[Invitation] Galaxy Unpacked February 2026: The New AI Cellphone to Make Your Life Simpler
Samsung Electronics unveils its new Galaxy S collection at “Galaxy Unpacked 2026,” to be hosted in San Francisco, USA. Showcasing Samsung’s latest Galaxy improvements to make every-day life much more handy and environment friendly, the occasion will likely be streamed reside on Samsung.com, Samsung Newsroom and the Samsung YouTube channel on February 26, from 10 a.m. PT, 1 p.m. EST, 6 p.m. GMT and seven p.m. CET. Be the primary to see the newest next-generation cell gadget to affix the Galaxy ecosystem on the Galaxy Unpacked 2026 reside occasion.
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Navigating the Samsung Pay SDK Growth Lifecycle: Finest Practices and Troubleshooting for Seamless Integration
To make sure seamless Samsung Pay integration, companions ought to comply with established finest practices, together with understanding the total improvement lifecycle, proactively addressing potential challenges, and adhering to tips for partnership setup, improvement, testing, and launch. This tutorial gives a sensible information to those practices and troubleshooting methods for integrating the Samsung Pay SDK. Learn to successfully handle every important step, together with the testing course of, and how one can set your product up for achievement.
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How Galaxy Watch’s EDA Sensor Enhances Your Well being Monitoring
The Electrodermal Exercise (EDA) sensor launched in Galaxy Watch8 displays and exactly analyzes physiological responses to supply detailed insights into customers’ stress ranges and sleep patterns. With the Samsung Well being Sensor SDK, builders can now straight make the most of uncooked EDA knowledge to create an revolutionary healthcare resolution that helps enhance sleep high quality and extra. Study extra about EDA knowledge, whose potential to advance the way forward for digital well being was demonstrated on the World Sleep Congress 2025, on our weblog.
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Samsung Achieves One other Trade-First Virtualized RAN Milestone, Accelerating AI-Native, 6G-Prepared Networks
Samsung Electronics has efficiently accomplished the business’s first business name on a Tier 1 U.S. operator’s reside community, utilizing its vRAN resolution powered by the Intel Xeon 6700P-B processor, supporting as much as 72 cores. This achievement represents greater than easy connectivity. It marks a technological breakthrough during which advanced community workloads, together with the cell core, radio entry, transport, and safety capabilities that had been beforehand bodily separated, had been absolutely built-in and processed inside a single-server setting. From considerably lowering energy consumption and complete price of possession (TCO) to constructing AI-native infrastructure, Samsung’s vRAN creates an optimized platform for the 6G period. Study extra about this innovation in our Newsroom.
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A Reinforcement Studying-Primarily based Price Management for Neural Video Compression
Over the previous few years, we’ve got witnessed the explosive development of end-to-end neural video compression (NVC) approaches, which surpass conventional requirements by leveraging the highly effective nonlinear modeling functionality of deep neural networks (DNNs) and some great benefits of optimization with large-scale coaching knowledge. Nevertheless, analysis on fee management, which is an integral part for the profitable deployment of video codecs in real-world purposes, stays restricted.
On this examine, we redefine NVC fee management as a Sequential Choice-Making Course of, assuaging the constraints of temporal stationarity and attaining joint optimization without having a further two-step method. We’ve got additional developed a devoted Actor-Critic reinforcement studying framework that comes with spatial-temporal state modeling and a joint quality-accuracy reward perform. Our experimental outcomes present a 19.7% discount in encoding time. This examine reveals the potential of NVC purposes and their feasibility by attaining breakthrough compression effectivity. Study extra about it on the Samsung Analysis weblog.
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Enhancing Noise Resilience in Face Clustering utilizing a Sparse Differential Transformer
The strategy used to measure relationships between face embeddings performs a important function in figuring out face clustering efficiency. Present strategies make use of the Jaccard similarity coefficient as a substitute of cosine distance to enhance measurement accuracy. Nevertheless, these strategies have a tendency to incorporate too many irrelevant nodes that decrease discriminative energy, which finally impacts clustering efficiency.
To deal with this downside, Samsung Analysis proposes a prediction-based Prime-Okay Jaccard similarity coefficient that improves measurement reliability by enhancing the purity of neighboring nodes. We’ve got developed a Sparse Differential Transformer (SDT) mannequin with an enhanced anti-noise functionality to resolve the noise concern launched by the traditional vanilla transformer adopted within the optimum Prime-Okay prediction course of. The face similarity captured as its result’s assessed to be extra correct than FC-ESER. SDT has confirmed to be a strong resolution by attaining state-of-the-art efficiency throughout a number of datasets, together with MS-Celeb-1M. Study extra concerning the SDT on the Samsung Analysis weblog.
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