Introducing the Galaxy Store fastlane Plugin
The Galaxy Store fastlane plugin integrates Galaxy Store publishing into your existing fastlane workflow. If you already publish applications to Google Play with fastlane, you can automate your Galaxy Store releases with the same setup and reuse the metadata and listing content you already maintain.
With the plugin, you can list the applications registered to your Seller Portal account, manage application metadata, upload an APK or AAB, choose publishing options, submit an update for review or publish immediately, manage staged rollouts, and track your application’s status throughout the Galaxy Store publication process.
Refer to the Galaxy Store fastlane plugin online guide for more information. |
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Updates to the Galaxy Store Content Publish API for ASAA and ADVSeveral new parameters have been added to the Galaxy Store Content Publish API to support compliance with the App Store Accountability Act (ASAA), which aims to protect minors in digital environments, and Android Developer Verification (ADV).
To help protect minors, four new parameters (exceptionAppYn, majorChangeYn, majorChangeDesc, and majorChangeDateTime) were added to the contentUpdate (to modify application data) and contentInfo (to view application details) API calls. These parameters are described in the Content Publish API Reference.
For ADV, three new response parameters (advStatus, advStatus[status], and advStatus[preAuthCertExpireDate]) were added to the contentList (to view all registered applications) and contentInfo (to view application details) API calls. See View Seller’s Application List and advStatus parameters for more information. |
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Migrate to the Latest Samsung Health Data SDK: Webinar Recap
Partners using the Samsung Health SDK for Android attended our recent webinar, "Migrate to the latest Samsung Health Data SDK," to learn why it is the time to move to the new version. The session covered simplified integration, two-way health data exchange, expanded SaMD data types, and how to use the migration guides and resources available on the Developer Portal. The webinar also included a live Q&A addressing common partner questions. If you missed it, you can read the key takeaways on our blog or watch the full recording on the official Samsung Developer YouTube channel. |
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Samsung Electronics Hosts Samsung AI Forum 2026 Themed “The Agentic Shift”
The Seocho office of Samsung Electronics hosted Samsung AI Forum 2026 on September 30, with a live online broadcast, bringing together leading global AI scholars to share insights into the latest technology trends.
Marking its 10th anniversary, the forum had the theme “The Agentic Shift: From Intelligence to Impact" and focused on the latest developments in agentic AI that can reason and act autonomously, and physical AI integrating with the physical world, as well as strategies for applying these technologies to industries. In particular, the forum took a deep dive into a vision for next-generation on-device agent architectures and high-performance simulation technologies using virtual environments, both offering insights relevant to developers from a practical perspective. The forum also shared AI application algorithms and implementation cases from real-world industrial settings, including digital twins in semiconductor manufacturing processes.
Recordings from the forum sessions featuring academics, global big tech experts, and Samsung Electronics experts are available on the official Samsung Developer YouTube channel.
Watch Samsung AI Forum 2026 (YouTube) |
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Managing Closed Beta Testing with the Galaxy Store Developer API
Closed beta testing in Galaxy Store helps you validate your application for stability with selected Samsung Account holders before release. This tutorial shows how to use the Galaxy Store Developer API with JavaScript (Node.js) to view closed beta test information, add or remove testers, and update the feedback channel. By automating these tasks, you can reduce manual work in Seller Portal, manage large tester groups more efficiently, and streamline your beta testing workflow.
Learn more |
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Samsung Introduces ‘SmartThings Now’ in New Platform Update That Brings More Intuitive User Experience
Samsung Electronics has announced the latest update to SmartThings, its global connected living platform. The update introduces "SmartThings Now" at the top of the Home tab, and reorganizes the layout to present key information, including dashboards, device cards, and service cards in a clearer and more streamlined way.
SmartThings Now presents cards with relevant information and immediately actionable controls for the user's current situation based on the home's insights. When users act on a suggestion, it also guides them to create a routine. Also introduced in this update is local control technology that allows a mobile device to communicate directly with a SmartThings Hub over the same Wi-Fi network bypassing the cloud, reducing response time by approximately 30%.
Check out the redesigned SmartThings home experience with 470 million registered users and support for more than 430 WWST-certified brands worldwide, on the Samsung Electronics Newsroom.
Learn more |
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Voice Over NB-IoT NTN in 3GPP Release 20
Narrowband Internet of Things (NB-IoT) was introduced as a part of 3GPP Release 13 in 2015 as a device category for IoT applications. Derived from 4G, it deliberately strips off many features to simplify implementation. Adapted for satellite environments in Release 17, NB-IoT NTN became the first widely available form of satellite-based 3GPP cellular connectivity. Its standardization is underway to support voice communications in Release 20. However, GEO satellite environments present significant challenges: propagation delays exceed 250 milliseconds, and data rates remain below 10 kbps. In simplifying NB-IoT, several features required for voice were omitted from the original specifications, including semi-persistent scheduling (SPS), robust header compression (RoHC), and emergency call procedures.
3GPP adopted a user plane approach that utilizes existing 4G voice procedures, and defined SPS, RoHC, and emergency call procedures. It also supports device transmission power of up to 37 dBm to ensure satellite uplink reliability. In particular, 3GPP has begun standardizing an Ultra Low Bitrate speech Codec (ULBC), operating at 1.0 kbps and 1.4 kbps to handle the limited bandwidth. This is the first attempt in 3GPP voice codec standardization where the candidate solutions are expected to be AI-based. Learn more about the ongoing standardization of voice over NB-IoT NTN, with the first standards targeted for publication for early 2027, on the Samsung Research blog.
Learn more |
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AnySimLite: A Lightweight Few-Shot Similarity Encoder for On-Device Speech-Adjacent Classification
Modern smartphones quietly run a surprising number of machine learning models to handle a range of features on-device: Voice assistants classify user intent, messaging applications flag spam, and keyboards analyze sentiment. Keeping this processing on the device is essential for privacy, network-independent latency, and energy efficiency. However, because each feature has traditionally relied on its own specialized model, storage and memory requirements grow with every new feature. The overhead arising from the combined storage and memory footprint is difficult to avoid when each task requires a separate architecture that must be compressed individually.
Samsung Research proposes AnySimLite, a similarity encoder that handles multiple classification tasks using a single lightweight architecture to address this issue. As these features at their core all involve classifying text into known categories, we have reframed the notion as nuanced text similarity (NTS), where similarity is judged based on task-specific feature alignment. With around 20 examples per class, the model classifies a new input by comparing it with the examples for each class and asking which class the new input is most similar to. Across nine datasets spanning six task families, AnySimLite achieved an average accuracy degradation of only 2.24%, relative to the best reported results. The 8-bit quantized model occupies roughly 700 KB on disk and runs inference in under 30 ms on the Galaxy S25 Ultra. AnySimLite demonstrates that an encoder smaller than 1 MB can replace a fleet of task-specific on-device classification models. Learn more about it on the Samsung Research blog.
Learn more |
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