Artificial Intelligence Chipsets Market Trends

Artificial Intelligence Chipsets Market Trends

Edge AI is increasingly being integrated into Internet of Things (IoT) devices, allowing for faster data processing and decision-making at the source, rather than relying on cloud-based servers. This trend is driven by the need for real-time analytics and reduced latency in applications such as smart home devices, industrial sensors, and autonomous vehicles.
 

For instance, in August 2022, NVIDIA announced its new Jetson Orin series, designed to bring powerful AI computing to edge devices. These chipsets offer enhanced performance for AI workloads directly on the device, supporting complex applications like autonomous robotics and real-time video analytics without relying on centralized cloud servers.
 

AI chipset miniaturization is a key trend in the industry, driven by the need to embed advanced AI capabilities into increasingly compact and portable devices. This trend is essential for integrating powerful AI functions into consumer electronics, wearables, and other compact gadgets. Miniaturization involves shrinking the size of AI chipsets while maintaining or even enhancing their performance. This trend is fueled by the growing demand for smarter, more efficient devices in various sectors.
 

Smaller chipsets allow for the inclusion of sophisticated AI features in devices with limited space, such as smartphones, smartwatches, and other wearable technology. The advantages of miniaturization include reduced power consumption, improved energy efficiency, and the ability to incorporate AI directly into devices without relying on cloud-based processing.
 

For example, in September 2023, Apple introduced the A17 Pro chip, which powers the iPhone 15 Pro and iPhone 15 Pro Max. Built using a cutting-edge 3nm process, the A17 Pro chip represents a significant advancement in miniaturization technology. The A17 Pro boasts 19 billion transistors, an increase from the 16 billion in the A16 Bionic chip. This enhancement is crucial as more transistors enable better processing capabilities and power efficiency.