Videogames have always existed in a weird place between high art and cutting-edge technology. Their consumer-facing nature has always forced them to be both eye-catching and affordable, while remaining tasteful enough to sit on retail shelves (both physical and digital). Running in real-time is a necessity, so it’s not as if game creators are able to pre-render the incredibly complex visuals found in feature films. These pieces of software constantly ride the line between exploiting the hardware of the future while supporting the past where their true user base resides. Each pixel formed and every polygon assembled comes at the cost of a finite supply of floating point operations today’s pieces of silicon can deliver. Compromises must be made.

Often one of the first areas in games that fall victim to compromise are environmental model textures. Maintaining a viable framerate is paramount to a game’s playability, and elements of the background can end up getting pushed to “the background”. The resulting look of these environments is somewhat more blurry than what they would have otherwise been if artists were given more time, or more computing resources, to optimize their creations. But what if you could update that ten-year-old game to take advantage of today’s processing capabilities and screen resolutions?

NVIDIA is currently using artificial intelligence to revise textures in many classic videogames to bring them up to spec with today’s monitors. Their neural network is able fundamentally alter how a game looks without any human intervention. Is this a good thing?

“So you take this neural network, you give it a whole bunch of examples, you tell it what is the input and what is the exact expected output; and you give it a chance to try, and try, and try again trillions and trillions of times on a super computer. Eventually it trains, and does this amazing thing.”

– Jensen Huang, CEO of NVIDIA

Artificial Intelligence, Revisionist History

We all stopped being able to count on Moore’s Law as transistors pushed towards 10nm dies, and NVIDIA knew this better than most. Alongside the announcement of their RTX series of GPUs the company stated that they would leverage neural network technology to boost overall performance of their cards. By feeding this neural network thousands of game screenshots taken at a higher resolution than the GPU can render natively, their AI model is able to learn how to display the higher quality imagery with no change to the on-board processing power. Their press release called this process “AI Up-Res”.

AI Up-Res is essentially a hands-off approach to increasing the overall resolution of model textures in games … which is exactly the problem. The traditional method of increasing a game’s resolution was to port a game to a newer, more powerful platform and have digital artists create new textures. Regardless of which development team performs the update process, there is the back-and-forth approval process where people intimately familiar with the game make decisions regarding its artistic direction. These type of projects additionally serve as …read more

Source:: Hackaday