What impact is AI having on the demand for electronics components?

9 September 2024

AI is driving significant growth in the demand for electronic components by enabling new applications, enhancing existing technologies and optimising manufacturing processes across various industries.

Demand for electronic components that power AI algorithms

AI is being integrated into a wide range of applications across industries, including healthcare, automotive, finance and manufacturing. As AI applications become more prevalent, the demand for electronic components that power AI algorithms, such as GPUs, TPUs and specialised AI chips is also increasing.

Increased Processing Power

Complex Algorithms

Running complex AI algorithms requires significant processing power. This translates to a demand for high-performance processors, GPUs (graphics processing units), and specialised AI accelerators. These components are seeing increased demand due to the growing adoption of AI in various fields.

Growth in Specialised Hardware

Machine Learning Applications

Machine learning, a core component of AI, relies heavily on specialised hardware like Field-Programmable Gate Arrays (FPGAs) and Application Specific Integrated Circuits (ASICs). These components can be optimised for specific AI tasks, leading to increased demand.

Rise of Edge Computing

Distributed Processing

The trend towards edge computing, where AI processing happens closer to data sources, requires a vast number of electronic components for devices like smart sensors and edge computing nodes. This creates a demand for smaller, more energy-efficient components.

Demand for Memory and Storage

Large Datasets

Training and running AI models often involve massive datasets. This necessitates a significant increase in memory and storage capacity, driving demand for DRAM, NAND flash and solid-state drives (SSDs).

Impact on Specific Components:

GPUs

GPUs, with their parallel processing capabilities, are well-suited for AI tasks. This has led to a surge in demand for high-performance GPUs for AI applications.

CPUs

While GPUs excel in specific AI tasks, traditional CPUs are still crucial for many AI applications. This fuels the demand for high-performance CPUs with increased core counts.

Specialized AI Hardware:

The emergence of specialised AI accelerators like TPUs (Tensor Processing Units) from companies like Google and Nvidia is creating a new category of high-demand components for AI applications.

AI is acting as a major driver for the electronics component industry

The demand for high-performance processors, specialised hardware, memory and storage is rising significantly. This presents an opportunity for component manufacturers but also creates challenges, such as keeping up with the evolving needs of AI and ensuring a stable supply chain for these components.

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