Samsung's AI Strategy: Revolutionizing Everyday Devices with On-Device and Hybrid AI

[AI Leadership] ③ Samsung's AI Strategy Centered on Customer Experiences

AI itself is not the Holy Grail at Samsung Electronics. Rather, AI is a tool -- a relatively new and powerful one -- to make meaningful improvements in users' everyday lives. Building on a long tradition of technological leadership and open innovation, Samsung leverages its diverse capabilities -- that range from operational technologies such as on-device and cloud AI to strategies including proprietary AI model development and partnerships -- to deliver practical solutions and elevate the customer experience. In this final installment of Samsung's AI Leadership series, Samsung Newsroom explores how Samsung's technological expertise and research initiatives aim to refine AI-driven user interactions across its expansive portfolio. Samsung utilizes on-device and cloud-based AI solutions in its offerings. This strategy is further reinforced by the pursuit of hybrid AI, which integrates the strengths of both technologies to provide context-aware, tailored solutions for diverse user needs. The decision on which type or combination of technologies to employ is anchored by this ultimate goal -- "How can we best serve the consumer?" On-device AI delivers secure and efficient AI experiences in devices such as smartphones and TVs by utilizing only the data and resources on the device itself. Because on-device AI doesn't communicate with the cloud, responses are virtually instantaneous. Since data doesn't leave the device, the technology is often considered safer for sensitive procedures such as those that involve personal information. Similarly, edge AI operates independently of cloud infrastructure and relies solely on specific local resources to perform AI functions. In interconnected home environments where appliances and IoT devices work in tandem, data processing in edge AI can be handled by either devices with higher performance specifications or devices nearby -- without depending on the cloud. Thus, edge AI offers speed and security benefits akin to on-device AI. While on-device and edge AI rely on technologies that use smaller models and fewer computations in constrained hardware environments, experiences that require access to extensive online information or high-performance computing are supported by cloud-based AI. The technology utilizes vast datasets and large-scale AI models hosted on servers to deliver a range of advanced capabilities. To achieve high performance while maintaining efficiency and security, Samsung conducts extensive research in areas including minimizing data latency, optimizing model efficiency and implementing data anonymization and encryption. With expertise in all these different forms of AI -- on-device, edge and cloud-based -- Samsung takes a step further and combines different formats as necessary to best serve the needs of each use case. In hybrid AI, sensitive and quick-response data can be processed using on-device AI models while the cloud can manage processing that requires external resources like up-to-date information or high-performance models. Galaxy AI, for instance, uses both on-device AI and cloud AI -- operating either independently or simultaneously as needed -- to deliver optimized solutions for users. Samsung continues to drive innovation in the realm of generative AI, further enhancing the versatility of its products and services. For instance, Galaxy AI offers a suite of features including Chat Assist, which supports translation and interpretation in select messaging apps; Note Assist, which helps summarize notes and generates note covers; and Photo Assist, which edits images with generative AI. Generative AI is also supported on select Samsung TVs and home appliances through the Generative Wallpaper feature. Users can enjoy 4K wallpapers that fit their tastes on the 2024 Neo QLED TV or transform their kitchens with AI-generated cover screens on the Family Hub™ refrigerator. To offer the best generative AI experience on its devices, Samsung not only collaborates with partners but also develops its own AI models. From fundamental technologies beginning with initial research -- including foundation model development -- to data collection and training as well as lightweight AI model development, Samsung leverages its vast expertise across the AI R&D board to optimize solutions and meet each product's specific needs. For example, Samsung developed proprietary foundation models specifically for image generation, editing and transformation to support a wide range of visual creation experiences. This was a challenge because unlike text data -- which is composed of discrete values -- image data consists of continuous values, offering nearly limitless possibilities for generation. To address this complexity, the company applied specialized training techniques to the image models while reducing their size for efficient on-device operation. Developers refined deep learning algorithms and data augmentation techniques to allow for rapid computation and seamless image creation with minimal processing requirements. These foundation models were then fine-tuned for specific applications. For instance, the Photo Ambient wallpaper in Samsung's latest smartphones integrates the image model with real-time data to create dynamic wallpapers that visually reflect current conditions such as snowfall or a starlit night depending on the time and weather. The application of generative AI is rapidly expanding beyond personal daily use into enterprise environments. Samsung has developed a proprietary generative AI model to strengthen its competitiveness in AI technology, securely manage sensitive internal information and optimize performance and scalability for specific purposes. Proprietary generative AI allows the company to establish models tailored to a wide range of products and services while improving internal productivity in a more secure environment. Samsung recently unveiled its upgraded proprietary generative AI model, Samsung Gauss2 with better performance and efficiency compared to its predecessor, Samsung Gauss1, introduced last year. Samsung Gauss2 is a multimodal model capable of simultaneously processing and understanding various data types. Samsung Gauss2 is available in three models tailored to specific use cases -- Compact, Balanced and Supreme. The Compact model is a lightweight variant optimized for on-device AI. The Balanced model, a medium-sized cloud-based variant, is designed for tasks such as text and code generation. The Supreme model, a large cloud-based variant, is built to support high-performance services with a particular focus on improving workplace productivity. To efficiently implement large models like the Supreme variant, Samsung has incorporated the Mixture of Experts (MoE) technique to selectively activate only the "expert models" most suitable for specific tasks within a large-scale neural network. MoE significantly reduces the number of computations during training and inference by activating only the necessary components, rather than running all expert models simultaneously in response to each query. This selective activation not only enhances efficiency but also facilitates the expansion of the model to address increasingly complex problems by adding more expert models. Samsung has meticulously trained these expert models to operate accurately and without interference. Samsung Gauss2 is already being applied across multiple areas within Samsung. For instance, the Device eXperience (DX) Division employs Samsung Gauss2's coding assistant service to support research and development activities. This service leverages a specialized model -- trained on Samsung's proprietary data, code and processes -- to generate code needed for product and service development. Fully integrated into the company's internal software development environment, the coding assistant supports natural language interactions and various programming languages to streamline developer workflows. The Samsung Gauss Portal, a conversational AI service, is widely used for workplace tasks such as document summarization and translation, email drafting and more. Future updates aim to enhance the portal's natural language question-and-answer capabilities and expand its multimodal features to include interpreting tables and charts and generating images. Leveraging its extensive product lines, Samsung is developing technologies that support on-device, cloud and generative AI to deliver a distinct competitive edge in AI capabilities. By connecting with consumers through its products, the company gains valuable insights into user behaviors and needs to enable the development of practical AI solutions. This creates a virtuous cycle -- whereby user data informs AI advancements, which in turn deliver value back to consumers. Samsung couples this understanding of products with in-house advancements and strategic partnerships to implement optimal AI technologies. For instance, neural processing units (NPUs) -- specialized accelerators for AI computation -- must be tailored to meet the specific requirements of individual products, rather than applied uniformly across all devices. Samsung not only designs NPUs in-house for its own products but also applies software optimizations to partner chipsets, ensuring support for AI functions and peak performance in Samsung devices. In addition, the company draws on the expertise and perspectives of product-specific specialists to address security issues and facilitate the immediate application of solutions to products while driving continuous technological improvement. The blockchain-based, multi-device security solution Knox Matrix is a notable example of how this collaborative approach can create an environment in which connected devices check each other for threats to enhance security. Through the implementation of customized AI technologies, Samsung continues to unlock new possibilities for users. Looking ahead, the company plans to deliver more differentiated AI experiences that empower users through meaningful and enriching interactions.

[AI Leadership] ③ Samsung's AI Strategy Centered on Customer Experiences

AI itself is not the Holy Grail at Samsung Electronics. Rather, AI is a tool -- a relatively new and powerful one -- to make meaningful improvements in users' everyday lives. Building on a long tradition of technological leadership and open innovation, Samsung leverages its diverse capabilities -- that range from operational technologies such as on-device and cloud AI to strategies including proprietary AI model development and partnerships -- to deliver practical solutions and elevate the customer experience. In this final installment of Samsung's AI Leadership series, Samsung Newsroom explores how Samsung's technological expertise and research initiatives aim to refine AI-driven user interactions across its expansive portfolio. Samsung utilizes on-device and cloud-based AI solutions in its offerings. This strategy is further reinforced by the pursuit of hybrid AI, which integrates the strengths of both technologies to provide context-aware, tailored solutions for diverse user needs. The decision on which type or combination of technologies to employ is anchored by this ultimate goal -- "How can we best serve the consumer?" On-device AI delivers secure and efficient AI experiences in devices such as smartphones and TVs by utilizing only the data and resources on the device itself. Because on-device AI doesn't communicate with the cloud, responses are virtually instantaneous. Since data doesn't leave the device, the technology is often considered safer for sensitive procedures such as those that involve personal information. Similarly, edge AI operates independently of cloud infrastructure and relies solely on specific local resources to perform AI functions. In interconnected home environments where appliances and IoT devices work in tandem, data processing in edge AI can be handled by either devices with higher performance specifications or devices nearby -- without depending on the cloud. Thus, edge AI offers speed and security benefits akin to on-device AI. While on-device and edge AI rely on technologies that use smaller models and fewer computations in constrained hardware environments, experiences that require access to extensive online information or high-performance computing are supported by cloud-based AI. The technology utilizes vast datasets and large-scale AI models hosted on servers to deliver a range of advanced capabilities. To achieve high performance while maintaining efficiency and security, Samsung conducts extensive research in areas including minimizing data latency, optimizing model efficiency and implementing data anonymization and encryption. With expertise in all these different forms of AI -- on-device, edge and cloud-based -- Samsung takes a step further and combines different formats as necessary to best serve the needs of each use case. In hybrid AI, sensitive and quick-response data can be processed using on-device AI models while the cloud can manage processing that requires external resources like up-to-date information or high-performance models. Galaxy AI, for instance, uses both on-device AI and cloud AI -- operating either independently or simultaneously as needed -- to deliver optimized solutions for users. Samsung continues to drive innovation in the realm of generative AI, further enhancing the versatility of its products and services. For instance, Galaxy AI offers a suite of features including Chat Assist, which supports translation and interpretation in select messaging apps; Note Assist, which helps summarize notes and generates note covers; and Photo Assist, which edits images with generative AI. Generative AI is also supported on select Samsung TVs and home appliances through the Generative Wallpaper feature. Users can enjoy 4K wallpapers that fit their tastes on the 2024 Neo QLED TV or transform their kitchens with AI-generated cover screens on the Family Hub™ refrigerator. To offer the best generative AI experience on its devices, Samsung not only collaborates with partners but also develops its own AI models. From fundamental technologies beginning with initial research -- including foundation model development -- to data collection and training as well as lightweight AI model development, Samsung leverages its vast expertise across the AI R&D board to optimize solutions and meet each product's specific needs. For example, Samsung developed proprietary foundation models specifically for image generation, editing and transformation to support a wide range of visual creation experiences. This was a challenge because unlike text data -- which is composed of discrete values -- image data consists of continuous values, offering nearly limitless possibilities for generation. To address this complexity, the company applied specialized training techniques to the image models while reducing their size for efficient on-device operation. Developers refined deep learning algorithms and data augmentation techniques to allow for rapid computation and seamless image creation with minimal processing requirements. These foundation models were then fine-tuned for specific applications. For instance, the Photo Ambient wallpaper in Samsung's latest smartphones integrates the image model with real-time data to create dynamic wallpapers that visually reflect current conditions such as snowfall or a starlit night depending on the time and weather. The application of generative AI is rapidly expanding beyond personal daily use into enterprise environments. Samsung has developed a proprietary generative AI model to strengthen its competitiveness in AI technology, securely manage sensitive internal information and optimize performance and scalability for specific purposes. Proprietary generative AI allows the company to establish models tailored to a wide range of products and services while improving internal productivity in a more secure environment. Samsung recently unveiled its upgraded proprietary generative AI model, Samsung Gauss2 with better performance and efficiency compared to its predecessor, Samsung Gauss1, introduced last year. Samsung Gauss2 is a multimodal model capable of simultaneously processing and understanding various data types. Samsung Gauss2 is available in three models tailored to specific use cases -- Compact, Balanced and Supreme. The Compact model is a lightweight variant optimized for on-device AI. The Balanced model, a medium-sized cloud-based variant, is designed for tasks such as text and code generation. The Supreme model, a large cloud-based variant, is built to support high-performance services with a particular focus on improving workplace productivity. To efficiently implement large models like the Supreme variant, Samsung has incorporated the Mixture of Experts (MoE) technique to selectively activate only the "expert models" most suitable for specific tasks within a large-scale neural network. MoE significantly reduces the number of computations during training and inference by activating only the necessary components, rather than running all expert models simultaneously in response to each query. This selective activation not only enhances efficiency but also facilitates the expansion of the model to address increasingly complex problems by adding more expert models. Samsung has meticulously trained these expert models to operate accurately and without interference. Samsung Gauss2 is already being applied across multiple areas within Samsung. For instance, the Device eXperience (DX) Division employs Samsung Gauss2's coding assistant service to support research and development activities. This service leverages a specialized model -- trained on Samsung's proprietary data, code and processes -- to generate code needed for product and service development. Fully integrated into the company's internal software development environment, the coding assistant supports natural language interactions and various programming languages to streamline developer workflows. The Samsung Gauss Portal, a conversational AI service, is widely used for workplace tasks such as document summarization and translation, email drafting and more. Future updates aim to enhance the portal's natural language question-and-answer capabilities and expand its multimodal features to include interpreting tables and charts and generating images. Leveraging its extensive product lines, Samsung is developing technologies that support on-device, cloud and generative AI to deliver a distinct competitive edge in AI capabilities. By connecting with consumers through its products, the company gains valuable insights into user behaviors and needs to enable the development of practical AI solutions. This creates a virtuous cycle -- whereby user data informs AI advancements, which in turn deliver value back to consumers. Samsung couples this understanding of products with in-house advancements and strategic partnerships to implement optimal AI technologies. For instance, neural processing units (NPUs) -- specialized accelerators for AI computation -- must be tailored to meet the specific requirements of individual products, rather than applied uniformly across all devices. Samsung not only designs NPUs in-house for its own products but also applies software optimizations to partner chipsets, ensuring support for AI functions and peak performance in Samsung devices. In addition, the company draws on the expertise and perspectives of product-specific specialists to address security issues and facilitate the immediate application of solutions to products while driving continuous technological improvement. The blockchain-based, multi-device security solution Knox Matrix is a notable example of how this collaborative approach can create an environment in which connected devices check each other for threats to enhance security. Through the implementation of customized AI technologies, Samsung continues to unlock new possibilities for users. Looking ahead, the company plans to deliver more differentiated AI experiences that empower users through meaningful and enriching interactions.

[AI Leadership] ② Shaping Personalized AI With Data Intelligence and Device Connectivity

The age of personalized AI is here. Samsung Electronics offers safe, tailored AI experiences backed by user insights across its products -- from mobile devices and TVs to home appliances -- through continuous innovation in software and platform technology. Just as performance metrics and physical measurements are essential to designing customized workout routines for professional athletes, data plays a crucial role in creating personalized AI. As such, Samsung is prioritizing data intelligence research to transform vast amounts of data into meaningful and intuitive user experiences. Samsung Newsroom takes a closer look at how Samsung's advanced data research and innovative connectivity solutions are pioneering the era of personalized AI. A truly personalized AI experience starts with understanding the user. Data intelligence identifies a user's needs at specific moments based not only on historical device usage data but also on the user's present context. This enables appropriate services to be delivered in a timely manner. However, there are challenges -- for example, users don't hand in refined reports of their needs and wants; the matching of expected needs and potential services must be carried out in real time; and most of all, personal information must constantly be kept safe. As Samsung reaches consumers across nearly all daily touchpoints -- including work, entertainment, household chores, health and security -- the company has the unique opportunity to gain deep insights into user behaviors and preferences. In order to harness this potential, Samsung has strengthened its data technology capabilities by researching user data collected annually from hundreds of millions of devices and services -- all in strict compliance with internal and external regulations. As AI models develop a better understanding of users through data collection, processing and analysis, they can leverage retrieval-augmented generation (RAG) to deliver more personalized services for different contexts. By using technologies to connect reliable, logic-based knowledge bases to large language models (LLMs), these AI models access the latest, most reliable information and find the most suitable answers. As Samsung focuses on technologies that connect data to refine personalized AI experiences, a key question is how can such vast and complex data be managed more effectively and tailored precisely to individual needs? The answer, in part, lies in knowledge graphs. A knowledge graph is a knowledge representation technology that organizes related information in an interconnected graph format, making it easily interpretable for both humans and computers. By defining individual entities within the data and linking them, their relationship can be represented as a "triple" in the form of "subject -- predicate -- object." For example, "the capital of South Korea is Seoul" can be represented in the following graph, "South Korea -- capital -- Seoul." Various types of knowledge such as people, objects, times and places can be structured in a highly refined manner by connecting numerous entities in this triple format. Unlike traditional relational databases that fill tables with information, knowledge graphs effectively store data and quickly retrieve information or new inferences as needed. Samsung is actively advancing research in knowledge graphs. While earlier forms of data usage were limited to individual apps, this technology allows for free data search and utilization across app or service boundaries -- enabling a hyper-personalized experience as if the device were tailored exclusively to the user. When combined with Samsung's on-device AI, knowledge graphs allow users to experience highly customized AI services while protecting sensitive personal data from external exposure. This technology is expected to be applied across various products and devices. The key to implementing knowledge graphs is the ability to quickly find specific answers from information represented in the graph. Converting constantly changing real-world data into graphs and efficiently extracting information requires complex computations -- and as the graphs grow, rapid information retrieval becomes more challenging. To bolster its capabilities in this area, Samsung acquired Oxford Semantic Technologies in July. Oxford Semantic Technologies, a U.K.-based startup renowned for its knowledge graph technology, specializes in optimizing data processing and advanced inference to facilitate swift understanding and precise extraction of information from knowledge graphs. Samsung has collaborated with Oxford Semantic Technologies on graph databases and ontologies since 2018, and the recent acquisition is anticipated to create synergy in personalized AI research across Samsung's product ecosystem. The company plans to develop applications that offer valuable experiences to consumers and explore new research avenues in various areas including the integration of generative AI and knowledge graphs. Samsung is rapidly incorporating personalized AI features powered by data intelligence across a wide range of products and services to enrich users' daily lives. Digital healthcare is one example. The Galaxy Watch7 and Galaxy Ring comprehensively analyze user health data including sleep, exercise and heart rate to offer an Energy Score via the Samsung Health app. Going beyond simple data measurement, this analysis provides an easy-to-understand numeric summary of a user's daily health status and personalized insights for individual activities. By researching the weighted importance of each factor in the Energy Score based on age and gender, Samsung has developed a more customized approach to health management. The entertainment experience has also been enhanced through data-driven insights. In the U.S., Gaming Hub -- Samsung's game platform available on its smartphones -- uses explainable AI (XAI) to offer personalized game recommendations. Leveraging a model of the user's preferences, this technology not only recommends games but also explains the reasoning behind each suggestion to help users select the games that suit them best. Personalized AI will evolve as more devices connect with each other and acquire usage data from users' daily lives. At Samsung Developer Conference 2024 (SDC24) in October, Samsung unveiled Home Insight -- a service that allows users to manage and control their smart home through SmartThings. The feature analyzes users' lifestyle patterns, device usage history and home conditions to provide real-time reports and tailored recommendations such as turning off devices or utilizing specific features based on different situations. In addition, Samsung has a personalized AI feature to support the well-being and safety of family members in need. Launched in June, SmartThings Family Care allows users to remotely monitor family members and take any necessary actions through SmartThings-connected devices and location-based data. The company plans to expand these AI-connected capabilities to health devices, supporting family health in areas like sleep and diet. Samsung is advancing technology that allows devices to recognize users and provide seamless, personalized experiences across all connected devices. For example, the company is planning to enable users who have large text mode activated on their smartphones to automatically apply the setting to other devices with a single voice command. Additionally, Samsung is exploring functions that use sensors and devices within the home to detect a user's location and adjust lighting, temperature and humidity according to individual preferences. Security is a fundamental requirement for delivering safe, personalized AI. To ensure the protection of personal information and address biases in AI systems, a multi-faceted approach is needed -- including improving data processing and model training processes and implementing a rigorous verification process for outputs. When collecting internal and external data for AI model training, Samsung performs data pre-processing to check and filter for privacy violations. Additionally, the company is strengthening its safety verification of AI outputs by addressing risks related to harm, bias, privacy and jailbreak vulnerabilities. Samsung's Knox Matrix further elevates security in a multi-device connected environment. Using blockchain technology, connected devices can monitor each other for security threats through Trust Chain; securely share user data by transmitting only encrypted information to servers via Credential Sync; and apply consistent security standards across operating systems such as Android, Tizen and Windows with Cross Platform. Samsung plans to expand Knox Matrix to cover its mobile devices, TVs and home appliances. Samsung continues to expand its user base through advanced data technology and multi-device connectivity experiences, leveraging data insights to drive research and bolster its competitive edge. Through these endeavors, the company is fueling the rapid advancement of personalized AI and placing increasingly innovative experiences at users' fingertips. In part three of this series, Samsung Newsroom will explore how various methods in Samsung's AI strategy meaningfully change users' lives.

[AI Leadership] ② Shaping Personalized AI With Data Intelligence and Device Connectivity

The age of personalized AI is here. Samsung Electronics offers safe, tailored AI experiences backed by user insights across its products -- from mobile devices and TVs to home appliances -- through continuous innovation in software and platform technology. Just as performance metrics and physical measurements are essential to designing customized workout routines for professional athletes, data plays a crucial role in creating personalized AI. As such, Samsung is prioritizing data intelligence research to transform vast amounts of data into meaningful and intuitive user experiences. Samsung Newsroom takes a closer look at how Samsung's advanced data research and innovative connectivity solutions are pioneering the era of personalized AI. A truly personalized AI experience starts with understanding the user. Data intelligence identifies a user's needs at specific moments based not only on historical device usage data but also on the user's present context. This enables appropriate services to be delivered in a timely manner. However, there are challenges -- for example, users don't hand in refined reports of their needs and wants; the matching of expected needs and potential services must be carried out in real time; and most of all, personal information must constantly be kept safe. As Samsung reaches consumers across nearly all daily touchpoints -- including work, entertainment, household chores, health and security -- the company has the unique opportunity to gain deep insights into user behaviors and preferences. In order to harness this potential, Samsung has strengthened its data technology capabilities by researching user data collected annually from hundreds of millions of devices and services -- all in strict compliance with internal and external regulations. As AI models develop a better understanding of users through data collection, processing and analysis, they can leverage retrieval-augmented generation (RAG) to deliver more personalized services for different contexts. By using technologies to connect reliable, logic-based knowledge bases to large language models (LLMs), these AI models access the latest, most reliable information and find the most suitable answers. As Samsung focuses on technologies that connect data to refine personalized AI experiences, a key question is how can such vast and complex data be managed more effectively and tailored precisely to individual needs? The answer, in part, lies in knowledge graphs. A knowledge graph is a knowledge representation technology that organizes related information in an interconnected graph format, making it easily interpretable for both humans and computers. By defining individual entities within the data and linking them, their relationship can be represented as a "triple" in the form of "subject -- predicate -- object." For example, "the capital of South Korea is Seoul" can be represented in the following graph, "South Korea -- capital -- Seoul." Various types of knowledge such as people, objects, times and places can be structured in a highly refined manner by connecting numerous entities in this triple format. Unlike traditional relational databases that fill tables with information, knowledge graphs effectively store data and quickly retrieve information or new inferences as needed. Samsung is actively advancing research in knowledge graphs. While earlier forms of data usage were limited to individual apps, this technology allows for free data search and utilization across app or service boundaries -- enabling a hyper-personalized experience as if the device were tailored exclusively to the user. When combined with Samsung's on-device AI, knowledge graphs allow users to experience highly customized AI services while protecting sensitive personal data from external exposure. This technology is expected to be applied across various products and devices. The key to implementing knowledge graphs is the ability to quickly find specific answers from information represented in the graph. Converting constantly changing real-world data into graphs and efficiently extracting information requires complex computations -- and as the graphs grow, rapid information retrieval becomes more challenging. To bolster its capabilities in this area, Samsung acquired Oxford Semantic Technologies in July. Oxford Semantic Technologies, a U.K.-based startup renowned for its knowledge graph technology, specializes in optimizing data processing and advanced inference to facilitate swift understanding and precise extraction of information from knowledge graphs. Samsung has collaborated with Oxford Semantic Technologies on graph databases and ontologies since 2018, and the recent acquisition is anticipated to create synergy in personalized AI research across Samsung's product ecosystem. The company plans to develop applications that offer valuable experiences to consumers and explore new research avenues in various areas including the integration of generative AI and knowledge graphs. Samsung is rapidly incorporating personalized AI features powered by data intelligence across a wide range of products and services to enrich users' daily lives. Digital healthcare is one example. The Galaxy Watch7 and Galaxy Ring comprehensively analyze user health data including sleep, exercise and heart rate to offer an Energy Score via the Samsung Health app. Going beyond simple data measurement, this analysis provides an easy-to-understand numeric summary of a user's daily health status and personalized insights for individual activities. By researching the weighted importance of each factor in the Energy Score based on age and gender, Samsung has developed a more customized approach to health management. The entertainment experience has also been enhanced through data-driven insights. In the U.S., Gaming Hub -- Samsung's game platform available on its smartphones -- uses explainable AI (XAI) to offer personalized game recommendations. Leveraging a model of the user's preferences, this technology not only recommends games but also explains the reasoning behind each suggestion to help users select the games that suit them best. Personalized AI will evolve as more devices connect with each other and acquire usage data from users' daily lives. At Samsung Developer Conference 2024 (SDC24) in October, Samsung unveiled Home Insight -- a service that allows users to manage and control their smart home through SmartThings. The feature analyzes users' lifestyle patterns, device usage history and home conditions to provide real-time reports and tailored recommendations such as turning off devices or utilizing specific features based on different situations. In addition, Samsung has a personalized AI feature to support the well-being and safety of family members in need. Launched in June, SmartThings Family Care allows users to remotely monitor family members and take any necessary actions through SmartThings-connected devices and location-based data. The company plans to expand these AI-connected capabilities to health devices, supporting family health in areas like sleep and diet. Samsung is advancing technology that allows devices to recognize users and provide seamless, personalized experiences across all connected devices. For example, the company is planning to enable users who have large text mode activated on their smartphones to automatically apply the setting to other devices with a single voice command. Additionally, Samsung is exploring functions that use sensors and devices within the home to detect a user's location and adjust lighting, temperature and humidity according to individual preferences. Security is a fundamental requirement for delivering safe, personalized AI. To ensure the protection of personal information and address biases in AI systems, a multi-faceted approach is needed -- including improving data processing and model training processes and implementing a rigorous verification process for outputs. When collecting internal and external data for AI model training, Samsung performs data pre-processing to check and filter for privacy violations. Additionally, the company is strengthening its safety verification of AI outputs by addressing risks related to harm, bias, privacy and jailbreak vulnerabilities. Samsung's Knox Matrix further elevates security in a multi-device connected environment. Using blockchain technology, connected devices can monitor each other for security threats through Trust Chain; securely share user data by transmitting only encrypted information to servers via Credential Sync; and apply consistent security standards across operating systems such as Android, Tizen and Windows with Cross Platform. Samsung plans to expand Knox Matrix to cover its mobile devices, TVs and home appliances. Samsung continues to expand its user base through advanced data technology and multi-device connectivity experiences, leveraging data insights to drive research and bolster its competitive edge. Through these endeavors, the company is fueling the rapid advancement of personalized AI and placing increasingly innovative experiences at users' fingertips. In part three of this series, Samsung Newsroom will explore how various methods in Samsung's AI strategy meaningfully change users' lives.

[AI Leadership] ① Revolutionizing Everyday Devices Using On-Device AI

AI is rapidly becoming an integral part of daily life. Samsung Electronics' "AI for All" vision focuses on providing users with enriching AI experiences throughout their daily lives by setting a new standard for next-generation devices with AI-powered mobile devices, TVs and home appliances. Central to Samsung's AI innovations is on-device AI. This technology enables AI to operate independently within the device and does not require a server or the cloud. Users benefit from quick AI response times without needing a network connection, reducing concerns over personal data leakage. On-device AI has now evolved beyond simple functions to handle demands requiring vast amounts of data -- such as generative AI -- using only the device's internal resources. Samsung Newsroom explores how Samsung is leading the world in on-device AI innovations. Citing the need for speed and security, much of the tech industry has focused on running complex generative AI in an on-device environment. With long-term investments that date back more than a decade, Samsung has already customized AI features for many of its devices and positioned itself front and center in providing on-device AI experiences for everyday life. Samsung's Galaxy AI, for example, offers on-device capabilities across the company's latest mobile devices and tablets. Now supporting a total of 20 languages, Galaxy AI enables communication without language barriers including real-time conversation interpretation as well as message and web page translation. For TVs, Samsung leverages its expertise as a global leader in the market to train AI models. Since 2020, the company has continuously enhanced its TV-specific processor with a built-in NPU (neural processing unit). The 2024 Neo QLED 8K model's NQ8 AI Gen3 processor features 512 neural networks for enhanced image and sound quality. By analyzing and modifying pixels, frames and sound sources, the processor delivers superior upscaling, smooth motion and clear dialogue for a seamless viewing experience in all situations. The key to on-device AI is minimizing model size while maintaining performance. To achieve this, Samsung has focused on efficient implementation while utilizing specialized AI training data tailored to specific tasks. As AI technology advances and data processing requirements increase, model optimization has become crucial. In other words, high-performance AI models must be able to operate efficiently within the limits of the devices' resources -- including their processors, memories and batteries -- while retaining performance levels and reliability for daily use. Key technologies for this include model compression, hardware optimization and data processing acceleration. Samsung has secured various technologies in the field of model compression to reduce the size of AI models. The company has succeeded in developing light and fast AI models through techniques like quantization, which enhances response speed by simplifying algorithms and optimizing computation processes; pruning, which removes non-essential elements of a larger model; and knowledge distillation, which transfers knowledge from large models to smaller models. Samsung also continues to innovate in hardware optimization and data processing acceleration to swiftly and efficiently run AI. For example, flash utilization technology partitions large AI models and significantly reduces memory usage. Additionally, the company has developed patented technology that is expected to assist quick inference on low-end devices without an NPU to broaden AI applications across various products. Further research is underway on increasing inference speeds with speculative decoding, a technology that predicts AI model outcomes, and enhancing computing power by running various hardware simultaneously. With expertise spanning hardware, software, components and end products, Samsung is spearheading on-device AI innovation from research and development to product implementation. From a device perspective, Samsung's market leadership in mobile devices, TVs, home appliances and more represents its excellence in both hardware and software. Samsung integrates AI into its own devices, allowing the company to leverage both in-house development and open collaboration with industry partners to create hardware-optimized AI models. Samsung's expertise also includes system software to bridge hardware and application software. For example, the Tizen operating system and the NPUs on Samsung TVs power on-device AI for a smarter, more enhanced viewing experience. The company also provides developers with Vision AI and Language AI SDKs, as well as machine learning APIs to facilitate AI model training and inference. Samsung Research, the company's advanced research and development hub, is focused on enhancing competitiveness by utilizing specialized expertise from its global network of labs -- from AI model structure development and model compression in the U.K. and U.S. to creating AI acceleration solutions in India and Poland. From a components perspective, Samsung has endlessly driven progress in NPU performance as a leading manufacturer of semiconductors and plans to continue working with its partners to develop new ways of utilizing on-device AI. With its on-device AI capabilities expected to expand across more products and services, Samsung is pioneering groundbreaking changes that will see AI technologies transform daily life. In part two of this series, Samsung Newsroom will explore the company's innovations in personalized AI.

[AI Leadership] ① Revolutionizing Everyday Devices Using On-Device AI

AI is rapidly becoming an integral part of daily life. Samsung Electronics' "AI for All" vision focuses on providing users with enriching AI experiences throughout their daily lives by setting a new standard for next-generation devices with AI-powered mobile devices, TVs and home appliances. Central to Samsung's AI innovations is on-device AI. This technology enables AI to operate independently within the device and does not require a server or the cloud. Users benefit from quick AI response times without needing a network connection, reducing concerns over personal data leakage. On-device AI has now evolved beyond simple functions to handle demands requiring vast amounts of data -- such as generative AI -- using only the device's internal resources. Samsung Newsroom explores how Samsung is leading the world in on-device AI innovations. Citing the need for speed and security, much of the tech industry has focused on running complex generative AI in an on-device environment. With long-term investments that date back more than a decade, Samsung has already customized AI features for many of its devices and positioned itself front and center in providing on-device AI experiences for everyday life. Samsung's Galaxy AI, for example, offers on-device capabilities across the company's latest mobile devices and tablets. Now supporting a total of 20 languages, Galaxy AI enables communication without language barriers including real-time conversation interpretation as well as message and web page translation. For TVs, Samsung leverages its expertise as a global leader in the market to train AI models. Since 2020, the company has continuously enhanced its TV-specific processor with a built-in NPU (neural processing unit). The 2024 Neo QLED 8K model's NQ8 AI Gen3 processor features 512 neural networks for enhanced image and sound quality. By analyzing and modifying pixels, frames and sound sources, the processor delivers superior upscaling, smooth motion and clear dialogue for a seamless viewing experience in all situations. The key to on-device AI is minimizing model size while maintaining performance. To achieve this, Samsung has focused on efficient implementation while utilizing specialized AI training data tailored to specific tasks. As AI technology advances and data processing requirements increase, model optimization has become crucial. In other words, high-performance AI models must be able to operate efficiently within the limits of the devices' resources -- including their processors, memories and batteries -- while retaining performance levels and reliability for daily use. Key technologies for this include model compression, hardware optimization and data processing acceleration. Samsung has secured various technologies in the field of model compression to reduce the size of AI models. The company has succeeded in developing light and fast AI models through techniques like quantization, which enhances response speed by simplifying algorithms and optimizing computation processes; pruning, which removes non-essential elements of a larger model; and knowledge distillation, which transfers knowledge from large models to smaller models. Samsung also continues to innovate in hardware optimization and data processing acceleration to swiftly and efficiently run AI. For example, flash utilization technology partitions large AI models and significantly reduces memory usage. Additionally, the company has developed patented technology that is expected to assist quick inference on low-end devices without an NPU to broaden AI applications across various products. Further research is underway on increasing inference speeds with speculative decoding, a technology that predicts AI model outcomes, and enhancing computing power by running various hardware simultaneously. With expertise spanning hardware, software, components and end products, Samsung is spearheading on-device AI innovation from research and development to product implementation. From a device perspective, Samsung's market leadership in mobile devices, TVs, home appliances and more represents its excellence in both hardware and software. Samsung integrates AI into its own devices, allowing the company to leverage both in-house development and open collaboration with industry partners to create hardware-optimized AI models. Samsung's expertise also includes system software to bridge hardware and application software. For example, the Tizen operating system and the NPUs on Samsung TVs power on-device AI for a smarter, more enhanced viewing experience. The company also provides developers with Vision AI and Language AI SDKs, as well as machine learning APIs to facilitate AI model training and inference. Samsung Research, the company's advanced research and development hub, is focused on enhancing competitiveness by utilizing specialized expertise from its global network of labs -- from AI model structure development and model compression in the U.K. and U.S. to creating AI acceleration solutions in India and Poland. From a components perspective, Samsung has endlessly driven progress in NPU performance as a leading manufacturer of semiconductors and plans to continue working with its partners to develop new ways of utilizing on-device AI. With its on-device AI capabilities expected to expand across more products and services, Samsung is pioneering groundbreaking changes that will see AI technologies transform daily life. In part two of this series, Samsung Newsroom will explore the company's innovations in personalized AI.