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The U.S. Producer Price Index (PPI) slightly increased in August, according to data released by the Bureau of Labor Statistics on September 12. The PPI rose by 0.2% month-over-month (previously 0%), exceeding market expectations of 0.1%. On a year-over-year basis, the PPI increased by 1.7% (previously 2.2%), falling short of the expected 1.8%, marking the lowest annual gain so far this year.
Breaking down the details, final demand goods prices remained flat month-over-month (previously up 0.6%), primarily due to a decline in energy prices, which dropped by 0.9% (previously up 1.8%). Excluding food and energy, prices rose by 0.2% for the month, posting the same increase as in the prior month.
Final demand services prices rose by 0.4% (previously down 0.3%), mainly driven by increases in other service categories, with guestroom rental prices contributing the most, surging by 4.8%. This mirrors the trend seen in the Consumer Price Index (CPI) data released a day earlier.
Overall, while the PPI demonstrated moderate growth in August, the Fed has shifted its focus on inflation towards the labor market. As a result, the inflation influence on future rate cuts has diminished. The market continues to anticipate a total of four 25-basis-point rate cuts throughout 2024, with expectations unchanged.
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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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(Photo credit: Intel)
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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)
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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.
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 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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(Photo credit: Infineon)
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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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(Photo credit: Loongson Zhongke Technology)