On-device machine learning opportunity sends chipset companies searching for gold at the end of the rainbow
Oct 18, 2017
Oyster Bay, New York - 18 Oct 2017: On-device machine learning (ML), aka edge processing and/or edge learning, is the fastest growing segment of AI, according to ABI Research, a leader in emerging technology intelligence. Announcements and early AI / ML-enabled device shipments in 2017 are sending the chipset companies scrambling to develop their own solutions and heavily invest in AI technologies now; somewhat in fear of not getting left behind as AI rockets beyond news headlines to both practical application and market interest.
While many of the announcements will not be seen in commercially available products for one to three years, “The momentum in the AI vendor hardware ecosystem and venture capital investments demonstrates how AI technologies are revolutionizing engagements between humans and machine systems at work and home,” says Jeff Orr, Research Director at ABI Research.
Semiconductor companies are rapidly taking a stance in support of edge devices with recent announcements made by Apple, ARM, CEVA, HiSilicon, Imagination, Intel Mobileye, Intel Movidius, Nvidia, and Qualcomm.
The Huawei P10 smartphone, Apple iPhone 8/8+, and upcoming Apple iPhone X are examples of consumer products that perform on-device machine learning. ABI Research forecasts that 34 million smartphones will utilize on-device learning in 2017. Other products with machine learning on-device this year include Bragi wireless earbuds and possibly the recently-announced Google Clips smart home camera.
Edge devices bring the functionality of the cloud closer to the data and the user. Benefits of performing learning on edge devices include application responsiveness and minimizing movement of sensitive data to the cloud.
Relevant statistics to support this trend:
- About 3% of active AI devices in 2017 will be done on-device, while the balance is in the cloud.
- In 2022, nearly 49% (2.7 billion units) of active AI-enabled devices will performing data learning on-device; the largest chunk of AI implementations.
These AI technologies are driving the major breakthroughs that enable safe and efficient driverless vehicles, give vision to machines, and the future of human-machine interfaces (HMI).
These findings are from ABI Research’s Artificial Intelligence and Machine Learning market data report. This report is part of the company’s AI and Machine Learning research service, which includes research, data, and analyst insights.
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