NexOptic Joins Qualcomm Platform Solutions Ecosystem

- Collaboration with a Global Semiconductor Leader 
- Enables Easier and Faster Integration of ALIIS AI Software with Device Makers
- Qualcomm Snapdragon Mobile Platforms are Widely Used by Smartphone Manufacturers Worldwide

VANCOUVER, British Columbia, April 20, 2020 (GLOBE NEWSWIRE) -- NexOptic Technology Corp. (“NexOptic” or the “Company”) (TSX VENTURE: NXO) (OTCQB: NXOPF) (FSE: E3O1), an innovator in optics and Artificial Intelligence (AI), is pleased to announce that it has been selected to join the Qualcomm Platform Solutions Ecosystem. Joint initiatives have already begun, optimizing ALIIS for select Qualcomm Snapdragon mobile platforms with support from Qualcomm Technologies’ AI and camera solution experts.

Qualcomm Technologies, Inc. is the world’s leading wireless technology innovator and a driving force behind the development, launch, and expansion of 5G.

“I’m pleased with the level of enthusiasm shown by both sides during the formalization of our collaboration,” said Rich Geruson, Chairman of NexOptic. “Working with a global semiconductor leader like Qualcomm Technologies is a big achievement and the most efficient way for NexOptic to gain a major foothold in the mobile industry.”

While NexOptic and each original equipment manufacturer (OEM) retains control over the choice to license this technology, the optimized version of ALIIS will significantly reduce the integration cost to device makers making it easier and faster to implement NexOptic’s state-of-the-art solutions on Snapdragon-based commercial devices. In the future, global OEMs requiring premium imaging enhancement will have direct access to NexOptic’s industry-leading machine learning imaging solutions optimized for use on select Snapdragon mobile platforms.

For more information on the Qualcomm Platform Solutions Ecosystem, please visit https://www.qualcomm.com/support/qan/software-accelerator-program/ 

About ALIIS

ALIIS (All Light Intelligent Imaging Solutions) delivers superior all light performance by learning a camera profile and optimally enhancing images and video in a fraction of a second using edge processing. The result is superior resolution and sharpness, dramatic reductions to image noise and motion-blur, noticeable enhancements to long-range image stabilization by enabling faster shutter speeds, and significantly reduced file and bandwidth requirements for storage or streaming applications.