Embedded AI Market Trends

Key Emerging Trends in the Embedded AI Market

There have been several market characteristics that have emerged that drive demand for smart and autonomous products resulting into significant growth in embedded AI market in recent years.

The rise of Internet of Things (IoT) is one of the key market trends driving the growth in embedded AI market. With increasing numbers of connected devices and growing demands for real-time data analysis, there has been an increase in demand for embedded artificial intelligence solutions capable processing and analyzing data locally. Unlike a server based or cloud-based computing system where these decisions would be made at, edge computing contains intelligent IoT endpoints that can make decisions independently without relying on backhaul connection to a central site.

Additionally, there is a shift towards edge computing being observed in the market currently. It refers to carrying out data processing as well as analysis right from where they were obtained rather than sending it back to any centralized cloud or even a data center The importance played by Embedded AI in edge computing includes reduction latency performing complex tasks locally improving privacy/security among others. Consequently this factors has pushed industries such as automotive manufacturing health care as well as smart homes into adopting embedded AI solutions that require real-time and local data analysis.

Consequently, there is growing need for energy efficient embedded AI system. This can cause an increase in power consumption when the devices become more intelligent and autonomous since they require much processing power. Embedded AI technologies have been developed to deal with this problem by consuming less power while still ensuring high performance. As a result, Energy efficiency and environmental friendliness are now becoming important consideration in the design and development of embedded AI since the energy required to run these machines is very high.

Another market trend in the embedded AI market is hardware acceleration and specialized chips. Often CPUs do not have good performance when it comes to AI tasks, thus having limited computing ability and consuming much power. These limitations made designing specialized chips such as GPUs, FPGAs or even ASICs specifically for artificial intelligence workloads possible.

On top of this, there has been increasing integration of embedded AI into consumer electronics and smart devices. In order to offer personalized intelligent experiences, smartphones, smart speakers wearables among other consumers’ electronic gadgets increasingly include embedded artificial intelligence capabilities that allows them to understand consumer preferences adapt accordingly and operate autonomously.

Moreover, the market is facing increased adoption of autonomous vehicles and robotics. Embedded AI helps in aiding self-driving cars and robots to sense their environment, reason, make intelligent decisions, and negotiate with complex situations. These applications need localized AI processing for real-time functions such as object detection, path planning or decision-making. This trend has led to development of embedded AI solutions that target autonomous systems specifically hence propelling growth in automotive and robotics sectors.