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Patents are always a pretty intriguing thing to follow in the tech industry – sometimes they represent ideas and products that will never see the light of day, but there are occasions when they give clues to future versions. A recently published US patent application could be the latter, as it relates to technology that could allow Nintendo to improve the visuals of its hardware.
Opened on March 25, 2020 and publicly released yesterday (September 30), the app is titled “Machine Learned Image Conversion Systems and Methods”, and while the initial language can be a puzzle, it does. This is essentially a similar idea to NVIDIA’s DLSS. It is the abbreviation for Deep Learning Super Sampling in the case of NVIDIA, which works on some of its GPUs to increase image resolution. and quality in real time, while being remarkably efficient and ensuring that the graphics card is less strained. It’s impressive technology, and it’s been the focus of a lot of talk about how Nintendo could produce a new Switch-style handheld device that produces higher resolution visuals while working with low power output. Digital Foundry explored this in detail.
What makes this app intriguing is that Nintendo is clearly exploring this internally – one named party on the app is Alexandre Delattre, who is co-founder of Nintendo European Research and Development. It is also recognized in the ‘introduction’ of the patent that this is an area explored throughout the industry:
Machine learning can give computers the ability to “learn” a specific task without specifically programming the computer for that task. One type of machine learning system is called convolutional neural networks (CNN) – a class of deep learning neural networks. Such networks (and other forms of machine learning) can be used, for example, to help automatically recognize if a cat is in a photo. Learning is done by using thousands or millions of photos to “train” the model to recognize when a cat is in a photo. While this can be a powerful tool, the processing resulting from using a trained model (and training the model) can still be computationally expensive when deployed in a real-time environment.
Image up-conversion is a technique that allows the conversion of images produced in a first resolution (for example, 540p resolution or 960 × 540 with 0.5 megapixels) to a higher resolution (for example, 1080p resolution , 1920 × 1080, with 2.1 megapixels). This process can be used to display first resolution images on a higher resolution screen. So, for example, a 540p image can be displayed on a 1080p television and (depending on the nature of the upscaling process) can be displayed with increased graphic fidelity compared to if the 540p image were displayed directly with a traditional mode ( eg linear) upscaling on a 540 television. Different image upscaling techniques can present a trade-off between speed (eg how long the process takes to convert a given image) and the quality of the converted image. ascending. For example, if an upscaling process is performed in real time (eg, during a video game), then the image quality of the resulting upconverted image may suffer.
Accordingly, it will be understood that new and improved techniques, systems and methods are continually in demand in these fields of technology.
Ultimately, it shouldn’t come as a surprise that Nintendo is looking at scaling through machine learning, as it’s likely to be a vital factor if the company chooses to keep a form factor. Switch style while providing greater graphics fidelity in the future. It is also interesting to know if Nintendo will still use NVIDIA technology in its future devices; if he is developing his own solution, he may not need NVIDIA’s DDSL tools. Of course, depending on what you believe and who you believe, there are reports that “4K” development units are already in the wild.
Let us know what you think in the comments!
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