AI-Powered Intelligent Edge flourishes and is powered by Snapdragon

While artificial intelligence was a buzzword occasionally used to describe new levels of machine or device automation, there is now no doubt that true machine learning and AI-based intelligence is having a substantial impact on more and more consumer, commercial and industrial devices. However, the AI ​​edge (or endpoint devices) has a unique set of requirements compared to AI in the data center or cloud. At the edge, strong low-latency (5G) connectivity is critical, as well as low power consumption and the ability to offer capable AI processing on-device, with as little reliance on cloud data centers as possible, in order to achieve latency and performance targets .

A major player driving the advancement of connected, intelligent AI technology is Qualcomm. The company has been innovating in this space for years and several generations of products now, so that it has shipped over 1.8 billion AI-enabled chips to date, if you consider the number of products it has shipped with an AI engine on board .

Measuring AI Performance – Enter MLPerf

Having recently submitted MLPerf results for its Snapdragon 8+ Gen 1 Mobile Platform SoC — demonstrating a notable performance lead in AI workloads such as natural language processing, image segmentation and object detection — Qualcomm continues to perform in the space by enabling more capable, smart mobile and edge devices, from smartphones to IoT, automotive and industrial automation.

MLPerf is a widely respected machine learning benchmark that emerged from MLCommons, a consortium of founding members that established a set of industry standard metrics for measuring machine learning performance in 2018. Since then, MLCommons and MLPerf have been adopted and contributed from almost all the big heavyweights, from Intel, AMD, NVIDIA and Arm, to Facebook, Google, Mediatek and many others such as Qualcomm.

As you can see above, with the exception of offline image classification, even Qualcomm’s previous generation Snapdragon 8 Gen 1 platform led the field for various smartphone AI workloads, and the Snapdragon 8+ Gen 1 platform is on present unmatched. .

Where Qualcomm AI lives

Beyond benchmarks, Snapdragon AI engines power a multitude of devices and platforms, ranging from less than 1 TOP compute for low-power functionality like wireless noise-cancelling headphones to more powerful devices like AR glasses, where AI helps hand and eye tracking in 6 DoF (6 degrees of freedom) projection and spatial awareness.

Upgraded in horsepower, Qualcomm’s Hexagon AI engine can also be found in Snapdragon 8cx Gen 3-powered laptops like Lenovo’s ThinkPad X13s, where it’s used for video conferencing with background blur, AI optimization, and noise and echo cancellation for feeds audio.

Robotics and industrial automation and monitoring are also big market opportunities for Qualcomm AI, where machine vision and real-time safety monitoring are keys to running factories smoothly and maintaining safe work environments for workers. However, perhaps one of the biggest opportunities for Qualcomm Snapdragon AI right now is the connected, software-defined smart car.

Here, Snapdragon Digital Chassis solutions with built-in AI engines power everything from infotainment systems to climate control, driver monitoring for safety, ADAS (Advanced Driver Assistance Systems) for self-driving functionality, lane detection, navigation and more.

You could say that Qualcomm’s AI engines are one of the best-kept secrets in the tech industry, because they feature so many of the company’s chips and provide a kind of unsung hero ability that allows for more intelligence, customization, and machine control.

As many others have noted, AI and machine learning permeate everything in electronics, and in fact it’s even now helping to design new chips. With Qualcomm’s long-standing heritage in AI development, low-power performance-per-watt leadership, and a rich set of developer tools and frameworks like the Qualcomm AI Stack, similarly Qualcomm’s AI engines and silicon solutions are powering more and more devices in connected, smart edge.

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