In a last-ditch effort before the upcoming board meeting this week, Intel is said to be seeking assistance from the U.S. government. The latest report by CNBC notes that Intel CEO, Pat Gelsinger, turned to Commerce Secretary Gina Raimondo recently, expressing his disappointment with the heavy dependence of U.S. companies on TSMC, the Taiwanese foundry heavyweight.

According to CNBC, after meeting with Intel, Raimondo followed up by meeting with several public market investors to emphasize the significance of U.S. chip manufacturing amid the rising geopolitical risks surrounding Taiwan. Her aim was to encourage shareholders in companies like NVIDIA and Apple to understand the economic advantages of having a U.S.-based foundry capable of producing AI chips, the sources cited by the report said.

Interesting enough, Jensen Huang, CEO of NVIDIA, mentioned yesterday that the U.S. chip giant heavily relies on TSMC for producing its most important chips, saying TSMC’s agility and ability to respond to demand are incredible. Thus, shifting orders to other suppliers could reportedly lead to a decline in chip quality.

Intel has introduced its Lunar Lake processors in early September, with the target to shake up the AI PC market. However, the chips are outsourced to TSMC, manufactured with the foundry giant’s 3nm node.

Getting stuck in its current situation, Intel is said to be pushing U.S. officials to expedite the release of funding, another report by Bloomberg notes. Earlier in April, Intel and Biden administration announced up to USD 8.5 billion in direct funding under the CHIPS Act.

The company is slated to receive USD 8.5 billion in grants and USD 11 billion in loans under the 2022 Chips and Science Act, but this funding is contingent on meeting key milestones and undergoing extensive due diligence, according to Bloomberg. Therefore, like other potential beneficiaries, Intel has not yet received any money.

An official cited by CNBC said that disbursements are anticipated by the end of the year.

Both the U.S. Commerce Department and an Intel spokesperson declined to comment, according to CNBC.

Regarding the latest development of Intel’s plan to shedding more than 15% of its workforce, a report by CTech notes that Intel may lay off over 1,000 employees in Israel as global cuts begin.

CTech states that Intel has been mindful of geopolitical factors and the timing of local holidays in Israel. Therefore, it would be rather unexpected for the company to initiate layoffs in the country before or during the holiday season, which begins in early October and extends through most of the month.

Citing Gelsinger’s remarks, the report notes that the restructuring process will continue until the end of the year, allowing Intel’s Israeli branch a window of time to start the layoffs after the holidays.

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• [News] CEO Jensen Huang Highlights Strong Demand, Stating that Everyone is Counting on NVIDIA
• [News] Intel Reportedly Outsources All Sub-3nm Process Production to TSMC

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

(Photo credit: Baidu)

In recent years, data center has been one of the key areas for GaN (Gallium Nitride) manufacturers to tap power electronics market, and GaN applications in the data center power supply market have taken a big step forward. Notably, the rise of AI technology has further fueled this market at present.

In the AI ecosystem, data centers have enormous demands for high-speed computing and power. According to a TrendForce report, NVIDIA’s Blackwell platform will be officially launched in 2025, replacing the existing Hopper platform, and will become NVIDIA’s primary solution for high-end GPU, accounting for nearly 83% of all high-end products.

For high-performance AI servers like the B200 and GB200, a single GPU can consume more than 1,000W of power.

Facing soaring power demands, the power specifications for each data center rack will increase from 30-40kW to 100kW, posing significant challenges for data center power systems. The combination of GaN and liquid cooling technologies will be critical to improving energy efficiency in AI data centers.

The hike in chip power consumption requires servers to achieve higher power density and efficiency.

GaN, which reduces energy losses and increases power density, is now seen as one of the key technologies for optimizing energy efficiency in AI data centers, which has attracted many players, including Infineon, Texas Instruments (TI), Navitas, Innoscience, Transphorm, CorEnergy, Danxi Tech, and GaNext, to join the race.

Among them, both Navitas and Infineon have unveiled their AI data center power roadmaps.

Infineon’s AI Data Center Power Roadmap (Source: Infineon)

Combining the unique advantages of Si (Silicon), SiC (Silicon Carbide), and GaN (Gallium Nitride), Infineon has launched a 3 kW PSU and a 3.3 kW PSU, with an 8 kW PSU expected to be available in the first quarter of 2025.

The new 8 kW PSU will support AI racks with outputs of up to 300 kW or more. Compared to the 32 W/in³ density of the 3 kW PSU, its efficiency and power density will increase to 100 W/in³, further reducing system size and lowering operator costs.

In terms of GaN technology, Infineon’s CoolGaN™ solution can provide over 99% system efficiency in PFC topologies. Moreover, GaN Systems, acquired by Infineon, already released a 3.2kW AI server power supply as early as 2022 and unveiled its fourth-generation GaN platform in 2023.

The new platform achieves efficiency exceeding the Titanium level, with power density increased from 100W/in³ to 120W/in³. Thereby, the industry highly expects the synergistic effect created by the combination of these two companies.

Navitas introduced its GaNSafe™ and Gen-3 Fast SiC technology last year, along with a 4.5kW CRPS design, achieving more than double the power density of traditional silicon solutions. In July this year, Navitas unveiled its CRPS185 4.5kW AI data center server power solution, with a power density of 137W/in³ and over 97% efficiency.

Navitas AI Data Center Power Roadmap (Source: Navitas)

Navitas revealed that over 60 customer projects involving 3.2kW and 4.5kW power solutions for data centers are currently under development.

These projects are expected to bring millions of dollars in revenue growth for Navitas’ GaN and SiC business between 2024 and 2025. It aims to begin small-scale production of AI data center power solutions in 2024.

Aside from Infineon and Navitas, other manufacturers like TI, EPC, CorEnergy, GaNext, and Innoscience also set sights on this market.

TI reached an agreement with Delta, the world’s largest server power supply provider (with nearly 50% market share), as early as 2021. Based on GaN technology and TI’s C2000™ MCU real-time control solution, they are developing high-efficiency, high-power server PSU for data centers.

Thus, their joint efforts and future fruit in the AI server power market are highly anticipated.

Beyond AI data center server, humanoid robot industry that enjoys burgeoning growth this year, also injects new vitality into the GaN market.

Humanoid robot is assembled by sensing, control, motor, and battery systems, in which GaN can has its place in LiDAR system, motor drive, DC-DC converter, and battery BMS, among which motor drive plays a critical role.

According to TrendForce, the demand for motor driver in humanoid robot has skyrocketed due to the mounting demands for degrees of freedom.

To achieve higher power output, high-power-density, high-efficiency, and fast-response motor driver are in demand, and GaN is a perfect fit for it, which also has the ability to strengthen overall robot performance in terms of heat management, compact design, and overall system design.

It is reported that Siemens, Yaskawa Electric, and Elmo have already integrated GaN technology into their robotic motors, and the GaN industry chain is gearing up for seizing more opportunities.

Currently, companies such as TI, EPC, Transphorm, Innoscience, Navitas, and CorEnergy are actively promoting GaN adoption in motor drive market. Among them, Transphorm has supplied GaN FET products for Yaskawa Electric’s new servo motor.

TrendForce points out that future robots will exceed our imagination, with precise, fast, and powerful movement capabilities as the key parts, which will inevitably push the motors required to drive these movements advance forward, and this is regarded as a boon for GaN technology.

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• [News] Global GaN Power Device Market Size Expected to Reach USD 4.376 Billion in 2030, CAGR of 49%
• [News] Foundry Giant GlobalFoundries Acquired GaN-Related IP

(Photo credit: Infineon)

At its 2024 semi-annual results briefing, Loongson Zhongke Technology announced that the 3B6600 processor is expected to begin sampling in the first half of next year and be officially released in the second half.

Per a report from IThome, Chairman and General Manager Hu Weiwu emphasized that this iteration involves significant structural changes, with anticipated single-core performance ranking among the “world-leading” levels.

Hu previously revealed that the 3B6600, an eight-core desktop CPU currently in development, utilizes a mature process and is expected to achieve mid-to-high-end performance levels comparable to Intel’s 12th to 13th generation Core-i CPUs.

Regarding product cycles, he mentioned that Loongson aims to release at least one server or PC chip each year.

Per Loongson’s previous roadmap, the next-generation 3B6600 processor will feature eight LA864 cores with a clock frequency of 3.0 GHz and include the LG200 integrated graphics card.

Additionally, a faster 3B7000 variant, currently in development, is expected to reach a frequency of up to 3.5 GHz and offer a comprehensive range of I/O interfaces, including PCIe4, SATA3, USB3, GMAC, and HDMI.

Last year, Loongson introduced the desktop CPU Loongson 3A6000, which officially matched the performance of Intel’s 10th-generation Core i4 processor released in 2020.

This year, Loongson successfully developed the 16-core and 32-core versions of the Loongson 3C6000 and 3D6000 server CPUs, which are officially claimed to perform at levels comparable to Intel’s Xeon 4314 and 6338.

As per another report from the global media outlet tom’s Hardware, the rumored new 7nm process may have achieved faster clock frequencies, increased core counts, and other improvements. However, it is still awaiting the release of the latest products.

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• [News] Rising Chinese GPU Contender Emerges? Achieving Local GPU Production in Three Years, Claims “Outperforming AMD”

(Photo credit: Loongson Zhongke Technology)

ACM Research, Inc., a provider of wafer processing solutions for semiconductor and advanced wafer-level packaging applications in China, announced on September 3rd the release of its Ultra C bev-p panel bevel etching tool for fan-out panel-level packaging (FOPLP) applications.

This new tool is designed for bevel etching and cleaning in copper-related processes, offering dual-side bevel etching for both the front and back of panels within a single system, further boosting process efficiency and enhances product reliability.

Moreover, a day after the announcement, the company further revealed that it had received purchase orders for four wafer-level packaging tools, including two from a U.S.-based customer and two from a U.S.-based research and development (R&D) center.

Dr. David Wang, ACM’s president and chief executive officer, believes that FOPLP will grow in importance as it addresses the evolving needs of modern electronic applications, offering benefits in integration density, cost efficiency, and design flexibility.

Reportedly, the new Ultra C bev-p tool is designed to deliver advanced performance, utilizing ACM’s expertise in wet processing. It is one of the first tools to incorporate double-sided bevel etching for horizontal panel applications.

Together with the Ultra ECP ap-p for electrochemical plating and the Ultra C vac-p flux cleaning tools, the Ultra C bev-p is expected to support the FOPLP market by enabling advanced packaging on large panels with high-precision features.

ACM emphasizes that the Ultra C bev-p tool is a critical enabler for FOPLP processes, employing a wet etching technique tailored for bevel etching and copper residue removal.

This process plays a vital role in preventing electrical shorts, reducing contamination risks, and preserving the integrity of subsequent processing steps, ensuring long-term device reliability. The tool’s effectiveness is driven by ACM’s patented technology, designed to tackle the specific challenges of square panel substrates.

Different from traditional round wafers, ACM’s design is said to ensure precise bevel removal process that stays confined to the bevel region, even on warped panels. This is essential for maintaining the integrity of the etching process while ensuring the high performance and reliability needed for advanced semiconductor technologies.

Currently, major players in the FOPLP advanced packaging field include Powertech Technology, ASE Group, SPIL, TSMC, Innolux, JSnepes, and Samsung Electro-Mechanics.

TrendForce points out that FOPLP technology presents advantages and disadvantages. Its main strengths are lower unit cost and larger package size, but as its technology and equipment systems are still developing, the commercialization process is highly uncertain.

It is estimated that the mass production timeline for FOPLP in consumer IC and AI GPU may fall between the second half of 2024 to 2026, and 2027-2028, respectively.

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• [News] ACM Research Steps into FOPLP Advanced Packaging Field
• [News] TSMC Reportedly Forms a Team on FOPLP Development, with Mini Line on the Road 

(Photo credit: ACMR)