NVIDIA CEO Jensen Huang’s current personal worth has exceeded the entirety of Intel. According to reports from TechNews, Tom’s Hardware, Huang’s current net worth has reached USD 109.2 billion, more than Intel’s total market cap of around USD 96 billion.

In early August, Intel has faced its most serious financial troubles in 50 years, with its stock prices plummeting 22%. In order to attract foundry customers, the company will transform its foundry business into a wholly-owned subsidiary with its own board of directors.

According to Tom’s Hardware, social media users have been sharing posts encouraging Jensen Huang to buy Intel. Currently, Huang holds more than 75 million NVIDIA share, with 786 million more through various trusts and a partnership. Even though he has cashed in more than USD 700 million by selling 6 million shares this year, it is merely a tiny fraction compared with the total value of his NVIDIA holdings of over USD 100 billion.

According to Forbes’ real-time billionaires list, Huang’s net worth currently ranks 11th in the world, just USD 20 billion away from breaking into the top ten. With growth driven by the AI boom, NVIDIA has become one of the largest tech companies by market capital in the world, alongside Microsoft, Apple, Amazon, and Google.

According to TrendForce, NVIDIA continues to remain the dominant supplier in the global AI server market in 2024. Specifically, in the GPU AI server market, NVIDIA commands an overwhelming lead with a nearly 90% market share, while AMD follows at a distant 8%.

(Photo credit: NVIDIA)

Rumors have been circulating that NVIDIA has stopped taking orders for its H20 chips customized for China since August. Now, according to the latest report by Bloomberg, regulators in China have been advising companies against buying H20, as part of the country’s strategy to bolster its semiconductor industry and respond to further US sanctions.

As the initiative aims to boost the market share of domestic Chinese AI chip manufacturers, Huawei and Cambricon Technologies, which are leading AI processor makers in China, may turn out to be the major beneficiaries, Bloomberg suggests.

Beijing’s approach has been more of a guideline than a strict prohibition, as the authority still hopes to support its own AI startups, the report notes.

However, it is indicated that in recent months, several Chinese regulators, including the Ministry of Industry and Information Technology, did issue the so-called “window guidance”—informal instructions that lack legal authority—to minimize the use of NVIDIA.

It is worth noting that China has a thriving AI sector amid US restrictions. Major tech player like ByteDance and Alibaba are making significant investments, while numerous startups are vying for dominance. According to an earlier report by The Information, it is rumored that ByteDance has ordered over 200,000 NVIDIA H20 chips this year for AI model training, costing it over USD 2 billion.

In addition, there are six rising stars in the country’s development of large language models, which are crucial for generative AI, including 01.AI, Baichuan, Moonshot, MiniMax, Stepfun, and Zhipu, Bloomberg notes.

According to Bloomberg, some companies are disregarding the Chinese directive to avoid H20 chips, hastily acquiring more before a potential US sanction by the end of the year. However, they are also purchasing domestic Huawei chips to appease Beijing.

As early as in 2022, the US government prohibited NVIDIA from selling its most advanced AI processors to Chinese clients to curb Beijing’s technological progress. In response, the AI chip giant launched a series of AI chips tailored for the Chinese market, including H20, L20 and L2. According to a previous report by Wccftech, H20 GPU has 41% fewer Cores and 28% lower performance versus H100.

NVIDIA declined to comment to Bloomberg’s report, neither did China’s Ministry of Commerce, Ministry of Information and Technology, and Cyberspace Administration respond, Bloomberg notes.

In a separate statement, NVIDIA CEO Jensen Huang noted in an interview with Bloomberg Television that he is focused on serving customers in China while adhering to US government restrictions.

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(Photo credit: NVIDIA)

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)