ABI Research Predicts 2.5 Billion TinyML Devices Within a Decade, Points to Open Source as a Driver
Edge AI explosion will be driven, the company claims, by organizations which "embrace open source."
Market advisory specialist ABI Research is bullish on the future of Tiny Machine Learning (tinyML), forecasting a future that will see shipments of tinyML chipsets reach 2.5 billion within the next decade — and it's the makers and tinkerers who are currently leading the way.
"Since AI is deployed to make immediate critical decisions such as quality inspection, surveillance, and alarm management, any latency within the system may result in machine stoppage or slowdown causing heavy damages or loss in productivity," explains Lian Jye Su, Principal Analyst at ABI Research, of the key issues that will drive tinyML adoption in industry. "Moving AI to the edge mitigates potential vulnerability and risks such as unreliable connectivity and delayed responses."
"At the moment most of these solutions are still in the early stages of commercial deployment in smart cities and smart manufacturing, mainly used for asset tracking and anomaly sensing, and yet to achieve large-scale adoption. While able to offer better processing capabilities, sensors with TinyML are often much more expensive. End users will also need to design and introduce a new set of procedures and protocols to leverage the information and insights derived from these sensors."
While commercial deployment may be in the early stages, the hacker, maker, and developer communities have been embracing tinyML with open arms: Numerous initiatives and products designed to democratize machine learning at the edge have already launched, from TinySpeech, Edge Impulse, and TensorFlow Lite to hardware like the Crazyflie AI-deck and the QuickFeather development board.
The key, ABI Research has found, will be less in the hardware that drives tinyML platforms and more in the community behind them: The research organization predicts success will come for companies which "developing their AI developer ecosystem or be part of existing ecosystems, embrace open source, and focus on articulating their unique selling points and target markets to end user."
ABI Research's full findings are available to the company's customers in the report Very Edge AI Chipset for TinyML Applications.