[News] Pioneering an AI Era: Assessing the Prosperity and Challenges of the NVIDIA

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Last year’s AI boom propelled NVIDIA into the spotlight, yet the company finds itself at a challenging crossroads.

According to a report from TechNews, on one hand, NVIDIA dominates in high-performance computing and artificial intelligence, continuously expanding with its latest GPU products. On the other hand, global supply chain instability, rapid emergence of competitors, and uncertainties in technological innovation are exerting unprecedented pressure on NVIDIA.

NVIDIA’s stock price surged by 246% last year, driving its market value past USD 1 trillion and making it the first chip company to achieve this milestone. According to the Bloomberg Billionaires Index, NVIDIA CEO Jensen Huang’s personal wealth has soared to USD 55.7 billion.

However, despite the seemingly radiant outlook for the NVIDIA, as per a report from TechNews, it still faces uncontrollable internal and external challenges.

• Internal Concern 1: CoWoS, HBM Capacity Bottlenecks

The most apparent issue lies in capacity constraints.

Currently, NVIDIA’s A100 and H100 GPUs are manufactured using TSMC’s CoWoS packaging technology. However, with the surge in demand for generative AI, TSMC’s CoWoS capacity is severely strained. Consequently, NVIDIA has certified other CoWoS packaging suppliers such as UMC, ASE, and American OSAT manufacturer Amkor as backup options.

Meanwhile, TSMC has relocated its InFo production capacity from Longtan to Southern Taiwan Science Park. The vacated Longtan fab is being repurposed to expand CoWoS capacity, while the Zhunan and Taichung fabs are also contributing to the expansion of CoWoS production to alleviate capacity constraints.

However, during the earnings call, TSMC also stated that despite a doubling of capacity in 2024, it still may not be sufficient to meet all customer demands.

In addition to TSMC’s CoWoS capacity, industry rumors suggest that NVIDIA has made significant upfront payments to Micron, SK Hynix, to secure HBM3 memory, ensuring a stable supply of HBM memory. However, the entire HBM capacity of Samsung, SK Hynix, and Micron for this year has already been allocated. Therefore, whether the capacity can meet market demand will be a significant challenge for NVIDIA.

• Internal Concern 2: Major Customers Shifting Towards In-house Chips

While cloud service providers (CSPs) fiercely compete for GPUs, major players like Amazon, Microsoft, Google, and Meta are actively investing in in-house AI chips.

Amazon and Google have respectively introduced Trainium and TPU chips, Microsoft announced its first in-house AI chip Maia 100 along with in-house cloud computing CPU Cobalt 100, while Meta plans to unveil its first-generation in-house AI chip MTIA by 2025.

Although these hyperscale customers still rely on NVIDIA’s chips, in the long run, it may impact NVIDIA’s market share, inadvertently positioning them as competitors and affecting profits. Consequently, NVIDIA finds it challenging to depend solely on these hyperscale customers.

• External Challenge 1: Export Control Pressures Lead to Loss of Chinese Customers

Due to escalating tensions between the US and China, the US issued new regulations prohibiting NVIDIA from exporting advanced AI chips to China. Consequently, NVIDIA introduced specially tailored versions such as A800 and H800 for the Chinese market.

However, they were ultimately blocked by the US, and products including A100, A800, H100, H800, and L40S were included in the export control list.Subsequently, NVIDIA decided to introduce new AI GPUs, namely HGXH20, L20 PCIe, and L2 PCIe, in compliance with export policies.

However, with only 20% of the computing power of H100, they are planned for mass production in the second quarter. Due to the reduced performance, major Chinese companies like Alibaba, Tencent, and Baidu reportedly refused to purchase, explicitly stating significant order cuts for the year. Consequently, NVIDIA’s revenue prospects in China appear grim, with some orders even being snatched by Huawei.

Currently, NVIDIA’s sales revenue from Singapore and China accounts for 15% of its total revenue. Moreover, the company holds over 90% market share in the AI chip market in China. Therefore, the cost of abandoning the Chinese market would be substantial. NVIDIA is adamant about not easily giving up on China; however, the challenge lies in how to comply with US government policies and pressures while meeting the demands of Chinese customers.

As per NVIDIA CEO Jensen Huang during its last earnings call, he mentioned that US export control measures would have an impact. Contributions from China and other regions accounted for 20-25% of data center revenue in the last quarter, with a significant anticipated decline this quarter.

He also expressed concerns that besides losing the Chinese market, the situation would accelerate China’s efforts to manufacture its own chips and introduce proprietary GPU products, providing Chinese companies with opportunities to rise.

• External Challenge 2: Arch-Rivals Intel and AMD Begin Their Offensive

In the race to capture the AI market opportunity, arch-rivals Intel and AMD are closely after NVIDIA. As NVIDIA pioneered the adoption of TSMC’s 4-nanometer H100, AMD quickly followed suit by launching the first batch of “Instinct MI300X” for AI and HPC applications last year.

Currently, shipments of MI300X have commenced this year, with Microsoft’s data center division emerging as the largest buyer. Meta has also procured a substantial amount of Instinct MI300 series products, while LaminiAI stands as the first publicly known company to utilize MI300X.

According to official performance tests by AMD, the MI300X outperforms the existing NVIDIA H100 80GB available on the market, posing a potential threat to the upcoming H200 141GB.

Additionally, compared to the H100 chip, the MI300X offers a more competitive price for products of the same level. If NVIDIA’s production capacity continues to be restricted, some customers may switch to AMD.

Meanwhile, Intel unveiled the “Gaudi3” chip for generative AI software last year. Although there is limited information available, it is rumored that the memory capacity may increase by 50% compared to Gaudi 2’s 96GB, possibly upgrading to HBM3e memory. CEO Pat Gelsinger directly stated that “Gaudi 3 performance will surpass that of the H100.”

• External Challenge 3: Startup Underdogs Form AI Platform Alliance in Attempt to Conquer

Several global chip design companies have recently announced the formation of the “AI Platform Alliance,” aiming to promote an open AI ecosystem. The founding members of the AI Platform Alliance include Ampere, Cerebras Systems, Furiosa, Graphcore, Kalray, Kinara, Luminous, Neuchips, Rebellions, and Sapeon, among others.

Notably absent is industry giant NVIDIA, leading to speculation that startups aspire to unite and challenge NVIDIA’s dominance.

However, with NVIDIA holding a 75-90% market share in AI, it remains in a dominant position. Whether the AI Platform Alliance can disrupt NVIDIA’s leading position is still subject to observation.

Read more

• [News] NVIDIA’s Exclusive Chips for China Now Reported to be Available for Pre-Order, Priced Similar to Huawei Products
• [News] NVIDIA CEO Jensen Huang Meets with TSMC Executives in Taiwan, Addressing the Significant AI Chip Shortage

(Photo credit: NVIDIA)