According to a report from The Wall Street Journal citing sources on August 13th, it’s revealed that Chinese internet companies and telecom operators have been testing Huawei’s latest processor, the “Ascend 910C,” in recent weeks. Reportedly, Huawei has informed potential customers that this new chip is comparable to NVIDIA’s H100 GPU, which cannot be directly sold in China.

Huawei’s ability to continue advancing its chip technology is a sign of its efforts to counter U.S. sanctions. However, the report also indicated that Huawei is already experiencing production delays with its current chips. The company faces additional U.S. restrictions, limiting its access to parts for production equipment and the latest memory used in AI hardware.

The sources cited by the same report point out that, TikTok’s parent company ByteDance, search giant Baidu, and state-owned telecom operator China Mobile are in preliminary talks with Huawei to secure the Ascend 910C chip. These negotiations suggest that Huawei could secure orders for more than 70,000 chips, valued at approximately USD 2 billion.

Reportedly, Huawei aims to begin shipping the Ascend 910C in October, but the final delivery schedule might differ from the initial plan and could be subject to adjustments.

Under U.S. sanctions, customers in China are forced to purchase the H20 from NVIDIA, which is a “downgraded” version of the AI chip designed specifically for the Chinese market.

Per a previous report from South China Morning Post, it’s expected that Chinese tech giants may be considering a shift towards local AI products, which could pose a challenge to NVIDIA. Currently, China accounts for 17% of NVIDIA’s revenue in the 2024 fiscal year, making the competition in the Chinese market increasingly fierce for NVIDIA.

Compared to NVIDIA’s customers in China, NVIDIA’s U.S. customers, such as OpenAI, Amazon, and Google, will soon have access to NVIDIA’s latest Blackwell architecture chips, including new products like the GB200, which NVIDIA claims offer significantly improved performance compared to existing products.

Meanwhile,  Wall Street Journal also has cited sources, pointed out that NVIDIA is working on another China-oriented chip called B20, but the design might have trouble getting U.S. approval for China export if the regulations are further tighten.

Read more

• [News] NVIDIA Reportedly Developing Tailored Version of the Blackwell Series for Chinese Market
• [News] U.S. Reportedly Enhancing Chip Export Restrictions to China, while NVIDIA’s H20 Might Get Banned

(Photo credit: NVIDIA)

Is the AI bubble about to burst? Two years after OpenAI launched ChatGPT, sparkling a surge in generative AI startups, China has now seen a wave of closures on AI companies. According to a report by Commercial Times, citing Chinese media TMTPost, nearly 80,000 AI companies in China have registered and then either closed down or suspended operations within the past 600 days.

The reports note that according to the data from the National Enterprise Credit Information Publicity System of China, between November 30, 2022, the release date of ChatGPT, and July 29, 2024, a total of 78,612 AI-related companies in China, which were newly registered during this period, are now in a deregistered or abnormal business status. This accounts for 8.9% of the 878,000 AI companies registered during the same period.

The current adversity for the AI companies in China, the reports suggest, could be attributed to excessive spendings regarding high computational costs and R&D investments, declines in venture capital leading to a funding freeze, and difficulties in achieving profitability.

According to the reports, over the past three years, more than 200,000 AI-related companies in China have been deregistered or revoked, with a total of 353,000 AI-related companies disappearing within the past decade.

On the other hand, as of August 7th, there are said to be 300,700 new AI companies registered in 2024. Currently, there are 1,804,300 AI-related companies in existence in China, the reports state.

Among them, over 4,500 companies are officially recognized as part of the AI industry system. More than 180 large generative AI models, which have completed registration and be online to provide public services, have been developed, with a registered user base exceeding 564 million.

Wang Xiaochuan, founder of Chinese search engine company Sogou, once stated in 2023 that the Large Language Model (LLM) for AI would undergo an “elimination tournament” in China, with the top tier likely consisting of no more than five companies, according to a report on Soho.

Baidu CEO Robin Li also mentioned in July that China has too many large language models, calling for tech leaders to focus more on building real-world applications driven by AI. A report by South China Morning Post, quoting Li, said that since the launch of ChatGPT in late 2022, China’s generative AI market has become crowded with over 200 large language models.

Read more

• [News] China Reportedly Imposes Mandatory AI Model Reviews on ByteDance, Alibaba, and Others

(Photo credit: )

According to a report from Reuters citing sources on August 7th, American chip giant Intel had an opportunity to invest in OpenAI several years ago but ultimately had the investment rejected by company executives, resulting in a missed opportunity.

Reportedly, Intel and OpenAI discussed collaboration several times between 2017 and 2018. At that time, OpenAI was still a nascent nonprofit research organization focused on developing relatively unknown generative AI technologies.

The discussions included Intel potentially purchasing a 15% stake in OpenAI for USD 1 billion in cash and possibly producing hardware for OpenAI at cost in exchange for an additional 15% stake.

Sources cited by the report further reveal that OpenAI was very interested in Intel’s investment, primarily because it would reduce the company’s reliance on NVIDIA chips and enable OpenAI to build its own infrastructure.

However, Intel ultimately rejected the deal. One reason cited by the report was that then-CEO Bob Swan did not believe generative AI could be commercialized in the short term and was concerned that Intel’s investment would not yield returns. Another reason was that Intel’s data center division was unwilling to produce hardware for OpenAI at cost.

After Intel’s refusal, Microsoft began investing in OpenAI in 2019. In 2022, OpenAI launched the chatbot ChatGPT, reportedly sparking a global AI boom and achieving a valuation of USD 80 billion. Per the data from CB Insights, it has made OpenAI the third most valuable tech startup worldwide, behind only ByteDance and SpaceX.

Neither Intel nor OpenAI has commented on these reports.

As per a previous report from The Atlantic, Intel had previously declined to produce processors for Apple’s iPhone, a misstep that caused Intel to miss the opportunity to transition into the mobile area.

The news from Reuters this time further suggests that Intel has made a similar mistake in the AI domain.

Read more

• [News] Intel’s 18A to Start Production in 2025, Featuring Processors for AI PCs and Servers
• [News] Intel’s Earnings Fall Short, Cutting Over 15% of Workforce

(Photo credit: Intel)

Apple’s latest technical document reveals that the two main AI models behind Apple Intelligence are trained using Google’s Tensor Processing Units (TPUs) instead of NVIDIA GPUs. According to a report from Commercial Times, this suggests that the demand for NVIDIA chips has outstripped supply, prompting some tech giants to seek alternatives.

Apple first introduced an AI technical document in June, briefly stating that its AI models were trained using TPUs. The latest technical document, which spans 47 pages, provides a detailed explanation of how Apple’s foundational models (AFM) and AFM servers are trained in Cloud TPU Clusters. This indicates that Apple rents cloud servers from cloud service providers to train its AI models.

In the document, Apple stated: “This system allows us to train the AFM models efficiently and scalably, including AFM-on-device, AFM-server, and larger models.”

Apple further mentioned that the on-device AFM models for iPhones and iPads are trained using a total of 2,048 TPUv5p chips, which are currently the most advanced TPU chips on the market. The AFM servers are trained using a total of 8,192 TPUv4 chips.

Google initially launched TPUs in 2015 for internal training use only and started offering TPU rental services to external clients in 2017. These TPUs are currently the most mature custom chips used for AI training. According to Google’s official website, the rental cost of their most advanced TPUs is approximately USD 2 per hour based on a three-year contract.

Though NVIDIA’s GPUs are currently dominating the high-end AI chip market, the enormous number of chips required for AI model training has led to a severe shortage. This is because major tech companies like OpenAI, Microsoft, Google, Meta, Oracle, and Tesla all use NVIDIA chips to develop their AI technologies.

Since the rise of ChatGPT at the end of 2022, which spurred the generative AI market, Silicon Valley tech giants have been racing to invest in AI research and development. In contrast, Apple has lagged behind its competitors and now has to intensify its efforts to bolster Apple Intelligence. On July 29th, Apple released a preview version of Apple Intelligence for certain devices.

Read more

• [News] NVIDIA’s H200 Order Delivered from Q3, Boosting Server Supply Chain with Strong Demand
• [News] US Government Reportedly Investigating Microsoft, NVIDIA, and OpenAI for AI Industry Monopolization

(Photo credit: NVIDIA)

According to a report from The Information, generative AI application giant OpenAI has held talks with several chip designers, including Broadcom, to discuss plans for developing new AI chip.

It’s reported that OpenAI is currently exploring the possibility of manufacturing its own AI chip. This move would not only allow for efficient integration of software and hardware,  but also help alleviate the current shortage of AI chips. Moreover, OpenAI is said to be actively recruiting former Google employees, hoping to leverage their experience and expertise in developing Tensor processors to create its own AI chip.

The report emphasized that there is little possibility for OpenAI to develop AI server chip that can rival that of NVIDIA, and it would take years of research and development to achieve any significant results.

However, OpenAI might be able to shorten the development time by actively drawing in former talents from Google and harnessing their expertise and experience in developing Tensor processors.

Previously, the industry pointed out that OpenAI CEO Sam Altman has formulated an ambitious AI chip development plan, aiming to raise USD 7 trillion to renovate the global semiconductor industry ecosystem and promote the development of the general AI industry.

Sam Altman also stated that this USD 7 trillion would bring about considerable investment in AI, enabling the fabrication of AI chip and the construction of AI-related infrastructures, which will ultimately translate into vast services to the world and substantial value to everyone.

Read more

• [Insights] OpenAI CEO’s Ambition to Build Semiconductor Plant Grows Stronger
• [News] OpenAI Reportedly Expected to Gather with Samsung and SK Group for Deepened Chip Collaboration

(Photo credit: Broadcom)