Big news, big news! If you have some spare cash and are nervously watching tech stocks, afraid of missing the wave in 2026 that could change your financial destiny, you must watch this video from start to finish without skipping a second.
Yesterday, NVIDIA just announced earnings, and the stock price jumped 6%! The whole market is buzzing, everyone shouting that AI is still accelerating. But that's not all. At Computex, Jensen Huang dropped an even bigger bombshell—the all-new RTX Spark super PC chip, squeezing monster-level AI computing power into the laptops and desktops we ordinary people use every day! At the same time, he made a bold prediction: Physical AI could be worth tens of trillions of dollars, and robotics will fully explode within five years!
Meanwhile, Google's parent company Alphabet made a rare $80 billion equity raise to fully invest in AI infrastructure. Buffett's Berkshire Hathaway directly put in $1 billion to participate! In China, the Southern China Sci-Tech Chip ETF also opened higher and strengthened, surging 1.42% with a net inflow of 152 million yuan.
Folks, this is not a story. This is a global AI drama, and NVIDIA is the person standing at the center of the stage. Today's episode will thoroughly dissect the entire logic around NVIDIA from beginning to end. After listening, you should have a more comprehensive and deeper understanding of the current situation, NVIDIA's true position, and the future direction of AI.
Let's get straight to the meat! How strong was NVIDIA's earnings report yesterday? In-depth review. Yesterday, as soon as NVIDIA released its earnings, the stock price jumped 6%, and trading volume expanded significantly. Why was the market reaction so intense? Let's break it down.
Four words: demand explosion. The data center business remains the absolute main force. There are no signs of slowing demand for AI training and inference computing power; instead, it is accelerating. Global tech giants are still placing massive orders to run larger models and process massive amounts of data. NVIDIA's gross margin remains extremely high, indicating that its pricing power and technology moat are still strengthening without any obvious loosening.
But Jensen Huang has never been someone who only focuses on the current quarter's performance. During the earnings call, he emphasized that NVIDIA's growth engine is diversifying, no longer relying solely on the data center business. PC, automotive, robotics, and edge computing are all ramping up simultaneously. This earnings report is essentially a long-term reassurance to the entire market: AI is not a short-term hype but a super technology cycle that could last a decade or more.
NVIDIA's current market position is somewhat like Apple's over a decade ago—it's not just selling hardware products; it's defining the ecological rules and development standards for the entire industry. The CUDA platform, developed over a decade ago, remains the mainstream choice for global AI developers, almost becoming a de facto industry standard. That's why so many competitors spend heavily to catch up but always fall short of that critical step. NVIDIA is not just a chip company; it has become an infrastructure-level presence in the AI era.
From a longer historical perspective, NVIDIA's transformation from a gaming graphics card company to a leader in AI computing has been very determined. Every time the market questions its high valuation, it responds with actual performance and new technologies. This earnings report once again proves this point.
RTX Spark Super Chip—AI Truly Enters Ordinary People's Lives. High-end servers in data centers are not enough. Jensen Huang personally launched the RTX Spark super chip (some internally call it the N1X series) at the Computex keynote. This is the first time NVIDIA has brought such powerful AI computing power to the PC market that ordinary consumers use every day on a large scale. The significance of this step cannot be overstated.
What excites me most is how powerful the specs are. Let me break it down clearly for you.
CPU: 20-core Grace ARM architecture processor, deeply collaborated with MediaTek, excellent performance and power balance, ideal for battery-conscious devices like laptops.
GPU: 6144 CUDA cores, graphics rendering performance close to the mobile RTX 5070 class, while supporting the latest real-time ray tracing and DLSS 4 intelligent frame generation technology, capable for both gaming and creation.
Memory: Supports up to 128GB unified memory (LPDDR5X), with CPU and GPU sharing the same memory pool, greatly reducing the overhead of data copying, resulting in significantly improved overall efficiency.
Process: Uses TSMC's most advanced 3nm process, with transistor count reaching 70 billion, extremely high integration, packing in a lot.
Peak AI computing power: 1 PFLOPS, that is 1 quadrillion floating-point operations per second, which is an unprecedented monster-level performance in the laptop category!
The most critical and impressive aspect is that it deeply integrates CPU and GPU through NVLink high-speed interconnect technology, supporting local efficient operation of 70B and even larger parameter large language models and personal AI agents. In the future, even if your laptop is completely offline, it can independently accomplish many tasks that previously had to rely on the cloud:
Automatically edit 4K or even higher resolution videos, intelligently recognize scenes, add subtitles, music, and transition effects
Generate complex code in real time, automatically debug bugs, optimize program performance
Play large 3A games with intelligent dynamic optimization of graphics, frame rate, and lighting effects
Run a personal AI assistant locally, quickly process documents, analyze photos, generate creative solutions, and even simulate simple physics experiments
Jensen Huang said a memorable line during the launch: "We've condensed everything we've learned over the last 33 years into this one chip."
The first batch of new laptops equipped with the RTX Spark super chip has attracted top-tier manufacturers like ASUS, Dell, Lenovo, Microsoft Surface, and MSI, and will hit the market gradually this fall. According to demo videos, the new machines can maintain over 100 frames per second stably on battery power while running "Forza Horizon 6" at 1440p resolution. This is a huge draw for gamers, video creators, and 3D designers.
This marks the transition of the AI PC era from concept hype to real mass deployment. Previously, AI applications mainly relied on cloud servers; now local devices can run efficiently, meaning lower latency, better privacy protection, and more controllable usage costs. This will bring direct and significant help to ordinary office workers completing work reports quickly, students aiding learning and thesis writing, and freelancers improving creative efficiency.
At the same time, this strongly catalyzes the entire global PC supply chain. As the world's largest PC production base and consumer market, China will be the first to enjoy the industry dividends from this round of hardware replacement cycle. This is one reason why the Southern China Sci-Tech Chip ETF saw significant rises and capital inflows after the news.
Physical AI: NVIDIA's True Long-Term Trillion-Dollar Killer. If RTX Spark is the quick highlight the market can see now, the big story that Jensen Huang is truly betting on long-term and that the market has the most hope for is actually Physical AI.
That is, Physical AI is not the AI we are familiar with that can only chat, write articles, and generate images. It is a type of embodied intelligence that truly understands the laws of the physical world, can operate hands-on, and interacts with the real world. It requires a deep understanding of physical principles such as friction, gravity, inertia, object persistence, and causality, and will ultimately be mass-applied in real-world physical scenarios like humanoid robots, smart factories, autonomous vehicles, drone swarms, and smart logistics.
Jensen Huang's prediction this time is very aggressive and very clear: the total addressable market for the Physical AI track could reach tens of trillions of dollars, with just the humanoid robot segment potentially contributing a massive $40-50 trillion. He believes that within the next five years, robots will move from laboratories to large-scale factory deployment and home applications, gradually becoming a part of daily life, much like smartphones did.
Why can this market reach such an astonishing scale? Let's analyze it from several dimensions.
First, the global labor shortage problem has reached a very severe level. In the US, many manufacturing plants have long been unable to find enough workers; in Europe and East Asia, aging populations are causing a continuous decline in labor supply. China has also entered a phase of rapidly rising labor costs. The biggest advantage of robots is that they can work 24/7 without rest, without pay increases, without sick leave, greatly alleviating the contradiction between labor supply and demand.
Second, the application space in industrial and production scenarios is extremely broad. Currently, the total value of new factories being built globally is around $5 trillion. If Physical AI technology is applied to optimize factory design, simulate production processes, and intelligently dispatch robots in real time, the efficiency of the entire production system could increase by 30% to 50%, bringing enormous economic value.
Third, the potential in consumer and service sectors is almost limitless. Imagine that in the future, ordinary households might have home robots to help with housework, care for the elderly and children; logistics warehouses achieve fully automated sorting and handling; construction sites use robots to move heavy objects and perform dangerous tasks; hospitals use robots to assist with care and deliver medication... Once these scenarios mature, the sale price of a single robot, plus subsequent revenue from software subscriptions, service maintenance, and data value-added, will form a market of astronomical scale.
NVIDIA has clearly started heavily investing in this direction years in advance and has now formed a relatively complete solution system:
Isaac platform: an operating system and simulation environment dedicated to robot development, allowing developers to efficiently test various complex scenarios.
GR00T humanoid robot foundation model: can generate massive amounts of synthetic training data, helping robots quickly learn new actions and skills, greatly shortening training cycles.
Omniverse digital twin platform: can create virtual mirrors of factories and equipment, allowing thorough testing and optimization before real deployment, already adopted by multiple industrial giants like TSMC, Foxconn, and Mercedes-Benz.
What is smarter and more noteworthy is that the newly released RTX Spark PC chip forms a perfect technical closed loop with Physical AI. Robot engineers and developers can quickly iterate models and perform local simulation tests on their ordinary laptops, greatly lowering the development threshold and time cost. Data centers are responsible for training super large models, while PCs and edge devices handle real-time inference and execution. This cloud-edge-device collaborative architecture is the unique advantage of NVIDIA's ecosystem.
Personally, I firmly believe that Physical AI is not a distant sci-fi, but the next industrial revolution that is gradually happening. 2026 will mainly be a phase of technology verification and small-scale pilot implementation, but by 2027-2028, we are likely to see humanoid robots truly enter mass production and volume. By then, you might see groups of humanoid robots working together in warehouses, robots helping with housework and chatting with the elderly at home, robots assisting medical staff in hospitals, and human society's productivity and lifestyle will undergo a major leap.
Part Four: Global Chain Reaction—How NVIDIA Drives the Entire AI Ecosystem
NVIDIA's strong performance is triggering a global chain reaction and resource reallocation.
Take Google for example. Why did they choose this time to raise a rare $80 billion through equity financing to invest heavily in AI infrastructure, and even attract a $1 billion subscription from Berkshire Hathaway? The fundamental reason is that they need massive, high-performance computing power, and NVIDIA is currently the most advanced and reliable choice in the industry. Google Cloud's first-quarter revenue growth was strong, and its backlog of orders has approached $460 billion. They must build infrastructure on a large scale in advance to meet future demand.
This further proves that NVIDIA is no longer just a chip supplier but the core foundation of the entire AI ecosystem. On the demand side, giants like Google, Microsoft, Meta, and Amazon are frantically increasing AI investment. On the supply side, NVIDIA provides cutting-edge chips and software platforms. In the middle is China's huge supply chain system and application deployment capabilities. These three forces interact and jointly drive the entire industry forward.
Therefore, the Chinese capital market reacted very quickly. The Southern China Sci-Tech Chip ETF tracks the Shanghai Sci-Tech Chip Index. Its constituent stocks cover multiple links such as chip design, manufacturing, equipment, and materials. The phenomenon of opening higher and strengthening with obvious net capital inflows yesterday reflects the market's continued attention and confidence in the NVIDIA supply chain and robotics industry chain.
Finally, let's stretch the timeline to 2030 and think about what changes might happen in ordinary people's daily lives if these technology trends continue to materialize.
Waking up in the morning, you may no longer need to set an alarm yourself. The home robot has already gently woken you up based on your sleep data and the day's schedule. It has also prepared a nutritionally balanced breakfast based on your health data and preferences, and tidied up the living room and bedroom.
You go to work and take a Robotaxi, which automatically adjusts the route and interior space based on real-time traffic, weather, and your personal habits. At the office, a Physical AI-driven digital twin system shows the real-time operation status of the global supply chain, allowing you to simulate the cost, efficiency, and risk of different decision-making scenarios within seconds.
Your RTX Spark second-generation laptop has become a super productivity tool. It can run complex AI models locally quickly, helping you analyze reports, generate creative solutions, and even simulate physics experiments, significantly shortening work that used to take days.
On a more macro industrial level, a large number of humanoid robots are working 24/7 with high precision, taking over repetitive, dangerous, or high-labor-cost positions. The labor shortage problem is fundamentally alleviated, and the overall social productivity curve shows a new steep rise.
From a company initially focused on gaming graphics cards, NVIDIA has gradually grown into the most important infrastructure driver in the AI era. It not only maintains a lead in chip hardware but also defines and promotes the intelligentization of the physical world through software platforms like CUDA, Isaac, and Omniverse. As a global manufacturing and consumer powerhouse, China plays an irreplaceable role in supply chain perfection, application scenario implementation, and cost optimization. The global AI industry chain is forming a pattern of benign complementarity.
This transformation from purely digital information intelligence to truly embodied physical intelligence is gradually happening before our eyes. Its profound impact on human society's production methods, lifestyles, and even the entire economic structure may far exceed our imagination today.
Friends, today's video has focused on NVIDIA, thoroughly explaining yesterday's earnings highlights, detailed technical analysis of the RTX Spark super chip, the trillion-dollar long-term outlook for Physical AI, the global supply chain resonance reaction, and possible life in 2030. I hope after listening, you have a more three-dimensional and deeper understanding of AI industry development trends in 2026 and beyond.
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All content in this video is for personal analysis, information compilation, and trend outlook only, and does not constitute any investment advice. Please make independent judgments based on your own actual situation. See you next time! Let's continue to follow the latest developments in the AI field! Let's go!
