Shares

NTT Ltd, an IT infrastructure and services company, has announced a partnership with Qualcomm Technologies, to invest in and accelerate the development of the 5G device ecosystem to facilitate private 5G adoption, which is critical to powering AI at the edge.

As part of a multi-year engagement, NTT and Qualcomm Technologies will prioritize the development of 5G enabled devices to accelerate innovation with global enterprise customers. This is a catalyst in driving widespread enterprise adoption of private 5G. IDC estimates that this market will exceed $8 Billion by 2026. Qualcomm Technologies’ leadership in application specific semiconductors and 5G chipsets, combined with NTT’s leadership in private 5G, will strengthen its ecosystem, advance AI processing capabilities at the edge and spur innovation across industries.

NTT and Qualcomm Technologies will use their combined expertise to meet the need for 5G-enabled devices that support use cases, such as push-to-talk devices, augmented reality headsets, computer vision cameras and sensors at the edge across the manufacturing, automotive, logistics and other industries.

“This collaboration is truly an exciting one because we are answering the demand we’re hearing from our clients. Together with Qualcomm Technologies, we will strengthen the 5G ecosystem delivering the devices our customers require in a simple and cost-effective way,” Shahid Ahmed, Executive Vice President, New Ventures & Innovation at NTT Ltd. “By working with Qualcomm Technologies, we will further accelerate demand for private 5G across global industries.”

Mark Bidinger, President, Commercial & Industrial Segments & Channels at Schneider Electric. “NTT’s collaboration with Qualcomm represents a significant step forward in advancing private 5G adoption and meeting the unique demands of the Internet of Things and Machine Learning.”

Qualcomm Technologies and NTT will work together to deliver 5G-ready devices with Qualcomm Technologies’ 5G chipsets with AI models built in to enhance AI at the edge through various applications, such as image recognition, with capabilities ranging from counting items and identifying object characteristics to verifying workers wearing safety masks or hardhats (PPE).