TinyML device shipments to reach 1.2 bn in 2022

In its new whitepaper, 70 Technology Trends That Will—and Will Not—Shape 2022, ABI Research analysts identify 35 trends that will shape the technology market and 35 others that, although attracting huge amounts of speculation and commentary, are less likely to move the needle over the next twelve months. “The fallout from COVID-19 prevention measures, the process of transitioning from pandemic to endemic disease, and global political tensions weigh heavily on the coming year’s fortunes. This whitepaper is a tool for our readers to help shape their understanding of the key critical trends that look set to materialize in 2022 as the world begins to emerge from the shadow of COVID-19. It also highlights those much-vaunted trends that are less likely to have meaningful impact in 2022,” says Stuart Carlaw, Chief Research Officer at ABI Research.

What will happen in 2022:
The proliferation of TinyML
TinyML is already showing massive potential and will be on the path to becoming the largest segment of the edge Machine Learning (ML) market by shipment volume. ABI Research forecasts total shipments of 1.2 billion devices with TinyML chipsets in 2022. This means more devices will be shipped with TinyML chipsets, as compared to those with edge ML chipsets. In addition, the proliferation of ultra-low-power ML applications means more brownfield devices will also be equipped with ML models for on-device anomaly detection, condition monitoring, and predictive maintenance.

What won’t happen in 2022:
Single regulation to govern AI
Following in the footsteps of the EU and China, more and more countries are preparing their regulations to govern the design, development, and deployment of AI. However, ABI Research believes that no nation will rely on a single regulation to govern AI. Instead, countries will develop guidelines, standards, and regulations to oversee various aspects of AI, including data collection, storage, model transparency, future update, and legal responsibilities. A good example will be the EU, which relies on General Data Protection Regulation (GDPR), ethics governance framework, risk-based legislative framework, and conformity assessments to govern AI.
CT Bureau