There are signs that OpenAI, the company that rose to fame with its AI models, is now eyeing the semiconductor manufacturing sector. However, can building a wafer fab be an easy success?

Recently, international media revealed details of OpenAI CEO Sam Altman’s meetings with senior executives from multiple chip manufacturers during his visit to Asia last year.

Altman visited top executives at companies such as TSMC and Samsung, proposing an ambitious plan to invest $7 trillion to build 36 new wafer fabs and data centers to drive the development of artificial intelligence. Altman envisioned that these fabs, funded by the United Arab Emirates, would produce AI chips, which OpenAI and other companies could use to build AI data centers.

The report highlighted that the scale of the investment Altman mentioned is equivalent to a quarter of the annual output of the U.S. economy. To meet OpenAI’s expansion needs for computing power, it would take several years to complete the necessary wafer fabs.

However, due to cost considerations, TSMC did not endorse Altman’s plan. TSMC executives considered Altman’s proposal too aggressive and risky. Even building a few more wafer fabs involves high risk due to the immense capital required, let alone 36 fabs.

How Much Does a Wafer Fab Cost? Hundreds of Billions of Dollars

In recent years, driven by the demand for AI models, the need for chips has surged, and wafer fabs have been expanding rapidly. However, as OpenAI’s experience shows building a wafer fab is no simple task. It faces challenges such as international dynamics, costs, and technological hurdles, with cost being the largest barrier.

The cost of a wafer fab primarily involves land and facility construction, equipment procurement, technology development and intellectual property, as well as operation and maintenance. Land and facility construction take up a significant portion, as a fab requires extensive land for building plants and basic infrastructure such as electricity, water supply, and communication.

On the equipment side, the purchase of lithography machines, etching machines, ion implanters, and thin-film deposition tools is a major expense, especially for advanced lithography machines, which are extremely costly.

Additionally, a wafer fab requires significant research and operational costs, including intellectual property, equipment maintenance, staff training, safety protocols, and environmental management, all of which demand continuous investment from manufacturers.

When all these factors are calculated, the cost of building a wafer fab is extremely high. Moreover, as chip manufacturing processes evolve, the cost of fabs continues to rise. The industry estimates that the cost of a modern fab is in the range of billions of dollars. For example, Intel’s two factories in Arizona are expected to cost $15 billion each, while Samsung’s fab in Taylor, Texas, is projected to cost $25 billion.

Regional Differences in Wafer Fab Costs

It’s also worth noting that the cost of building a wafer fab varies by region. In Asia, for example, due to a well-established supply chain, abundant talent, and policy support, the cost of building a fab is relatively lower. In regions like Europe, the U.S., and the Middle East, however, costs may be higher due to the need to import technology, train talent, and develop a complete supply chain.

(Photo credit: Intel)

With AI giants in the Western world, such as OpenAI, Google and Meta, stealing the spotlight by their development of generative AI, some big names in China have introduced their AI models over the past 18 months, according to a latest report by CNBC.

Though trying to keep a low profile, five tech conglomerates in China, including Alibaba, Baidu, ByteDance, Huawei and Tencent, have launched their AI models lately, adding a new dimension to the competitive landscape of the ongoing tech rivalry between China and the U.S. Here is a brief introduction of the major Chinese AI models developed by the country’s leading tech firms, based on the information compiled by CNBC and other media reports.

Alibaba: Tongyi Qianwen

In November, 2023, a report by pandaily notes that Alibaba Cloud released its AI model, Tongyi Qianwen 1.0 a few months ago, while the 2.0 version was introduced later in the same year. Another report by South China Morning Post states that as of May, Alibaba reports that its Tongyi Qianwen AI models, often referred to as Qwen, are utilized by more than 90,000 corporate clients across China.

CNBC notes that in terms of Qwen, the company has developed various versions tailored to different functions. For instance, one model specializes in generating content or solving math problems, while another handles audio inputs and provides text-based responses.

It is worth noting that as some Qwen models are open-sourced, developers are allowed to download and use them under certain restrictions, according to CNBC.

Baidu: ERNIE

As one of China’s leading internet companies, Baidu was among the first to introduce generative AI applications in the country. A report by The Verge notes that the Ernie chatbot was available for download in August, 2023, after the approval by the Chinese government.

CNBC reports that Baidu intends to compete with OpenAI’s ChatGPT with Ernie Bot, as the company claims the bot to have 300 million users.

According to CNBC, ahead of the launch of its “Turbo” version, which took place in late June, Baidu stated that its Ernie 4.0 offers capabilities comparable to OpenAI’s GPT-4. According to Baidu, this foundational model has advanced understanding and reasoning abilities.

Similar to other companies, Baidu is offering access to its AI model through its cloud computing services, CNBC says.

ByteDance: Doubao

TikTok parent company ByteDance, though entered the AI race later than competitors like Baidu and Alibaba, has surprised the market with its low-cost Doubao model, which was launched in May, 2024.

According to a report by technode, the model can process 2 million Chinese characters, equivalent to 1.25 million tokens, for just RMB 1 (USD 0.14). In comparison, OpenAI’s latest multimodal model, GPT-4o, costs USD 5 per million input tokens.

CNBC notes that Doubao has various capabilities, including voice generation and coding support for developers.

Huawei: Pangu

Introduced by Huawei in 2021 as the world’s largest pre-trained Chinese large language models (LLMs) with over 100 billion parameters, the Pangu models are now entering their fourth iteration, according to Counterpoint. In May, 2024, the latest Pangu models are said to boast 230 billion parameters.

Interesting enough, Huawei has adopted a different strategy from its competitors with its Pangu AI models, CNBC remarks. The tech giant focuses on developing industry-specific models tailored to sectors like government, finance, manufacturing, mining, and meteorology.

For instance, Huawei claims that its Pangu Meteorology Model can predict a typhoon’s trajectory 10 days in advance in just 10 seconds, a task that previously took four to five hours, according to CNBC.

Tencent: Hunyuan

Last year, Tencent introduced its foundational model, Hunyuan, which is accessible through Tencent’s cloud computing services.

According to CNBC, Tencent has highlighted Hunyuan’s strong Chinese language processing abilities and advanced logical reasoning, supporting features like image generation and text recognition. The model is designed for use across industries such as gaming, social media, and e-commerce.

As the operator of China’s largest messaging app, WeChat, Tencent launched an AI chatbot this year based on the Hunyuan model. The AI assistant, named Yuanbao, can access information and content from WeChat, setting it apart from competitors, CNBC notes.

Notably, China’s large language models, just like its rivals in the West, rely on the strong computing power of AI chips. A previous report by Reuters in November, 2023, states that Tencent is said to have stockpiled a substantial reserve of AI chips from NVIDIA, as the company prepares in advance to train its Hunyuan AI models for the following generations.

How far will the tech giants in China be able to push the boundaries of AI models? The answer may lie in the development of the country’s domestic chips, as the U.S. authority already banned the export to China of AI chips.

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(Photo credit: Baidu)

TSMC’s angstrom-level A16 process is creating a buzz even before mass production. According to a report from the Economic Daily News, not only has major client Apple already booked the capacity for TSMC’s A16, OpenAI has also joined in to secure TSMC’s A16 capacity due to its long-term need for self-developed AI chips.

Regarding this matter, TSMC stated on August 30 that the company does not comment on market rumors or on business dealings with individual customers.

Despite that TSMC’s A16 process is scheduled to enter mass production in 2026, the report has hinted that the first batch of customers has already surfaced.

In addition to Apple, which has been in continuous collaboration with TSMC, the most notable new customer of TSMC’s A16 is said to be OpenAI, the developer of ChatGPT, which is actively investing in the design and development of its own ASIC chips.

Industry sources cited by the same report reveal that OpenAI had initially been in active discussions with TSMC about establishing a dedicated fab. However, after assessing the potential benefits, the plan to build a dedicated facility was shelved.

Strategically, OpenAI is now partnering with U.S. companies like Broadcom and Marvell to develop its own ASIC chips, and potentially emerging as one of Broadcom’s top four customers.

Since both IC design giants are long-term clients of TSMC, the ASIC chips they are helping OpenAI develop are expected to be produced using TSMC’s 3nm process family and the subsequent A16 process, according to the chip design roadmap.

It is worth noting that OpenAI not only holds a critical position in the development of AI applications beyond Apple’s ecosystem but also contributes to the advancement of AI applications in Apple devices.

In June of this year, Apple unveiled its personalized intelligent system, Apple Intelligence, which has integrated ChatGPT. This strategic move has led observers to believe that OpenAI plays a key role in Apple’s AI development.

As OpenAI continues to invest in the design and development of its own ASIC chips, it is reportedly expected to maintain its influence in the AI computing field.

TSMC unveiled its angstrom-class A16 advanced process during the company’s 2024 North America Technology Symposium on April 25, set to be mass-produced in 2026.

Per TSMC, Compared to TSMC’s N2P process, the A16 offers an 8% to 10% speed increase at the same Vdd (operating voltage), a 15% to 20% reduction in power consumption at the same speed, and a density increase of up to 1.1 times, supporting data center products.

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The Wall Street Journal reported that OpenAI is in talks for a new round of funding, with tech giants Apple and NVIDIA both interested in investing in the AI research company OpenAI.

It’s reported that this investment will be part of OpenAI’s new round of financing, which will bring its estimated value to exceed USD 100 billion.

Sources indicated that OpenAI plans to raise billions of dollars, and venture capital firm Thrive Capital will lead this round of funding with a USD 1 billion investment. Microsoft, OpenAI’s largest shareholder, will also be a part of this round.

Reportedly, sources have revealed that Apple is currently in talks with OpenAI for the potential investment, while NVIDIA has already discussed joining the latest round of funding, who reportedly considered investing USD 100 million.

Although it is not yet clear how much Apple and Microsoft plan to invest, the point is that the three most valuable tech giants in the world would all become shareholders of OpenAI if these negotiations end in success.

In a memo on Wednesday, OpenAI’s CFO Sarah Friar stated that the company is seeking new financing but did not disclose specific details. Friar mentioned that OpenAI would leverage this funding to strengthen computing power and cover other operational expenses.

With the rise of the AI industry, Microsoft, Apple, and NVIDIA have also accelerated their pace in developing AI technologies.

Microsoft has invested USD 13 billion in OpenAI since 2019, holding a stake of 49% in this company. Apple, at its Worldwide Developers Conference (WWDC) in June this year, launched the Apple Intelligence system and announced a partnership with OpenAI.

As for NVIDIA, it has long been closely collaborating with OpenAI and has been highly active in making investment in this field. Its investment arm, NVentures, has invested in several AI companies since 2023.

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(Photo credit: OpenAI)

According to a report from Nikkei on August 29, Apple is said to be betting that its first iPhone with Apple Intelligence will be a hit. Thus, the tech giant has requested suppliers to provide components for approximately 88 to 90 million iPhones, over 10% more than the initial component orders of 80 million units for new iPhones in 2023.

Reportedly, some component suppliers have received orders for more than 90 million iPhones. However, they also noted that Apple’s initial orders are typically larger, with adjustments made based on actual sales performance after the launch.

An industry source cited in the report expressed caution regarding Apple’s strong order volume, noting that geopolitical factors are likely to pose significant challenges for iPhone sales in China.

The report cited multiple sources, noting that Apple suppliers are generally cautious,  and forecasting that iPhone shipments for the year will likely be flat, due to the high comparison base from 2023.

In late 2022, COVID-19 has caused disruptions in Zhengzhou, China, the world’s largest iPhone manufacturing hub, resulting in the delay in iPhone shipments to the first half of 2023.

On the other hand, it is still unclear how Apple Intelligence will operate in China, as Apple has yet to finalize agreements with any Chinese AI companies.

While OpenAI’s chatbot, ChatGPT, is available in countries like the United States, it is not accessible in China. To introduce similar AI functionalities, Apple will likely need to collaborate with Chinese AI companies.

A previous report from Economic Daily News once indicated that Apple has been in discussions with Baidu, Alibaba Group, and Beijing-based startup Baichuan AI, but no agreements have been confirmed yet.

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(Photo credit: Apple)