NVIDIA has officially crossed the $1 trillion market capitalization threshold, marking its prominent ascent in the realm of semiconductor technology, particularly within the artificial intelligence (AI) computing sectorThis remarkable achievement not only emphasizes NVIDIA’s leadership in the global chip market but also resonates with the ongoing trend of AI development worldwide, persuading investors to place their bets on companies at the forefront of this technological revolution.
On May 24, NVIDIA reported its earnings for the first quarter of the 2024 fiscal year, ending April 30, 2023. The company recorded a revenue of $7.192 billion, which, while down 13% from $8.288 billion year-on-year, showed a substantial 19% increase from the previous quarter's $6.051 billionMore impressively, NVIDIA's net profit soared to $2.043 billion, reflecting a substantial year-on-year increase of 26% and a commendable 44% rise from the preceding quarter.
However, the true surprise came from NVIDIA's optimistic revenue projections for the following quarterThe company anticipates that revenue for the second fiscal quarter of 2024 will reach $11 billion, with a variation of 2%. This forecast signifies an impressive 64% growth compared to the same period last year and is expected to set a new record for the highest quarterly revenue in NVIDIA's historyPrevious analyst expectations only predicted revenue amounts averaging around $7.15 billionFollowing the earnings report, NVIDIA’s stock soared in after-hours trading, showing a leap of up to 30% at one point, further highlighting the market’s positive reception to its ambitious outlook.
On May 25, shares continued to rally, propelling the company’s market capitalization to an astonishing $939.2 billion, accounting for an increase of $184 billion over just one trading day
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By May 30, NVIDIA's market value temporarily breached the $1 trillion mark, making it the fifth U.S. company to achieve such a valuation following tech giants like Apple, Microsoft, Alphabet (Google's parent company), and Amazon.
The surge in NVIDIA's stock can be attributed to the consensus that AI models are leading a transformative wave in computingInstitutional analysts, such as those at Minsheng Securities, noted that the market now recognizes the clear demand for AI computing power, and NVIDIA is poised to deliver on this front more decisively than ever.
Within this AI-powered landscape, companies that manufacture AI chips have emerged as significant beneficiaries in the ongoing technological tideGPUs, in particular, have become crucial players in the AI sectorAs NVIDIA captures a significant share of AI computing power, it now forms the backbone of numerous technology firms globally, underscoring its essential role.
NVIDIA's Chief Financial Officer, Colette Kress, highlighted that the demand for computational power driven by generative AI is experiencing exponential growthThis demand is swiftly transitioning to the GPU market, and NVIDIA's advancements in GPU technology place the company at a significant advantage, leading to heightened demand for its products.
NVIDIA's distinct strategy involves harnessing its GPU capabilities along with a combination of CPU (Central Processing Unit) and DPU (Data Processing Unit). The company is constructing a “three-chip” architecture aimed at enhancing performanceThis innovative strategy signifies not only augmentation in product offerings but also a synchronized approach to maximizing performance through the collaborative use of GPUs, CPUs, and DPUs.
On May 29, during the COMPUTEX 2023 conference, NVIDIA's founder and CEO Jensen Huang proclaimed a narrowing shift in the computing paradigm, suggesting that the era of CPU-expansion is behind us
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Huang implied that we have reached a pivotal point in the generative AI explosion, with a burgeoning computational need emerging across all spheres of the globe.
At the conference, NVIDIA unveiled its groundbreaking supercomputer, the DGXGH200, which is currently regarded as the world's most powerful computing systemThis system is designed to cater to the training requirements of expansive AI modelsHuang's pronouncements not only marked a technological milestone but also heralded a new epoch in computing.
As we witness this AI-driven industrial revolution unfold on a global scale, NVIDIA's trajectory has mirrored the enthusiasm seen in the A-share market, where AI has emerged as a key investment theme in the first half of 2023. Analysts from Huachuang Securities commented on the explosive wave of AI triggered by the introduction of ChatGPT, leading to a significant increase in cloud computing and storage data, thus expediting the growth rates of upstream AI computing and storage chips.
As the 2023 AI landscape developed, leveraging advanced technology became essential to keep pace with this rapid growthData, computational power, and algorithms are recognized as the triad of foundations for AIThe evolution of large language models has ushered in a revolution in individual productivity, propelling enormous potential for applicationThe continuous advancement in model parameters has exacerbated the demand for higher computational training capabilities, ultimately driving investment opportunities in computational power chips.
On May 26, Huawei's chief technology officer for its Ascend computing division, Zhou Bin, remarked that the surge in large AI model trends is augmenting the demand for computational power, characterized by substantial value rather than being a temporary phenomenon
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He introduced a new principle termed the "AI computing power growth curve," suggesting that AI computing demand doubles approximately every four months, indicating a significant acceleration compared to the traditional Moore's Law.
Looking ahead, both domestic and international trends can validate the performance of the computational power industryWith no ceiling on the demand for computing power, the compelling performance metrics bolster investor confidence, as the industry stands at the cusp of a monumental long-term growth trajectory.
CITIC Securities delineated the demand for AI model computational power in three distinct phasesThe initial phase, before 2010, involved a gradual rise in demand as machine deep learning was not widely adoptedThis was followed by a transformation when deep learning models began to dominate traditional areas such as natural language processing and computer vision between 2010 and 2015. The latest phase, post-2016, has witnessed the AI model's shift into a realm of massive parameters, causing a tremendous spike in computational needs.
With the advent of ChatGPT in November 2022, a race has ignited among leading tech companies and startups to acquire NVIDIA's A100 chips, which are touted as global leaders specifically engineered for generative AI tasks.
Huang noted, “2022 was a trying year for us; however, with the introduction of OpenAI’s ChatGPT, we swiftly shifted towards tremendous demand in short order.” The rising intelligence and human-like characteristics of AI models, highlighted by their emergent capabilities, are further complemented by the notable growth in parameters.
Following the launch of models like GPT-3, we have entered an era of large language models characterized by hundreds of billions of parameters
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