TinyML Device Shipments to Grow to 2.5 Billion in 2030, Up From 15 Million in 2020

OYSTER BAY, N.Y., May 13, 2021 /PRNewswire/ -- Between 2021 and 2026, the number of IoT connections will nearly triple to 23.6 billion. Each new connection represents an opportunity to leverage Artificial Intelligence (AI) and Machine Learning (ML), and TinyML technology will be pivotal in seizing that opportunity.

In its new whitepaper, TinyML: The Next Big Opportunity in Tech, global tech market advisory firm ABI Research identifies the six key benefits of TinyML, offers strategic recommendations to vendors and end users, and explains why the TinyML market will grow from 15.2 million shipments in 2020 to 2.5 billion in 2030.

"The proliferation and democratization of AI has fueled the growth of Internet of Things (IoT) analytics. Data collected from IoT devices are used to train Machine Learning (ML) models, generating valuable new insights into the IoT overall. These applications require powerful and expensive solutions that rely on complex chipsets," explains Lian Jye Su, AI & ML Principal Analyst at ABI Research. At the same time, edge AI chipsets have introduced AI to myriad end points, including mobile devices, automobiles, smart home speakers, and wireless cameras. "However, these devices are often too underpowered to make use of all the data flowing across them and struggle to support high computing performance and high data throughput, causing latency issues, which is a death knell for AI," Su says.

TinyML chipsets aim to solve the issues of both cost and power efficiency. TinyML enables the performance of data analytics on low-powered hardware with low processing power and small memory size, aided by software designed for small-sized inference workloads. It has the potential to revolutionize the future of the IoT.

The proliferation of TinyML will lead to the expansion of edge AI beyond traditional key markets. "By bringing AI analytics beyond machine vision, more end users can benefit from smart connected sensors and IoT devices based on soundwaves, temperature, pressure, vibration, and other data sources," Su says. This growth offers tangible and important benefits such as data privacy, high interconnectivity and interaction of various components, high-energy efficiency, small chipset footprint, functional safety, and security concerns, and overcoming network bandwidth challenges.

"Given that very edge AI exists in a slightly more specialized environment as compared to the general edge AI, end users must prepare their equipment, connectivity infrastructure, and internal expertise to capture the real benefits of very edge AI. Knowing the user demand and requirements for TinyML, TinyML AI chipset vendors need to differentiate through key use cases and focus on software and services," Su concludes.

To learn more about the potential of TinyML chipsets, the key TinyML benefits, and ABI Research's strategic recommendations for vendors and end users, download TinyML: The Next Big Opportunity in Tech. You are welcome to share this link with your readers.

About ABI Research
ABI Research provides actionable research and strategic guidance to technology leaders, innovators, and decision makers around the world. Our research focuses on the transformative technologies that are dramatically reshaping industries, economies, and workforces today. ABI Research's global team of analysts publish groundbreaking studies often years ahead of other technology advisory firms, empowering our clients to stay ahead of their markets and their competitors.

ABI Research提供开创性的研究和战略指导，帮助客户了解日新月异的技术。 自1990年以来，我们已与全球数百个领先的技术品牌，尖端公司，具有远见的政府机构以及创新的贸易团体建立了合作关系。 我们帮助客户创造真实的业务成果。 

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SOURCE ABI Research

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