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  • AI-Powered mobile
    graphics revolution
    AI-Powered mobile
    graphics revolution
    AI-Powered mobile graphics revolution
    Upward‑angled view of Samsung’s office building, featuring a modern glass façade against a clear blue sky.
Mobile graphics is entering a new era. As high-resolution textures, advanced shading, and ray tracing become mainstream, demand for GPU performance continues to rise, while power and thermal constraints remain inherent to mobile devices. Exynos addresses this challenge with AI-powered ENSS™, enabling advanced gaming technologies to operate efficiently on mobile devices. Mobile graphics is entering a new era. As high-resolution textures, advanced shading, and ray tracing become mainstream, demand for GPU performance continues to rise, while power and thermal constraints remain inherent to mobile devices. Exynos addresses this challenge with AI-powered ENSS™, enabling advanced gaming technologies to operate efficiently on mobile devices. Mobile graphics is entering a new era. As high-resolution textures, advanced shading, and ray tracing become mainstream, demand for GPU performance continues to rise, while power and thermal constraints remain inherent to mobile devices. Exynos addresses this challenge with AI-powered ENSS™, enabling advanced gaming technologies to operate efficiently on mobile devices.

What is ENSS™? What is ENSS™? What is ENSS™?

ENSS™ (Exynos Neural Super Sampling) is an AI-driven rendering optimization technology integrated into the Xclipse, the Exynos GPU.

In high-resolution and high-refresh-rate environments, rendering at native resolution requires intensive pixel shading, texture sampling, and lighting calculations, leading to a significant increase in computational workload and power consumption. To alleviate this structural burden, ENSS™ strategically lowers the internal rendering resolutions and combines NSS (Neural Super Sampling), an AI-based resolution reconstruction technology, with NFG (Neural Frame Generation), an AI-driven intermediate frame generation technology. Through this integrated architecture, ENSS™ balances computational efficiency and visual smoothness, making high-fidelity gaming experiences sustainable within strict mobile power constraints.

ENSS™ (Exynos Neural Super Sampling) is an AI-driven rendering optimization technology integrated into the Xclipse, the Exynos GPU.

In high-resolution and high-refresh-rate environments, rendering at native resolution requires intensive pixel shading, texture sampling, and lighting calculations, leading to a significant increase in computational workload and power consumption. To alleviate this structural burden, ENSS™ strategically lowers the internal rendering resolutions and combines NSS (Neural Super Sampling), an AI-based resolution reconstruction technology, with NFG (Neural Frame Generation), an AI-driven intermediate frame generation technology. Through this integrated architecture, ENSS™ balances computational efficiency and visual smoothness, making high-fidelity gaming experiences sustainable within strict mobile power constraints.

ENSS™ (Exynos Neural Super Sampling) is an AI-driven rendering optimization technology integrated into the Xclipse, the Exynos GPU.

In high-resolution and high-refresh-rate environments, rendering at native resolution requires intensive pixel shading, texture sampling, and lighting calculations, leading to a significant increase in computational workload and power consumption. To alleviate this structural burden, ENSS™ strategically lowers the internal rendering resolutions and combines NSS (Neural Super Sampling), an AI-based resolution reconstruction technology, with NFG (Neural Frame Generation), an AI-driven intermediate frame generation technology. Through this integrated architecture, ENSS™ balances computational efficiency and visual smoothness, making high-fidelity gaming experiences sustainable within strict mobile power constraints.

Futuristic sci-fi soldier wearing high-tech heavy armor and a white helmet with a dark visor, standing with a tactical squad.

Neural Super Sampling Neural Super Sampling Neural Super Sampling

An Image rendered at a lower internal resolution being upscaled to near-native visual quality through Neural Super Sampling

NSS (Neural Super Sampling) is an AI-based upscaling technology that reconstructs images rendered at a lower internal resolution to near-native visual quality.

In mobile environments, maintaining native resolution while enabling advanced graphical effects such as ray tracing significantly increases GPU load and power consumption. NSS reduces pixel processing demand by lowering the internal rendering resolution, while leveraging a trained neural network to precisely restore edge sharpness and texture detail through AI inference. This approach preserves ray tracing effects while delivering visual quality comparable to native resolution, enabling improved performance and smoother gameplay.

NSS (Neural Super Sampling) is an AI-based upscaling technology that reconstructs images rendered at a lower internal resolution to near-native visual quality.

In mobile environments, maintaining native resolution while enabling advanced graphical effects such as ray tracing significantly increases GPU load and power consumption. NSS reduces pixel processing demand by lowering the internal rendering resolution, while leveraging a trained neural network to precisely restore edge sharpness and texture detail through AI inference. This approach preserves ray tracing effects while delivering visual quality comparable to native resolution, enabling improved performance and smoother gameplay.

NSS (Neural Super Sampling) is an AI-based upscaling technology that reconstructs images rendered at a lower internal resolution to near-native visual quality.

In mobile environments, maintaining native resolution while enabling advanced graphical effects such as ray tracing significantly increases GPU load and power consumption. NSS reduces pixel processing demand by lowering the internal rendering resolution, while leveraging a trained neural network to precisely restore edge sharpness and texture detail through AI inference. This approach preserves ray tracing effects while delivering visual quality comparable to native resolution, enabling improved performance and smoother gameplay.

Neural Frame Generation Neural Frame Generation Neural Frame Generation

NFG (Neural Frame Generation) enhances FPS by generating AI-based intermediate frames between rendered frames.

It analyzes motion vectors and optical flow information between consecutive frames computed by the GPU. Based on temporal data, the neural network predicts object trajectories and scene transitions to generate new intermediate frames. Rather than duplicating existing frames, NFG reconstructs them with a comprehensive understanding of object-level motion and temporal continuity. This method minimizes distortion and ghosting during rapid camera movements or complex action scenes, ensuring stable visual consistency and enhanced smoothness without proportionally increasing rendering workload.

NFG (Neural Frame Generation) enhances FPS by generating AI-based intermediate frames between rendered frames.

It analyzes motion vectors and optical flow information between consecutive frames computed by the GPU. Based on temporal data, the neural network predicts object trajectories and scene transitions to generate new intermediate frames. Rather than duplicating existing frames, NFG reconstructs them with a comprehensive understanding of object-level motion and temporal continuity. This method minimizes distortion and ghosting during rapid camera movements or complex action scenes, ensuring stable visual consistency and enhanced smoothness without proportionally increasing rendering workload.

NFG (Neural Frame Generation) enhances FPS by generating AI-based intermediate frames between rendered frames.

It analyzes motion vectors and optical flow information between consecutive frames computed by the GPU. Based on temporal data, the neural network predicts object trajectories and scene transitions to generate new intermediate frames. Rather than duplicating existing frames, NFG reconstructs them with a comprehensive understanding of object-level motion and temporal continuity. This method minimizes distortion and ghosting during rapid camera movements or complex action scenes, ensuring stable visual consistency and enhanced smoothness without proportionally increasing rendering workload.

AI generating intermediate frames between rendered frames through Neural Frame Generation to increase FPS
Fluid neon purple and blue energy particles flowing as an abstract representation of technology and data
ENSS™ elevates the mobile gaming experience by integrating resolution reconstruction and frame generation. It delivers sharp visual quality and smooth frame rates within the power constraints of mobile devices. Samsung will continue to advance ENSS™ technology, leading next-generation AI-driven rendering innovation that overcomes the physical limits of mobile GPU processing. ENSS™ elevates the mobile gaming experience by integrating resolution reconstruction and frame generation. It delivers sharp visual quality and smooth frame rates within the power constraints of mobile devices. Samsung will continue to advance ENSS™ technology, leading next-generation AI-driven rendering innovation that overcomes the physical limits of mobile GPU processing. ENSS™ elevates the mobile gaming experience by integrating resolution reconstruction and frame generation. It delivers sharp visual quality and smooth frame rates within the power constraints of mobile devices. Samsung will continue to advance ENSS™ technology, leading next-generation AI-driven rendering innovation that overcomes the physical limits of mobile GPU processing.

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