TSMC: 3-нм техпроцесс загружен до отказа до 2027 года

Taiwanese company TSMC (Taiwan Semiconductor Manufacturing Company), the world's largest semiconductor manufacturer, has faced an unprecedented situation: its advanced production line using 3-nanometer process technology (3-nm) is completely booked out, with all capacity reserved until 2027. The reason is explosive growth in demand for chips necessary for the development and operation of artificial intelligence (AI) systems. The 3-nanometer process (3-nm) is one of the most advanced and complex semiconductor manufacturing methods.

It enables the creation of more compact, faster, and energy-efficient chips, which is critical for resource-intensive tasks such as neural network training and large-scale data processing. The growing popularity of AI across all sectors, from autonomous vehicles to cloud services, has led to a sharp increase in demand for such chips, causing a shortage of TSMC's production capacity. This situation creates serious problems for many companies dependent on TSMC for chip supplies.

Primarily, this concerns AI system developers and manufacturers, who now must either wait their turn for production or seek alternative suppliers. It is clear that delays in chip shipments could negatively impact the development pace of the AI industry as a whole. Analysts at Deutsche Bank believe that the current situation opens new opportunities for South Korean company Samsung Electronics, which also possesses 3-nanometer process chip manufacturing technology (3-nm).

Samsung could attempt to attract some orders away from TSMC by offering shorter production timelines. However, whether Samsung will be able to fully capitalize on this opportunity remains to be seen. It must be considered that TSMC has enormous experience and a reputation as a reliable supplier, which makes it attractive to many clients despite current capacity issues.

For end users, this could mean increased costs of devices and services using AI. The chip shortage and competition for production capacity could lead to rising semiconductor prices, which will inevitably be reflected in the cost of end products. Additionally, there may be delays in the release of new models of smartphones, computers, and other devices using advanced AI technologies.

In conclusion, the shortage of TSMC's 3-nanometer chips is a serious challenge for the entire AI industry. It highlights the growing dependence on a limited number of semiconductor manufacturers and the need for supply chain diversification. In the coming years, competition in the chip manufacturing market will likely intensify as other companies strive to carve out their niche in this rapidly growing industry.

This situation also raises the question of the need for investment in developing new production capacity and technologies to meet the growing demand for AI chips.