Samsung's "AI + Everything" blueprint is rapidly advancing! Announcing the integration of generative AI into the best-selling televisions.

The South Korean tech giant Samsung Electronics Co. is expanding its presence in the field of artificial intelligence on smart TVs, smartphones, smartwatches, and smart glasses through the introduction of new AI-enhanced features branded as "Vision AI" for its high-end smart TV product line. This move is aimed at accelerating Samsung's ambitious goal of "AI integration in all things." In an official statement released during the pre-show event of the "CES International Consumer Electronics Show" in Las Vegas on Sunday, the company revealed that smart TV screens powered by their edge AI technology will be able to perform "online AI search" for information related to displayed content, such as identifying actors or specific products, real-time translation, and generating personalized background and main screen images. The built-in AI processor in the top-tier Samsung smart TV models will also analyze TV content to enhance colors and contrast, optimize audio, quickly navigate to pages users want to browse, movies they want to watch, or TV shows they want to see, and personalize smart TV functions based on user commands, similar to the latest version of Apple Inc.'s Siri voice assistant embedded with ChatGPT. SW Yong, Head of Samsung's Visual Display Business, stated in the official announcement, "Samsung believes that TVs are not just passive electronic devices for consumption but interactive intelligent partners that can adapt to all user needs." As the world's largest smartphone manufacturer for nearly two decades, Samsung has recently announced strategic collaborations with tech giants Microsoft Corporation and Alphabet Inc.'s Alphabet Inc. Class C to expand its "Vision AI" smartphone AI brand with more powerful AI capabilities provided by partners. This advancement is seen as a step towards realizing Samsung's vision of "AI everywhere." The company's AI roadmap aims to integrate generative AI technology into its smartphones, smart TVs, smartwatches, and other consumer electronic products, creating an array of AI products that cover every aspect of consumer electronics and ultimately achieve the goal of "AI integration in all things." At last year's CES, Samsung Electronics held a highly anticipated edge AI product launch at the CES 2024 exhibition under the theme "All for AI: Interconnectivity in the Age of Artificial Intelligence." The products launched by Samsung were all related to edge AI, such as AI TVs, AI refrigerators, AI washing machines, AI vacuum cleaners, and AI laptops. Edge AI is expected to be a core focus at CES 2025 With the emerging trend of AI integration in consumer electronics such as AI PCs and AI smartphones in 2024, the unstoppable trend of "AI + everything" has emerged. In the upcoming year, edge AI will be a major focus at the International CES, exploring how AI can be seamlessly integrated into consumer electronic products at the edge and penetrating deeply into people's daily lives. The advancement and development of new products in the most vital edge AI field, such as "AI humanoid Siasun Robot & Automation," are highly anticipated by global investors and tech enthusiasts. Wall Street analysts generally expect NVIDIA Corporation to showcase its latest strategy for humanoid Siasun Robot & Automation at CES 2025 and unveil the Jetson Thor platform designed specifically for humanoid Siasun Robot & Automation, closely related to NVIDIA Corporation's "Embodied AI" strategy. Qualcomm, the world's largest smartphone chip company, recently unveiled the new version of its Snapdragon processor, and its CEO Cristiano Amon stated in a recent interview that AI smartphones, which can run powerful artificial intelligence models, are expected to become widespread among global consumers in the next five years. As data centers deploy AI chips for parallel computing on a massive scale to meet the computational demands of enterprise and individual AI models, the trend of stronger AI models like o1-preview being integrated into consumer electronics terminals, including smartphones, PCs, humanoid Siasun Robot & Automation, electric vehicle software systems, and industrial production terminals, is inevitable. These powerful AI models will eventually be integrated into these devices and can call on cloud-based AI resources for immediate collaboration, known as edge AI. Currently, leading smartphone hardware manufacturers are embracing this breakthrough technology of AI models and are incorporating incredibly powerful AI models that can run offline inference into their new generation devices to create so-called "AI smartphones." Compared to general cloud-based AI models that rely solely on cloud computing resources, having a core local AI model at the edge while leveraging cloud AI resources can allow smartphone users to use products like ChatGPT more efficiently, quickly, securely, and efficiently. Additionally, with edge AI, users are likely to achieve more personalized "private AI assistants" that better meet their individual needs.An "all-in-one AI companion" similar to the movie "HER".In order to run AI large models on smartphones, some smartphone hardware manufacturers are exploring integrating dedicated AI processors. These proprietary AI chips are designed specifically for efficiently processing AI tasks, striving to improve computational efficiency and energy consumption ratio. Manufacturers are also striving to combine cloud computing and edge computing, completing certain complex AI processing tasks in the cloud, while real-time or sensitive tasks are processed locally. They are also exploring the use of model pruning, quantification, knowledge distillation, and lightweight architectures (such as MobileNet, TinyBERT, etc.) and other cutting-edge technologies to reduce the actual size and computational requirements of large models, making them suitable for running powerful AI large models smoothly on application devices terminals such as smartphones and PCs where training/inference computational resources are severely limited.