At the AWS re:Invent conference, TSMC, a leading cloud computing service provider, showcased the next-generation products of two chip families designed by AWS - AWS Graviton4 and AWS Trainium2, bringing improvements in cost-effectiveness and energy efficiency for various customer workloads. Just weeks before AWS made the announcement, Microsoft, a competitor to AWS in the cloud computing field, also announced two self-developed chips - Microsoft Azure Maia 100 AI accelerator and Azure Cobalt 100 CPU. Interestingly, both AWS and Microsoft's in-house chips will be developed by TSMC, a Taiwanese semiconductor manufacturing company. This Taiwanese semiconductor giant also produces chips for Google's Tensor Processing Unit (TPU), which was announced by the tech giant at the 2016 Google I/O conference. In addition, Google is also developing its own custom chips for its Pixel smartphones and will be using TSMC as the chip manufacturer, replacing Samsung. It is reported that Apple, the most popular smartphone manufacturer, is also working on incorporating many generative AI features into iOS 18. Similarly, these features are developed based on TSMC's N3E 3-nanometer process node. The revenue generated by artificial intelligence is expected to grow rapidly. TSMC's advanced manufacturing process enhances the computational capabilities of chips, meeting the demands of generative AI workloads. As of December 2023, TSMC's market value is $511.1 billion, making it the 12th largest company in terms of market capitalization. Currently, around 6% of TSMC's total revenue (which was $73.86 billion in 2022) comes from AI. However, the company expects this number to double in the next four to five years. From 2022 to 2027, TSMC anticipates a significant compound annual growth rate of nearly 50% in the field of artificial intelligence. The latest developments from major tech companies highlight the importance of TSMC in the AI ecosystem. Let's not forget that NVIDIA also relies on TSMC to manufacture their Graphics Processing Units (GPUs), which have become the most sought-after products in the AI industry this year. Interestingly, Intel's Gaudi2 processor, which competes with NVIDIA's H100, is also manufactured based on TSMC's 7-nanometer process. To keep up with the demand, TSMC plans to invest $2.87 billion in building a new factory for advanced semiconductor packaging, which is crucial for generative AI. Furthermore, despite having manufacturing facilities in Taiwan, TSMC has announced several expansion plans. In Arizona, USA, TSMC is constructing its second semiconductor factory, with the investment amount increasing from $12 billion to $40 billion. This new facility, called Fab 21, is expected to start chip production on TSMC's advanced N3 process technology in 2026. The latest reports indicate that TSMC is considering establishing a third manufacturing facility in the United States to develop 2-nanometer and 1-nanometer technologies. Similar expansion plans are also being evaluated in Japan. Additionally, the establishment of a second wafer fab in Europe is under consideration. Relying on TSMC sets a dangerous precedent. TSMC's 3-nanometer technology is crucial for AI chip companies. Accurate processing of large amounts of data is essential for AI applications, and TSMC's 3-nanometer process enables the development of more powerful and efficient AI chips by allowing the integration of more transistors on a single chip, thereby improving performance, energy efficiency, and overall capability. TSMC is one of the few companies in the world that can reliably produce cutting-edge semiconductor technology chips, including advanced AI chips. The company began mass production of its 3-nanometer technology in 2022, making it the most advanced semiconductor process in the industry. However, the AI industry's significant dependence on TSMC's chip manufacturing introduces potential risks, reminiscent of the challenges faced by industries that were overly reliant on specific suppliers in the past. For example, the industry faced severe dependence on NVIDIA's GPUs, but supply shortages left many companies desperate to obtain these GPUs. Given that the semiconductor industry has largely relied on Taiwan to meet global chip demand, will the AI field's dependence on TSMC set a similar precedent? It is worth noting that Samsung is the only other company with 3-nanometer technology. However, TSMC holds 60% of the market share in the third-party chip manufacturing business, compared to Samsung Electronics, which has a 12% market share. Interestingly, Qualcomm, which is trying to disrupt the smartphone industry with its AI processors, hinted at a dual foundry strategy with both TSMC and Samsung. However, Qualcomm officially announced its decision not to include Samsung in the production of its upcoming processors, once again emphasizing the importance of TSMC in the field of artificial intelligence.