As the U.S. and its allies continue to impose technology restrictions on China’s semiconductor sector, Beijing has accelerated its efforts to develop homegrown alternatives. Chinese firms are aggressively pursuing advanced AI chip development, aiming to rival Nvidia, the global leader in AI semiconductors. A recent CNBC report highlighted seven Chinese companies to watch, including Huawei and Alibaba.

Huawei, the first of Nvidia’s Chinese challengers, is gaining attention with its new Ascend 910C AI chip, which is expected to compete with Nvidia’s H100.

Alibaba follows closely behind. After acquiring C-Sky Microsystems in 2018, the company integrated it with its in-house chip division to form T-Head. In 2019, T-Head launched its first AI inference chip, the Hanguang 800, which has since been deployed at scale in Alibaba’s hyperscale data centers.

Baidu ranks third with its self-developed AI chip, Kunlun. The chip has matured significantly, and in June, Baidu received a strategic investment from Beijing’s AI Industry Investment Fund, marking the first time a state-owned entity has invested in an AI chip firm, boosting Baidu’s growth prospects.

Biren Technology, in fourth, focuses on GPUs like Nvidia, with a software platform to build applications on top of its hardware. Biren’s Bili series of chips are designed for AI training in data centers. Last week, Biren registered for IPO guidance with the Shanghai Securities Regulatory Bureau, marking the start of its public listing journey.

Cambricon Technologies, ranked fifth, designs a wide range of semiconductors, from chips that train AI models to those running AI applications on devices. Known as China’s first AI chip stock, Cambricon has faced setbacks since being blacklisted by the U.S. in late 2022, with reports of large-scale layoffs last year.

Moore Threads, founded in 2020, is developing GPUs for training large AI models. Its data center product, MTT KUAE, integrates GPUs and is aimed at competing with Nvidia.

Enflame Technology, the seventh company on the list, positions itself as a domestic alternative to Nvidia, focusing on AI training chips for data centers. Enflame began IPO guidance on August 26, and is expected to list on the STAR Market alongside Biren either by the end of this year or early next year.

(Photo credit: Huawei)

While all eyes are on Intel’s restructuring plan, which features the foundry unit’s spin-off and the delay of Germany and Poland factories, there is another critical decision regarding its photonics business.

According to Intel’s announcement, the tech giant is moving Integrated Photonics Solutions (IPS) into its Data Center and Artificial Intelligence division (DCAI), as it tries to drive a more focused R&D plan that’s fully aligned with its top business priorities.

This shuffle seems to be reasonable, as earlier this year, Intel has achieved a milestone in integrated photonics technology for high-speed data transmission, and the two arenas seem to be inseparable.

A few months ago, Intel demonstrated the industry’s most advanced and first-ever fully integrated optical compute interconnect (OCI) chiplet co-packaged with an Intel CPU and running live data. According to Intel, the OCI chiplet represents a leap forward in high-bandwidth interconnect by enabling co-packaged optical input/output (I/O) in emerging AI infrastructure for data centers and high performance computing (HPC) applications.

A report by Photonics Spectra notes that Intel’s IPS division focuses on technologies such as light generation, amplification, detection, modulation, CMOS interface circuits, and package integration.

Here’s why this technology matters: As chipmakers advance Moore’s Law, increasing transistor density, signal loss during transmission becomes a significant issue because chips use electricity to transmit signals. Silicon photonics technology addresses this problem by using optical signals instead of electrical ones, allowing for high-speed data transmission, greater bandwidth, and faster data processing.

Intel has been developing silicon photonics technology for over 30 years. Since the launch of its silicon photonics platform in 2016, Intel has shipped over 8 million photonic integrated circuits (PICs) and more than 3.2 million integrated on-chip lasers, according to its press release. These products have been adopted by numerous large-scale cloud service providers.

In addition to Intel, rivals such as AMD and TSMC are also accelerating the development of next-generation silicon photonic solution.

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(Photo credit: Intel)

ByteDance, the parent company of TikTok, is said to be collaborating with TSMC, eyeing for the mass production of two self-developed AI chips by 2026, according to reports by Economic Daily News and The Information.

ByteDance’s AI chips are expected to be made with TSMC’s 5nm node, which would be one generation behind the foundry giant’s most advanced process, the reports suggest, making the move comply with the U.S. export regulations to China. The chips are similar to NVIDIA’s next-generation flagship AI chip, Blackwell, which are manufactured with TSMC’s 4NP node.

Citing sources familiar with the matter, the reports note that the tech giant in China aims to reduce its reliance on NVIDIA for AI model development. Though the chips are still in the design phase and the plan is subject to change, ByteDance’s self-designed chips could save billions of dollars compared to purchasing NVIDIA’s products, according to the reports.

The Information estimates that ByteDance’s spending on developing generative AI models has been increasing, and it is rumored that the company has ordered over 200,000 NVIDIA H20 chips this year, costing it over USD 2 billion, with some orders still pending delivery.

In response to US export bans, NVIDIA launched AI chip H20, L20 and L2, specially designed for the Chinese market earlier this year. According to a previous report by Wccftech, H20 GPU has 41% fewer Cores and 28% lower performance versus H100. Still, the product is reportedly seeing strong demand for AI servers among Chinese Cloud Service Providers (CSPs) and enterprises, including Huawei and Tencent.

However, due to its lower computing power, Chinese companies need to purchase more H20 chips to build clusters with equivalent computing capacity, which raises costs, Economic Daily News notes.

According to TSMC’s financial report in the second quarter, North American clients contributed 65% of its total revenue. While China, the second-largest market, contributed 16% of its quarterly revenue, with a significant jump from 9% in the first quarter and 12% during the same period last year.

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(Photo credit: ByteDance)

According to a report from wccftech, AMD CEO Lisa Su has indicated that she believes the AI Supercycle has just started, and the company has accelerated its product development plans to meet the substantial market demand.

In addition to NVIDIA, AMD is a significant player in the AI market as well. This is not only due to its market impact but also because the company has significantly expanded its AI product portfolio over the past few quarters, attracting attention from major clients like Microsoft and Amazon.

While AMD has not yet replicated NVIDIA’s success in the market, the company remains optimistic about the future, which is why it believes the AI boom has only just begun.

A few months ago, AMD outlined its AI chip development roadmap for the next year. The “Advancing AI” event in this October will showcase the next-generation Instinct MI325X AI chip.

The flagship Instinct MI350 AI chip is scheduled for release in 2025, followed by the Instinct MI400 AI chip in 2026. Despite AMD’s advancements, there remains a generational gap, as competitor NVIDIA is poised to launch its Blackwell architecture AI chips in the coming months.

This move is particularly noteworthy as AMD is focusing on competing with NVIDIA’s CUDA on the software front.

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(Photo credit: AMD)

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)