While NPUs are established for TinyML in Personal and Work
Devices, they have only recently started to make inroads in IoT
applications
LONDON, July 24, 2024 /PRNewswire/ --
Embedded chipset vendors are increasing their focus on Neutral
Processing Units (NPUs) for Internet of Things (IoT) applications
thanks to the architecture's efficient execution of neural network
workloads. NPUs will take an increasing share of overall shipment
numbers at the expense of the established Microcontrollers (MCUs)
as implementers seek ever greater insights and intelligence at the
far edge. According to ABI Research, a global technology
intelligence firm, this will contribute to chipset revenues from
AI-dedicated silicon for IoT-focused applications reaching over
US$7.3 billion by 2030.
"NPUs for TinyML applications in Personal and Work Devices
(PWDs) are already well established. However, they are still
nascent outside of this device vertical, and major vendors ST
Microelectronics, Infineon, and NXP Semiconductors are only just
introducing this type of ASIC to their embedded
portfolios," says Paul Schell,
Industry Analyst at ABI Research. "By screening PWDs, we provided
greater insight into our modeling for IoT applications, which spans
15 verticals, including the most significant, namely Smart Home and
Manufacturing."
On the software side, comprehensive MLOps toolchains are now
table stakes for vendors big and small, including start-ups like
Syntiant, GreenWaves, Aspinity, and Innatera. As with bigger form
factors, the investment into the software offering often matches
hardware R&D, which has paid off for vendor Eta Compute in
their partnership with NXP to license their Aptos software
platform. Such innovations also democratize the deployment of
TinyML by reducing the need for in-house data science talent.
Including highly performant architectures like NPUs and some
FPGAs into embedded devices will expand the offering of
applications able to run on-device from object detection to simple
object classification for machine vision use cases, as well as some
NLP for audio-based analytics. "Along with the trend in larger edge
form factors such as PCs and gateways, this will contribute to AI's
scalability by reducing networking costs and the reliance on cloud.
As such, we expect the TinyML market to grow as it capitalizes on
these innovations, spurred largely by major industrial sites
upgrading their IoT deployments, the growing intelligence of
vehicles, and smart home devices."
These findings are from ABI Research's Artificial Intelligence
and Machine Learning: TinyML market data report. This report
is part of the company's AI & Machine
Learning research service, which includes research, data, and
ABI Insights.
About ABI Research
ABI Research is a global technology intelligence firm uniquely
positioned at the intersection of technology solution providers and
end-market companies. We serve as the bridge that seamlessly
connects these two segments by providing exclusive research and
expert guidance to drive successful technology implementations and
deliver strategies proven to attract and retain customers.
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SOURCE ABI Research