When the global datacenter ai chip leader releases its third-quarter earnings for fiscal year 2025, all investors' attention is focused on this global highest market cap company's datacenter business sector, which has a market cap of 3.5 trillion dollars. $NVIDIA (NVDA.US)$ However, as Nvidia's datacenter business, which can be described as a "money-making tool," may begin to see a slowdown in growth due to a high base and excessive customer concentration, the market starts to look forward to Nvidia's next "explosive growth business."

Recently, the global trend of autonomous driving is booming, and therefore, Nvidia's auto chip business, which has long been considered "very low-key," is starting to be continuously mentioned by Wall Street analysts.

Q3 earnings report data shows that thanks to$Amazon (AMZN.US)$、 $Alphabet-A (GOOGL.US)$ 、$Microsoft (MSFT.US)$And the parent company of Facebook.$Meta Platforms (META.US)$The explosive demand for the intel H100/H200 and the newly launched Blackwell architecture AI GPU by large technology companies, who continue to invest heavily in the construction or expansion of AI datacenters around the world, shows no signs of waning in this global enthusiasm for artificial intelligence.

Nvidia's AI GPU is considered the most core hardware driving generative AI applications like ChatGPT. Nvidia's unparalleled 'explosive performance' over multiple quarters highlights the gradual onset of the AI era as heavyweight generative AI applications such as ChatGPT and Sora emerge one after another. Worldwide enterprises and core government departments continue to see explosive growth in demand for Nvidia's high-performance AI GPU, the most core infrastructure hardware for artificial intelligence.

Financial reports indicate that revenue from the datacenter business unit accounts for nearly 90% of intel's total revenue of 35 billion dollars in Q3. The datacenter business unit is currently intel's most core business unit, and it is the H100/H200 and Blackwell architecture AI GPUs provided by this unit that offer incredibly powerful AI computing infrastructure for datacenters globally.

The financial report shows that as the global wave of AI deployment gains momentum, this business segment's revenue increased by 112% year-on-year, reaching 30.8 billion dollars, although the growth rate has slowed compared to previous quarters. This figure significantly exceeds Wall Street expectations and also surpasses the combined revenue of intel and AMD.

The market is very bullish on Nvidia's automotive chip business amid the blazing wave of autonomous driving.

In contrast, nvidia's auto chip business only accounts for 1% of total revenue and has long been overlooked by investors. However, unlike the declining growth rate seen in the datacenter business, the growth rate of its auto chip business presents a textbook growth curve, with a year-on-year growth rate expanding to 72% in Q3 and a sequential increase of 30%, comparable to the astonishing growth rates of high-performance SoC auto chip competitors.$Qualcomm (QCOM.US)$The astonishing growth rate is similar.

An increasing number of Wall Street analysts state that as$Tesla (TSLA.US)$the wave of autonomous driving led by continues to sweep the world—especially after Trump's administration, the progress of the US government's approval for fully autonomous driving may accelerate significantly, and the demand for high-performance SoC auto chips may exhibit an exponential growth trend. Both nvidia's Orin chip and the Thor chip, which will begin mass production early next year, are considered 'the H100/H200 and Blackwell of the global auto industry' in terms of performance and popularity.

Therefore, the automotive chip business may become a crucial catalyst for Nvidia's vision of "diversified business," significantly alleviating Wall Street investment institutions' cautious sentiment due to Nvidia's performance overly relying on a few American tech giants like Microsoft, Amazon, and Google.

Although cars are still primarily made of steel, the silicon elements inside vehicles, especially in the trending "electric vehicles," are gradually becoming significant differentiators among various auto brands. Sophisticated infotainment and refined navigation systems represent early opportunities for chip manufacturers. Now, the intelligent features of electric vehicles based on "vehicle networking"—intelligence is making the functional indicators of electric vehicles increasingly comprehensive, and some electric vehicle models can even cover features that surpass those of smart phones. More importantly, the globally competitive pursuit of assistive driving and autonomous driving features has significantly increased the reliance on semiconductors for new complex systems.

Global electric vehicle leader Tesla (TSLA.US) and large tech companies like Google’s Waymo are driving the need for more automotive chips with higher TOPS AI computing power for autonomous driving functions.

According to the latest forecast data from S&P Global Mobility, by 2028, the value of the embedded chips in an average vehicle will significantly rise from approximately $500 in 2020 to $1,400, reflecting the direction of "intelligence" as the recent development trend in the automotive industry. If 0.1 billion vehicles are sold worldwide by then, this would represent an unprecedented market exceeding $140 billion, with an expansion speed comparable to that of the extremely hot datacenter AI chips.

The nvidia DRIVE Orin automotive chip, fully integrated with GPU, CPU, and deep learning accelerator (DLA), is regarded in the industry as the "supercomputer" for electric vehicles. Its highly integrated design allows it to handle a large number of parallel computing tasks and provides 254 TOPS of computing power.

Thanks to the Ampere architecture GPU and the efficient general computing performance provided by the Arm Cortex-A78AE core, the DRIVE Orin excels in high-load AI inference and high-performance computing tasks, meeting all high-performance demands, including advanced driver assistance systems (ADAS) and full autonomous driving (FSD). The DRIVE Orin supports autonomous driving from level L2 to L5, capable of processing complex AI algorithms such as image recognition, object detection, and path planning, ensuring the safe operation of vehicles in complex environments.

Nvidia's more powerful DRIVE Thor chip is planned for mass production in 2025. Currently disclosed information reveals that the Thor chip contains up to 77 billion transistors, provides up to 2000 TOPS (trillion operations per second) of AI computing power, fuses CPU, GPU, and an engine for processing Transformer large models, supports Multi-Instance GPU (MIG) technology, enabling efficient use and isolation of resources.

The Battle of the Automotive Chip Titans

Besides Tesla opting for a self-developed route, creating its own customized HW series SoC chips, many auto manufacturers heavily rely on nvidia's system-on-chip (SoC) to support the intelligent driving and infotainment systems of their brand vehicles, including $MERCEDES-BENZ GROUP AG UNSP ADR EACH REP 0.25 ORD SHS (MBGYY.US)$ 、 $VOLKSWAGEN A G (VWAGY.US)$ Jaguar Land Rover,$Volvo AB Unsponsored ADR Class B (VLVLY.US)$and traditional automotive giants like Hyundai. $BYD COMPANY (01211.HK)$ And the new electric vehicle forces from china such as Wei Xiaoli.

In addition to Nvidia, other chip giants are actively pursuing this potential market. Qualcomm, a chip giant focused on smartphone chips, has been increasing its investment in the automotive chip business in recent years, with a revenue of 0.899 billion USD from the automotive business in the last quarter, a 70% year-on-year growth. Although Nvidia CEO Huang Renxun can provide graphics processing and AI technology to support infotainment systems and up to L5 level of autonomous driving for automakers, Qualcomm's exclusive background in low-power mobile chips gives it a relative advantage in wireless connectivity and general processing power.

It is reported that in October, qualcomm announced a deep collaboration with google, a subsidiary of alphabet, to integrate qualcomm automotive chips with the android automotive operating system. nvidia's long-standing competitor in the pc field. $Intel (INTC.US)$ Supported by the automotive chip giant.$Mobileye Global (MBLY.US)$Is attempting to transform the advantages of camera systems into an equivalent advantageous position in the field of fully autonomous driving.

These chip giants are entering a promising new automotive market and focusing on the automotive chip market. This enables them to largely diversify their revenue channels and gain strong support from Wall Street for the stock prices and market value of these chip companies. For example, Nvidia will be able to reduce its dependence on a few giants: its top three customers account for more than a third of its revenue. Meanwhile, Qualcomm can take advantage of growth opportunities beyond the already mature smartphone market.

Leading electric vehicle and smart driving companies like tesla may try to launch their own exclusive internal systems, but as high-tech features in autos accelerate in popularity, other auto manufacturers will need ready-made integrated hardware and software solutions.

More importantly, for tesla and the new wave of car manufacturers in china, the autonomous driving function is a key step in applying powerful generative ai applications like chatgpt to the real world. Any new developments in this field are likely to have beneficial effects on humanoid robots and other potential ai terminal devices. For auto manufacturers, creating an outstanding autonomous driving system will be the foundation for mass-producing high-end ai industrial products like humanoid robots in the future.

However, while these futuristically focused opportunities have huge potential, there is still a long way to go. But with tesla's fsd major upgrade and the release of robotaxi, more importantly, as the influence of trump's ceo musk begins to span both political and business realms, fully autonomous vehicles are indeed becoming a reality, and may even accelerate development due to the likelihood of accelerating the review of tesla's fsd and robotaxi after trump returns to the white house.

According to informed sources, the transition team of elected president trump plans to make the federal framework for "fully autonomous vehicles" a top priority for review by the u.s. department of transportation.

Editor/Rocky