The impact of artificial intelligence on the electronic component supply chain

Artificial intelligence and machine learning technologies are constantly advancing, and as a result, the electronics industry has received more widespread attention. Experts predict that the application of artificial intelligence in the semiconductor industry may accelerate in the next few years.

Not only will the semiconductor industry produce artificial intelligence chips, but the chips themselves can also be used to improve the efficiency of the supply chain for electronic components. Included in AI chips are GPUs, field programmable gate arrays (FPGAs), and application-specific integrated circuits (ASICs) dedicated to AI.

CPUs are common components used for basic AI tasks, but they are used less frequently as AI technology develops. The power of artificial intelligence depends on the number and size of transistors it uses. The more and smaller the transistors, the more advanced the AI chip will be.

AI chips need to do a lot of computation in parallel rather than sequentially, and the data they process is huge.

It has been suggested that designing AI chips and networks operate in the same way as the human brain. If the chip acts like a neuron synapse, sending information only when needed, rather than working continuously. For this use, non-volatile memory on a chip would be a good choice for AI. This type of memory can hold data without power, so there is no need for a constant supply. If combined with processing logic, a system-on-chip processor can be implemented.

While designs were created for AI chips, production was an extraordinary challenge. The node size and cost required to produce these chips are often too high to be profitable. As structures get smaller, such as moving from the 65nm node to the latest 5nm, costs skyrocket. The R&D cost for 65nm is $28 million, while the R&D cost for 5nm is $540 million. Likewise, for the same two-node fab construction, the price has increased from $400 million to $5.4 billion.

Companies have been investing in research and development of AI chip infrastructure. However, at every stage of the development and manufacturing process, significant capital investment is required.

Manufacturers also require a high degree of specialization, as the AI infrastructure is uniquely set according to its intended use. That means the entire supply chain of a manufacturer that hasn't been specialised could cost millions of dollars to revamp.

Artificial Intelligence The use of artificial intelligence in the electronic component distribution industry can revolutionize the way people work and maximize profits for companies. It helps companies make supply forecasts, optimize inventory, schedule deliveries, and more.

At every step of the electronics supply chain, artificial intelligence and machine learning can perform time-consuming tasks. At the sales stage, AI can assist with customer segmentation and dynamic pricing, which is very rare in the current market. It also prevents possible errors in the manufacturing process and increases the intelligence of manufactured ICs and semiconductors.

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