Intel is using machine learning to make GTA V more realistic
Intel is using machine learning to make GTA V more realistic

Intel has a new machine learning project called Enhanced Photo Reality Enhancement which can take Grand Theft Auto: San Andreas into realism.

Grand Theft Auto: One of the most impressive things about San Andreas is the distance between Grand Theft Auto: San Andreas and real life in Los Angeles and Southern California.

Intel researchers have developed techniques that use machine learning for play to impart extraordinary realism.

This method not only uses natural colors, but also improves reflections and changes the slip of the road structure. The overall lively look of GTA V is complemented by other fine features.

Visual upgrades require a new way to improve AI.

While the concept of using real-world snapshots to control algorithms is not new, researchers have found that current methods are generally unstable or very slow.

Usually, there is a big gap between the hardware used to train the AI ​​and the game scene.

The new method captures similar shape corrections to provide better parameters for optimization, for example for cars and people, while maintaining a relatively high frame rate.

Although Intel scientists have found their method to be the strongest and most consistent of any AI-based system they have ever seen, the authenticity of the image still depends on its availability. some examples.

You need a lot of pictures to improve the interior scene and keep an eye on all aspects of GTA V upgrades.

Using the unoptimized GeForce RTX 3090 code for this high-end graphics card requires half a second of indicative time.

Intel researchers believe you can combine their machine learning system with game engines to speed things up that may represent the future of gaming graphics.

You'll find that games often rely on AI to create a realistic look that is otherwise difficult to achieve because technologies like NVIDIA's DLSS make 4K games more profitable.


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