Last Wednesday, Nvidia's market capitalization crossed the $3 trillion mark, surpassing Apple and jumping to the second largest market value in the world. In the days that followed, Nvidia was one step away from overtaking Microsoft to become the world's No. 1 market capitalization, and the market is generally optimistic about its future, especially the upcoming stock split, which is seen as a key move to drive the stock price up further.
Nvidia's market capitalization soared
Nvidia has fulfilled an unprecedented myth in the U.S. stock market. Previously, it took Apple more than two years to move from $2 trillion to $3 trillion, and in three months, Nvidia created a miracle.
The soaring market value of Nvidia lies in the gradual dissolution of its divergence in the capital market. The stellar results, amazing products, and the stimulation of investors' enthusiasm for trading by stock splits have convinced Wall Street that it can continue to break the "ceiling".
From the perspective of performance fundamentals, Nvidia's total revenue in the first quarter recorded $26 billion, more than three times that of a year ago, and Nvidia, which sells "AI arms", is stepping towards the peak step by step, and has not slowed down at all, and this figure will continue to climb to $28 billion in the second quarter.
At the same time, CEO Jensen Huang's worth has also risen, with a net worth of more than $100 billion, making him one of the 16 "super-rich" on the Forbes list of the world's richest people with assets of more than $100 billion.
On June 2, less than 3 months after the announcement of the 2024 Taipei International Computer Show, Blackwell is already on the way to mass production. What's more, Nvidia will update a new generation of products every year, and a three-year upgrade plan has surfaced: Blackwell will be launched in 2025 Ultra, the new architecture Rubin will be iterated in 2026, and Rubin will be launched in 2027 Ultra。
At the same time, in order to continue to consolidate the moat, Nvidia has long turned itself into an "AI factory". Based on GPU and CUDA, users can continuously connect computing power in series to form a huge data center and become a "power station" in the AI era.
Whether it is the pursuit of the ultimate in software and hardware ecology, or the rhythm of annual upgrades, NVIDIA does not leave opponents with a chance to breathe.
Wall Street was excited about this, and BofA raised its price target on Nvidia to $1,500. Analysts believe that AI is developing rapidly, and many top technology and cloud computing companies are still in the experimental stage of training large language models, so the peak of AI in the chip industry has not yet arrived.
It is estimated that the computing power update demand of global data centers will cost about 250 billion to 500 billion US dollars per year, and only 20-30% has been completed at present, and it will take 3-5 years to complete it in the future.
Institutions generally believe that it is only a matter of time before Nvidia surpasses Microsoft to become the world's largest market capitalization. Nvidia announced that it will "split 10 from 1" on June 7 to allow more retail investors to catch its own express and provide impetus for the stock price to continue to soar. The stock split will also make it easier for Nvidia to join the Dow Jones index and strengthen its position in the U.S. capital market.
This series of layouts is an all-round preparation for NVIDIA to become the "number one player" in the global capital market.
A rapidly changing market
Semiconductors are also a highly cyclical industry. Whether it's crypto or the wave of gaming during the pandemic, Nvidia has experienced large fluctuations in revenue and profits amid short-term surges in demand. The bursting of the cryptocurrency bubble in 2021 caused Nvidia to be abandoned by the market, and its stock price fell from an all-time high of $835 to less than $200 in half a month.
At present, Nvidia is still in a state of "not worrying about selling" when revenue and profit margins continue to hit new highs, and products are in short supply.
However, the existence of the cycle indicates that if Nvidia wants to continue to refresh history, sales and profit margins must maintain a momentum of rapid growth, and at the same time make its moat high. On the way to the top, Nvidia is facing a series of problems from industry trends, rival siege, resource bottlenecks and so on.
At present, NVIDIA occupies more than 70% of the market share of AI training chips, and the market share of its data center GPUs is an overwhelming 92%. It's hard not to be coveted by your opponents.
At the beginning of June, AMD unveiled the new MI350X AI acceleration chip, compared with NVIDIA's strongest AI chip H200, memory, bandwidth, and computing performance have been doubled, and like NVIDIA, AMD also said that it aims to release products once a year; Intel also revealed that its Gaudi The price of 3AI chips will be much lower than that of competitors, and it is planned to be listed on a large scale in the third quarter of this year. According to the official positioning, the performance of this chip is 1.5 times that of Nvidia H100, which is comparable to H200.
Not only that, Microsoft, Amazon, Google, Meta and other major Nvidia customers who have no better choice and are "stuck" by Nvidia have also begun to "make their own arms", design AI chips and entrust manufacturers to produce them, trying to get rid of their dependence on Huang Sect Master.
More importantly, after experiencing the 100-model war, both technology giants and AI start-ups have entered a cooling-off period to find scenarios for large models.
Sequoia Capital estimated in March that AI startups were sending $50 billion to Nvidia to train large language models, but only a meagre $3 billion in revenue from the market.
In other words, in this vigorous "arms race", players must rethink the reality of making a profit. If commercialization is delayed, Nvidia may not be able to escape the cycle of cycles.
Jingtai Investment Advice|Challenges and risks coexist
Despite the boom in investment in AI, uncertainty over the commercialization process could weigh on long-term growth expectations, especially as AI startups face profitability challenges, and Nvidia may also feel indirect pressure as an upstream supplier.
Short-term: Given NVIDIA's current market position, technology leadership, and the positive impact of market sentiment, investors can consider buying dips and taking advantage of market volatility to operate tactically in the short term, but need to pay close attention to industry dynamics and changes in the competitive situation.
Medium-term: It should pay attention to the pace of product upgrades, market acceptance, and industry demand trends, especially in the development of data centers and AI applications, and the medium-term investment strategy should focus on evaluating whether it can continue to maintain its innovative advantages and stable market share growth.
Long-term: Considering the long-term development of the AI industry and NVIDIA's central position in it, long-term investors should focus on the company's R&D capabilities, ecosystem expansion, and ability to respond to cyclical fluctuations in the industry. At the same time, pay attention to diversifying your portfolio to reduce the concentration risk of a single stock.
