The latest quarterly reports from the big four cloud service providers (CSPs) have been released in succession. According to a report from Commercial Times, not only has there been significant revenue growth, but capital expenditures for these CSPs have also surged compared to the same period last year, underscoring the ongoing momentum in AI investments.

Industry scources cited by Commercial Times estimate that capital expenditures by CSPs will surpass USD 240 billion by 2025, reflecting an annual increase of over 10%.

The report indicated that the increase in capital expenditures by CSPs is expected to boost demand for Taiwanese companies in the supply chain during the fourth quarter of this year and into next year, benefiting companies such as Quanta, Wistron, Wiwynn, and Inventec.

According to the report, Microsoft’s capital expenditures for the first quarter of fiscal year 2025 (the third quarter of 2024) reached USD 20 billion, higher than USD 19 billion of the previous quarter, reflecting a 78% increase year-on-year. Microsoft noted that the demand for AI now exceeds available production capacity, and they plan to continue increasing investment, expanding data center construction, and promoting AI services.

The report indicated that the market estimates Microsoft’s total expenditures for fiscal year 2025 will reach USD 80 billion, an increase of over USD 30 billion compared to the previous year.

Google’s capital expenditures in the third quarter reached USD 13.1 billion, an annual increase of 62%, which means that total capital expenditures in 2024 will reach USD 51.4 billion, an annual increase of 59%, and capital expenditures will continue to increase next year, according to the report.

Amazon’s capital expenditures for the third quarter reached USD 22.62 billion, reflecting an 81% year-on-year increase. This year, Amazon’s total capital expenditures have reached USD 51.9 billion, and full-year investments are projected to be as high as USD 75 billion. Furthermore, capital expenditures for next year are expected to be even higher, as the report indicated.

According to the report, as for Meta, capital expenditures in the third quarter were USD 9.2 billion, an annual increase of 36%. Moreover, Meta adjusted their capital expenditure forecast for fiscal 2024 to an upward revision of USD 40 billion. The report indicated that its capital expenditures will continue to grow in 2025.

The report highlighted that AI business opportunities will continue to benefit Taiwan’s major server ODMs. Companies such as Quanta, Wistron, Wiwynn, Inventec, and Foxconn all reported strong results in the third quarter and are optimistic about the fourth quarter and the year ahead.

According to the report, Quanta’s third-quarter revenue reached a record high, driven by strong demand for AI server orders. Quanta Chairman Barry Lam also expressed an optimistic outlook on the future of AI, noting that as large-scale CSPs develop generative AI applications, the scale of AI data centers is continually expanding, leading to a substantial increase in orders.

After demonstrating strong growth momentum in the first half of the year, Wistron has benefited from urgent orders in the second half. Additionally, some B200 series products utilizing the next-generation Blackwell platform are scheduled to be shipped after the fourth quarter. The report indicated that Wistron is quite optimistic about its performance for this quarter and next year.

Inventec plans to ship servers to customers primarily from US-based CSPs in the second half of the year. The report highlighted that orders from Google have increased as the company expands its purchase of AI servers based on its own TPU architecture, in addition to acquiring general-purpose servers for new platforms.

Read more

• High-End AI Server Demand from North America’s Top Four CSPs Expected to Exceed 60% in 2024, Says TrendForce
• [Insights] Big Four CSPs Continue to Shine in Q1 2024 Financial Reports, AI Returns Garnering Attention

(Photo credit: Microsoft)

According to a report from Wccftech, Google is rumored to switch to TSMC’s second-generation 3nm process, “N3E”, for its Tensor G5. The report also claims that for the Tensor G6, Google will utilize TSMC’s “N3P” process instead of the 2nm process speculated earlier. Its entire Pixel 10 series set to be launched next year will use TSMC’s 3nm process.

The report suggests that the Tensor G4 processor may be the last Google chipset manufactured by Samsung using its 4nm process, since the Tensor G4 reportedly offers only a slight upgrade compared to the Tensor G3 in the Pixel 8 smartphone, as it continues to use Samsung’s older FO-PLP packaging technology instead of the newer FO-WLP packaging, which is more capable in preventing overheating.

Notably, the report states that Qualcomm and MediaTek have also adopted the 3nm “N3E” process for their Snapdragon 8 Elite and Dimensity 9400 chipsets for the first time this year, having bridged the technological gap with Apple.

Therefore, the report notes that Google will still be a year behind in the competition when it announces the Tensor G5 and Tensor G6, since Qualcomm, MediaTek, and Apple are already using TSMC’s 3nm process and are expected to shift to N3P.

According to the report, the Tensor G5 was reported to have reached the tape-out stage earlier this year and is expected to use TSMC’s InFO-POP packaging, which allows the chipset’s packaging to be smaller and also more power efficient.

Regarding Tensor G6, it will likely launch two years from now. Although it was previously rumored that Tensor G6 will use TSMC’s 2nm process, the report indicates that it will instead utilize TSMC’s enhanced version of 3nm, N3P node.

According to a report from AnandTech, as a more enhanced process node compared to N3E, N3P offers better performance with higher transistor density and reduced power consumption.

The report indicates that it makes sense that Google is not opting to adopt the 2nm process immediately, especially since even Apple is expected to wait until the launch of the iPhone 18, two years from now, to introduce its first A-series chipsets that will exceed the 3nm barrier. Additionally, it is expected that the 2nm A-series chipsets will not be included in all iPhone 18 models due to their high cost.

Read more

• [News] TSMC Rumored to Secure Tensor G6 Orders from Google with Its 2nm Process
• [News] Google’s Tensor G5 Reportedly Manufactured with TSMC’s 3nm and InFO-POP Packaging

(Photo credit: Google)

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.

Read more

• [News] China’s Core AI Industry Achieved a Market Size of Nearly CNY 600 Billion

(Photo credit: Baidu)

On September 9, Indian tech blog PiunikaWeb cited a report from Tech & Leaks Zone, stating that rumors have hinting at Google’s preparation to exit Samsung Electronics’ wafer foundry business, Samsung Foundry, and switch to TSMC in 2025. The next two generations of Google’s custom Tensor processors are reportedly expected to use TSMC’s 3nm and 2nm processes, respectively.

As per the same report, Google’s Tensor G4 processor is being manufactured by Samsung Foundry using its 4nm process. However, the G4 offers only a slight upgrade compared to the Tensor G3 in the Pixel 8 smartphone, as the G4 continues to use Samsung’s older FO-PLP packaging technology instead of the newer FO-WLP packaging, which is more capable in preventing overheating.

On the other hand, Google’s Tensor G5, which will be used in the Pixel 10, is reportedly set to be manufactured by TSMC using the latest 3nm process and TSMC’s advanced InFO-POP packaging technology. The Tensor G6, which will support the Pixel 11 series, will also be produced by TSMC using 2nm process.

Notably, Apple had introduced an AI technical document in June, disclosed that two AI models supporting “Apple Intelligence” were trained in the cloud using Google’s custom-designed Tensor Processing Unit (TPU).

Per Google’s official website, the cost of using its most advanced TPU can be less than USD 2 per hour if reserved three years in advance. Google first introduced the TPU in 2015 for internal use, and it became available to the public in 2017.

Additionally, per a report from wccftech, Google’s ARM-based TPU v5p “Axion,” designed specifically for data centers, is also rumored to be manufactured using TSMC’s enhanced 3nm process, N3E.

Read more

• [News] Google’s Tensor G5 Reportedly Manufactured with TSMC’s 3nm and InFO-POP Packaging
• [News] Breaking Apple’s Monopoly – TSMC’s InFO Packaging Reportedly Adds Google Chips

(Photo credit: Google)

China has long been the preferred location for tech companies to establish their supply chains. However, in recent years, the decline in population dividends has led to rising labor costs, and the need for tech companies to mitigate the impact of geopolitical risks has prompted them to accelerate the relocation of supply chains out of China, with some shifting production capacity to Southeast Asia and South Asia.

Recently, as per a report from TechNews citing sources, it’s indicated that HP is considering moving more than half of its personal computer production away from China to countries like Thailand and Vietnam.

This move is primarily aimed at significantly reducing its reliance on China’s supply chain, as well as addressing global trade dynamics and the need to lower costs.

In addition to HP, several well-known tech companies are also shifting their supply chains to Southeast Asian and South Asian countries.

• Apple

One notable example of supply chain relocation is Apple. Having long relied on China’s supply chain, Apple is now finding that the era of full dependence on China is coming to an end due to political and commercial pressures.

iPhone

As one of Apple’s most important products, iPhone has been a key focus in this shift.

Although supply chain diversification was always part of Apple’s strategy, the plan has been accelerated following a series of disruptions at Foxconn’s Zhengzhou plant during the pandemic. These events have compelled Apple to expedite its efforts to diversify its supply chain.

According to a report from Business Standard, since April of this year, Apple has assembled iPhones worth USD 14 billion in India, with 14% of iPhones now being manufactured there.

Rajeev Chandrasekhar, India’s former Union Minister of State for Electronics and Information Technology, also stated on the X platform that by 2028, it is estimated that up to 25% of iPhones will be made in India.

iPad

In addition to iPhone, Apple has also started shifting part of its iPad production to Vietnam. Foxconn is responsible for manufacturing iPads in Vietnam, where mass production and shipments are already underway.

MacBook

Similarly, the MacBook production line has been partially moved out of China and relocated to Vietnam, which is primarily produced by Quanta and Foxconn in their Vietnamese facilities.

Earlier rumors cited by Nikkei have suggested that Apple was considering shifting some of its production to Thailand as well. However, Thailand’s supply chain for key components is not yet fully developed, with many parts still reliant on imports from China.

The associated transportation costs and the risk of potential damage during transit have led Apple to prioritize setting up production lines in Vietnam first.

Nevertheless, Thailand’s strong electronics manufacturing infrastructure and cost advantages make it a potential future production site for Apple.