column splitting as sequence labeling tasks, utilizing dual Transformer encoders to capture feature interactions. The merging process is framed as a grid cell classification task, leveraging an additional Transformer encoder to ensure accurate and coherent merging. By eliminating unstable bounding box predictions, our method reduces resolution loss and computational complexity, achieving high accuracy while maintaining fast processing speed. Extensive experiments on FinTabNet and PubTabNet demonstrate the superiority of our model over existing approaches, particularly in real-world applications. Our method offers a robust, scalable, and efficient solution for large-scale table recognition, making it well-suited for industrial deployment.
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Gemini in Google Home Keeps Mistaking My Dog for a Cat
Google's Gemini AI has offended my dog, but at least it can automatically turn the lights on for me. A cat jumped up on my couch. The alert about the leaping feline is something my Google Home app sent me when I was out at a party. Turns out it was my dog. This notification came through a day after I turned on Google's Gemini for Home capability in the Google Home app.
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Large language models management of medications: three performance analyses
Henry, Kelli, Xu, Steven, Blotske, Kaitlin, Cargile, Moriah, Barreto, Erin F., Murray, Brian, Smith, Susan, Bauer, Seth R., Zhao, Xingmeng, Tilley, Adeleine, Gao, Yanjun, Liu, Tianming, Sohn, Sunghwan, Sikora, Andrea
Purpose: Large language models (LLMs) have proven performance for certain diagnostic tasks, however limited studies have evaluated their consistency in recommending appropriate medication regimens for a given diagnosis. Medication management is a complex task that requires synthesis of drug formulation and complete order instructions for safe use. Here, the performance of GPT 4o, an LLM available with ChatGPT, was tested for three medication management tasks. Methods: GPT-4o performance was tested using three medication tasks: identifying available formulations for a given generic drug name, identifying drug-drug interactions (DDI) for a given medication regimen, and preparing a medication order for a given generic drug name. For each experiment, the models raw text response was captured exactly as returned and evaluated using clinician evaluation in addition to standard LLM metrics, including Term Frequency-Inverse Document Frequency (TF IDF) vectors, normalized Levenshtein similarity, and Recall-Oriented Understudy for Gisting Evaluation (ROUGE 1/ROUGE L F1) between each response and its reference string. Results: For the first task of drug-formulation matching, GPT-4o had 49% accuracy for generic medications being matched to all available formulations, with an average of 1.23 omissions per medication and 1.14 hallucinations per medication. For the second task of drug-drug interaction identification, the accuracy was 54.7% for identifying the DDI pair. For the third task, GPT-4o generated order sentences containing no medication or abbreviation errors in 65.8% of cases. Conclusions: Model performance for basic medication tasks was consistently poor. This evaluation highlights the need for domain-specific training through clinician-annotated datasets and a comprehensive evaluation framework for benchmarking performance.
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