November 16 (Portaltic/EP) –
The next phone in the series OPPO FindX It will be one of the new devices that will have the advantages of the new processor Snapdragon 8 Gen 2 presented by Qualcomm this Tuesday at the Snapdragon Summit 2022.
The new chip, which commitment to higher performance and improved efficiencyis unified with OPPO technology by confirming that it will be one of the first manufacturers to have this processor in its Find X series. In addition, the ‘smartphone’ brand has worked jointly with Qualcomm Technologies from the first phase of the development of the next generation processor.
In this sense, the company has assured in a press release that users who use Find X will receive a jump into your video game experiences, as well as in the connectivity. “We are looking forward to expanding our cooperation with Qualcomm Technologies to redefine the smartphone experience and put more cutting-edge technology in the hands of millions of users around the world,” added OPPO Senior Vice President and Chief Product Officer Pete Lau.
On the other hand, OPPO has also highlighted the ray tracing technologyray tracing for mobiles, which it has developed together with Qualcomm and which makes it possible to display shades that offer great realism, reflections on curved surfaces and global illumination.
“This technology allows game developers to take full advantage of the ray trace quality of desktop computers and thus be able to enjoy a high-level gaming experience on mobile”, explained Qualcomm’s Vice President of Product Management, Ziad Asghar.
With this technology, the best mobile games will be able to work at constant 60 FPS. Furthermore, the efficiency of ray tracing rendering has been multiplied by five and has reduced CPU workload by 90 percent.
In the same way, the mobile company has valued the progress made together with Google and Qualcom to implement Google Vertex AI Neural Architecture Search (Google NAS) for the first time on a phone.
As reported by OPPO, this technology achieves a 27 percent reduction in target stop algorithm power and a reduction than 40 percent of the computational latency. Improvements that “will allow AI models to be trained with greater energy efficiency and hardware compatibility in a shorter period of time.”
