Author: Aki Wu Talks Blockchain In late October 2025, Nvidia's stock price reached a new all-time high, pushing its market capitalization past the $5 trillion mark, making it the first company globally to cross this threshold. Since the emergence of ChatGPT in late 2022, Nvidia's stock price has increased more than 12-fold. The AI revolution has not only driven the S&P 500 to new highs but also sparked discussions about a tech valuation bubble. Today, Nvidia's market capitalization even exceeds the total size of the entire cryptocurrency market, and in terms of global GDP ranking, Nvidia's market capitalization is second only to the United States and China. Remarkably, this AI superstar also had a "honeymoon period" in the cryptocurrency field. This article will review Nvidia's tumultuous history with the cryptocurrency mining industry and why it chose to withdraw and shift its focus to its core AI business. Crypto Bull Market Frenzy: Gaming Graphics Cards Turn into "Money Printing Machines" Looking back at Nvidia's history is like reading a legend of the ever-evolving narrative of technology. Founded in 1993, Nvidia started by inventing the GPU (Graphics Processing Unit) and rode the wave of the PC gaming boom in the late 1990s. Nvidia's GeForce series graphics cards were a huge success, and the company quickly rose to become a graphics card giant. However, when the gaming market gradually saturated and growth slowed, Nvidia also faced the predicament of unsold inventory. Fortunately, opportunity always favors the prepared—a major turning point was the cryptocurrency boom. In 2017, the prices of cryptocurrencies such as Bitcoin and Ethereum soared, sparking a "mining" craze. Because GPUs are ideally suited for parallel computing in mining, miners worldwide scrambled for graphics cards, turning them into money-printing machines with supply falling short of demand and prices skyrocketing. Nvidia emerged as one of the biggest winners behind this crypto bull market, reaping huge profits from card sales. Starting in the second half of 2020, the cryptocurrency market rebounded after a two-year hiatus. Bitcoin prices surged from less than $15,000 in the middle of the year to a peak of over $60,000 in early 2021, while Ethereum rose from a few hundred dollars to over $2,000. This new wave of price increases reignited the GPU mining frenzy. Miners snapped up the new generation of GeForce RTX 30 series graphics cards, leading to a shortage of high-end cards originally intended for gamers, plunging the market into a frenzy of "supply falling short of demand." While NVIDIA's RTX 30 series graphics cards initially surprised gamers with their high performance and cost-effectiveness, the soaring profits from Ethereum mining pushed their actual selling prices to outrageous levels. The RTX 3060, with a suggested retail price of 2499 RMB, was being resold for 5499 RMB, and the flagship RTX 3090 was even being priced close to 20,000 RMB. However, the persistent shortage of graphics cards brought the conflict between gamers and miners to the forefront. Nvidia opted for a "dual-track" approach, simultaneously lowering the Ethereum hash rate for its gamer-oriented GeForce cards (starting with the RTX 3060). However, this was later discovered to be a smokescreen. In reality, miners discovered that by plugging the RTX 3060 with a "dummy HDMI cable," it would perceive other graphics cards as also functioning as display adapters, thus bypassing the hash rate limitations in multi-GPU scenarios and achieving full-speed mining. Andreas demonstrated this on his Twitter account. On the other hand, a series of Cryptocurrency Mining Processors (CMPs) were launched specifically for miners, attempting to "divide the market." The official blog stated explicitly that day: "GeForce is born for gamers, CMP is born for professional miners." CMPs would eliminate display output, use open baffles to improve airflow in densely packed mining racks, and lower peak voltage/frequency for stable energy efficiency. However, precisely because CMPs lacked display output and had a short warranty period, exiting the market was more difficult for miners. GeForces, on the other hand, could be used for mining and could be refurbished and resold to struggling miners, offering better residual value and liquidity. Therefore, this project ultimately generated much hype but little substance, eventually fading from public view. According to Nvidia's financial report, graphics cards used for mining accounted for a quarter of its shipments in the first fiscal quarter of 2021, with sales of cryptocurrency-specific chips (CMP series) reaching $155 million. Fueled by the crypto boom, Nvidia's revenue for the entire year of 2021 soared to $26.9 billion, a 61% increase year-over-year, and the company's market capitalization briefly surpassed $800 billion. However, this favorable situation did not last long. On May 21, 2021, the Financial Stability and Development Committee of the State Council of China proposed to severely crack down on Bitcoin mining and trading. Subsequently, mining farms in Xinjiang, Qinghai, Sichuan and other places were shut down, and the mining business quickly came to a halt. In the same month and the following month, Bitcoin hashrate and price both came under pressure, and miners were forced to relocate or liquidate their equipment. By September 24, the People's Bank of China and multiple departments issued a joint notice, defining all virtual currency-related transactions as illegal financial activities and proposing a nationwide "orderly cleanup of the mining industry," further "closing the loopholes" at the policy level. For those in the Huaqiangbei mining machine industry, the cycle of boom and bust is nothing new. Those who experienced the mining machine "crash" of early 2018 still vividly remember it; some withdrew from the market in despair, but a few persevered and weathered the storm, investing their unsold machines into their own mining farms, waiting for the next boom. As it turns out, the bull market of 2020-2021 once again allowed those who held on to turn their fortunes around. In September 2022, a landmark event occurred in the crypto industry: the Ethereum blockchain completed its "merge" upgrade, transitioning from a Proof-of-Work (PoW) mechanism to a Proof-of-Stake (PoS) mechanism, eliminating the need for a large number of GPUs to participate in mining. This marked the end of the long-standing era of GPU mining. Without the specific needs of crypto miners, the global GPU market cooled rapidly, directly impacting Nvidia's performance. In the third quarter of 2022, Nvidia's revenue declined by 17% year-on-year to $5.93 billion, and net profit was only $680 million, a year-on-year decrease of 72%. Nvidia's stock price once fell to around $165 in 2022, nearly halving from its peak, and the former crypto boom instantly became a burden on its performance. Drawing a line: Nvidia's breakup with the mining industry Faced with the frenzy in the mining industry, complaints from gamers, and problems arising from cyclical profits, Nvidia gradually realized it needed to find a balance within the cryptocurrency mining boom and, at the right time, "draw a clear line" with it. As concerns about a bubble emerged from soaring cryptocurrency prices, the company also suffered from financial compliance issues. A subsequent investigation by the U.S. Securities and Exchange Commission (SEC) found that Nvidia had failed to adequately disclose the contribution of cryptocurrency mining to its gaming graphics card revenue growth for two consecutive quarters in fiscal year 2018. This was deemed improper disclosure. In May 2022, Nvidia agreed to settle with the SEC and pay a $5.5 million fine. This incident forced Nvidia to re-evaluate its delicate relationship with the crypto industry; while the cryptocurrency mining boom brought considerable profits, its volatility and regulatory risks could also damage the company's reputation and performance. After Ethereum switched to PoS in 2022, GPU mining demand plummeted, and Nvidia's gaming graphics card business quickly returned to normal supply and demand. Jensen Huang has also repeatedly emphasized that the company's future growth will primarily come from areas such as artificial intelligence, data centers, and autonomous driving, rather than relying on speculative businesses like cryptocurrencies. It can be said that after experiencing the highs and lows of the "mining card craze," Nvidia decisively distanced itself from this highly volatile industry, investing more resources in the broader and more socially valuable AI computing landscape. Furthermore, Nvidia's latest Inception program website for AI startups explicitly lists "unqualified organization types," including "crypto-related companies," demonstrating Nvidia's clear desire to distance itself from its former crypto associates. So, after fully embracing the AI industry, will Nvidia's chip business still intersect with the crypto industry? On the surface, since Ethereum bid farewell to the "mining era," the connection between GPUs and traditional crypto mining has weakened significantly. Major cryptocurrencies like Bitcoin have long used dedicated ASIC miners, and GPUs are no longer the highly sought-after "golden goose" for crypto miners as they once were. However, the two fields are not entirely without overlap, and new points of convergence are emerging in different forms. Some companies that previously focused on cryptocurrency mining are shifting their business focus to AI computing power services, becoming new customers of Nvidia. Furthermore, traditional Bitcoin mining companies are also exploring using surplus electricity and space resources to undertake AI computing tasks. Some large mining companies have recently replaced some of their equipment with GPU hardware for training AI models, believing that AI training offers a more stable and reliable source of revenue compared to the volatile cryptocurrency mining industry. The person who made the most money in the AI gold rush — Nvidia, the company that sells "shovels" In November 2022, OpenAI's ChatGPT emerged, causing a huge sensation worldwide with its large-scale AI models. For NVIDIA, this was undoubtedly another once-in-a-century opportunity. The world suddenly realized that to power these computationally intensive AI monsters, NVIDIA's GPU hardware support was indispensable. Following ChatGPT's explosive popularity, major tech companies and startups flocked to the "large model" track, leading to an explosive growth in the computing power required to train AI models. NVIDIA astutely recognized this fundamental truth: regardless of technological advancements, computing power will always be the basic currency of the digital world. Currently, Nvidia holds over 90% of the market share for large-scale model training chips. Its A100, H100, and next-generation Blackwell/H200 GPUs have become industry standards for AI acceleration computing. Due to demand far exceeding supply, Nvidia possesses extraordinary pricing power and profit margins in high-end AI chips. Goldman Sachs predicts that from 2025 to 2027, the capital expenditures of just the five major cloud service providers—Amazon, Meta, Google, Microsoft, and Oracle—are expected to approach $1.4 trillion, nearly tripling compared to the previous three years. These massive investments have laid the foundation for Nvidia's astronomical market capitalization. However, the AI field once experienced a shockwave of "cost reduction and efficiency improvement"—the explosive popularity of the open-source large model DeepSeek. The DeepSeek project claimed to have trained the DeepSeek V3 model with performance comparable to GPT-4 at an extremely low cost of only about $5.576 million, and subsequently released the R1 model with ultra-low inference cost. The industry was in an uproar at the time, with many predicting Nvidia's demise. They argued that the emergence of such low-cost AI models meant that small and medium-sized enterprises could deploy large models with fewer GPUs, potentially impacting demand for Nvidia's high-end GPUs. The question of whether "AI computing power demand will be replaced by an efficiency revolution" became a hot topic. Affected by this expectation, Nvidia's stock price plummeted, closing down about 17%, wiping out approximately $589 billion in market capitalization in a single day (considered one of the largest single-day market capitalization losses in US stock market history). However, just a few months later, it became clear that these concerns were short-sighted. DeepSeek did not reduce the demand for computing power; instead, it triggered a new surge in demand. Its technical approach essentially achieved "computing power equality"—through algorithmic innovation and model distillation, it significantly lowered the hardware barrier for large models, making AI applications more affordable for more institutions and enterprises. On the surface, it seemed that "less computing power was needed" due to improved model efficiency; but in reality, the DeepSeek phenomenon greatly popularized AI applications, leading to an exponential increase in computing power demand. A large number of enterprises rushed to adopt DeepSeek, triggering a wave of AI applications, with inference computing quickly becoming the new main driver of computing power consumption. This precisely illustrates the famous "Jeves' paradox"—increased technical efficiency actually accelerates resource consumption. DeepSeek lowered the barrier to AI and led to a surge in applications, resulting in even more insufficient computing resources. As it turns out, the emergence of a new AI model often translates into a surge of new GPU orders. The more AI innovation Nvidia produces, the stronger it becomes, a fact once again validated in the DeepSeek controversy. Nvidia's financial report released in February 2025 showed that its data center business significantly exceeded expectations. At a deeper level, the success of DeepSeek is not a threat to Nvidia; rather, it demonstrates that "cost reduction and efficiency improvement" can lead to larger-scale application expansion, thereby driving up total computing power demand. This time, DeepSeek has become new fuel for Nvidia's computing power empire. As AI pioneer Andrew Ng said, "AI is the new electricity." In the era where AI is electricity, computing power providers like Nvidia undoubtedly play the role of power companies. Through massive data centers and GPU clusters, they continuously supply "energy" to various industries, driving intelligent transformation. This is also the core logic behind Nvidia's market value soaring from $1 trillion to $5 trillion in just two years—a qualitative leap in global demand for AI computing power, with tech giants around the world investing in computing power in an arms race-like manner. After its market capitalization climbed to $5 trillion, Nvidia's influence and scale have surpassed even the economic influence of many national governments. Nvidia is no longer just a graphics card manufacturer that makes games run smoother; it has transformed into the fuel of the AI era, becoming the undisputed "shovel seller" in this gold rush. With its increasing size, the wealth creation stories of Nvidia employees have become legendary in the industry, with many employees holding stock worth more than their annual salaries. Nvidia itself has achieved one leap forward after another by continuously "telling" new technological narratives. Gaming graphics cards opened the first door for it, the mining boom provided a second wave of growth, and AI has propelled Nvidia to its true peak.Author: Aki Wu Talks Blockchain In late October 2025, Nvidia's stock price reached a new all-time high, pushing its market capitalization past the $5 trillion mark, making it the first company globally to cross this threshold. Since the emergence of ChatGPT in late 2022, Nvidia's stock price has increased more than 12-fold. The AI revolution has not only driven the S&P 500 to new highs but also sparked discussions about a tech valuation bubble. Today, Nvidia's market capitalization even exceeds the total size of the entire cryptocurrency market, and in terms of global GDP ranking, Nvidia's market capitalization is second only to the United States and China. Remarkably, this AI superstar also had a "honeymoon period" in the cryptocurrency field. This article will review Nvidia's tumultuous history with the cryptocurrency mining industry and why it chose to withdraw and shift its focus to its core AI business. Crypto Bull Market Frenzy: Gaming Graphics Cards Turn into "Money Printing Machines" Looking back at Nvidia's history is like reading a legend of the ever-evolving narrative of technology. Founded in 1993, Nvidia started by inventing the GPU (Graphics Processing Unit) and rode the wave of the PC gaming boom in the late 1990s. Nvidia's GeForce series graphics cards were a huge success, and the company quickly rose to become a graphics card giant. However, when the gaming market gradually saturated and growth slowed, Nvidia also faced the predicament of unsold inventory. Fortunately, opportunity always favors the prepared—a major turning point was the cryptocurrency boom. In 2017, the prices of cryptocurrencies such as Bitcoin and Ethereum soared, sparking a "mining" craze. Because GPUs are ideally suited for parallel computing in mining, miners worldwide scrambled for graphics cards, turning them into money-printing machines with supply falling short of demand and prices skyrocketing. Nvidia emerged as one of the biggest winners behind this crypto bull market, reaping huge profits from card sales. Starting in the second half of 2020, the cryptocurrency market rebounded after a two-year hiatus. Bitcoin prices surged from less than $15,000 in the middle of the year to a peak of over $60,000 in early 2021, while Ethereum rose from a few hundred dollars to over $2,000. This new wave of price increases reignited the GPU mining frenzy. Miners snapped up the new generation of GeForce RTX 30 series graphics cards, leading to a shortage of high-end cards originally intended for gamers, plunging the market into a frenzy of "supply falling short of demand." While NVIDIA's RTX 30 series graphics cards initially surprised gamers with their high performance and cost-effectiveness, the soaring profits from Ethereum mining pushed their actual selling prices to outrageous levels. The RTX 3060, with a suggested retail price of 2499 RMB, was being resold for 5499 RMB, and the flagship RTX 3090 was even being priced close to 20,000 RMB. However, the persistent shortage of graphics cards brought the conflict between gamers and miners to the forefront. Nvidia opted for a "dual-track" approach, simultaneously lowering the Ethereum hash rate for its gamer-oriented GeForce cards (starting with the RTX 3060). However, this was later discovered to be a smokescreen. In reality, miners discovered that by plugging the RTX 3060 with a "dummy HDMI cable," it would perceive other graphics cards as also functioning as display adapters, thus bypassing the hash rate limitations in multi-GPU scenarios and achieving full-speed mining. Andreas demonstrated this on his Twitter account. On the other hand, a series of Cryptocurrency Mining Processors (CMPs) were launched specifically for miners, attempting to "divide the market." The official blog stated explicitly that day: "GeForce is born for gamers, CMP is born for professional miners." CMPs would eliminate display output, use open baffles to improve airflow in densely packed mining racks, and lower peak voltage/frequency for stable energy efficiency. However, precisely because CMPs lacked display output and had a short warranty period, exiting the market was more difficult for miners. GeForces, on the other hand, could be used for mining and could be refurbished and resold to struggling miners, offering better residual value and liquidity. Therefore, this project ultimately generated much hype but little substance, eventually fading from public view. According to Nvidia's financial report, graphics cards used for mining accounted for a quarter of its shipments in the first fiscal quarter of 2021, with sales of cryptocurrency-specific chips (CMP series) reaching $155 million. Fueled by the crypto boom, Nvidia's revenue for the entire year of 2021 soared to $26.9 billion, a 61% increase year-over-year, and the company's market capitalization briefly surpassed $800 billion. However, this favorable situation did not last long. On May 21, 2021, the Financial Stability and Development Committee of the State Council of China proposed to severely crack down on Bitcoin mining and trading. Subsequently, mining farms in Xinjiang, Qinghai, Sichuan and other places were shut down, and the mining business quickly came to a halt. In the same month and the following month, Bitcoin hashrate and price both came under pressure, and miners were forced to relocate or liquidate their equipment. By September 24, the People's Bank of China and multiple departments issued a joint notice, defining all virtual currency-related transactions as illegal financial activities and proposing a nationwide "orderly cleanup of the mining industry," further "closing the loopholes" at the policy level. For those in the Huaqiangbei mining machine industry, the cycle of boom and bust is nothing new. Those who experienced the mining machine "crash" of early 2018 still vividly remember it; some withdrew from the market in despair, but a few persevered and weathered the storm, investing their unsold machines into their own mining farms, waiting for the next boom. As it turns out, the bull market of 2020-2021 once again allowed those who held on to turn their fortunes around. In September 2022, a landmark event occurred in the crypto industry: the Ethereum blockchain completed its "merge" upgrade, transitioning from a Proof-of-Work (PoW) mechanism to a Proof-of-Stake (PoS) mechanism, eliminating the need for a large number of GPUs to participate in mining. This marked the end of the long-standing era of GPU mining. Without the specific needs of crypto miners, the global GPU market cooled rapidly, directly impacting Nvidia's performance. In the third quarter of 2022, Nvidia's revenue declined by 17% year-on-year to $5.93 billion, and net profit was only $680 million, a year-on-year decrease of 72%. Nvidia's stock price once fell to around $165 in 2022, nearly halving from its peak, and the former crypto boom instantly became a burden on its performance. Drawing a line: Nvidia's breakup with the mining industry Faced with the frenzy in the mining industry, complaints from gamers, and problems arising from cyclical profits, Nvidia gradually realized it needed to find a balance within the cryptocurrency mining boom and, at the right time, "draw a clear line" with it. As concerns about a bubble emerged from soaring cryptocurrency prices, the company also suffered from financial compliance issues. A subsequent investigation by the U.S. Securities and Exchange Commission (SEC) found that Nvidia had failed to adequately disclose the contribution of cryptocurrency mining to its gaming graphics card revenue growth for two consecutive quarters in fiscal year 2018. This was deemed improper disclosure. In May 2022, Nvidia agreed to settle with the SEC and pay a $5.5 million fine. This incident forced Nvidia to re-evaluate its delicate relationship with the crypto industry; while the cryptocurrency mining boom brought considerable profits, its volatility and regulatory risks could also damage the company's reputation and performance. After Ethereum switched to PoS in 2022, GPU mining demand plummeted, and Nvidia's gaming graphics card business quickly returned to normal supply and demand. Jensen Huang has also repeatedly emphasized that the company's future growth will primarily come from areas such as artificial intelligence, data centers, and autonomous driving, rather than relying on speculative businesses like cryptocurrencies. It can be said that after experiencing the highs and lows of the "mining card craze," Nvidia decisively distanced itself from this highly volatile industry, investing more resources in the broader and more socially valuable AI computing landscape. Furthermore, Nvidia's latest Inception program website for AI startups explicitly lists "unqualified organization types," including "crypto-related companies," demonstrating Nvidia's clear desire to distance itself from its former crypto associates. So, after fully embracing the AI industry, will Nvidia's chip business still intersect with the crypto industry? On the surface, since Ethereum bid farewell to the "mining era," the connection between GPUs and traditional crypto mining has weakened significantly. Major cryptocurrencies like Bitcoin have long used dedicated ASIC miners, and GPUs are no longer the highly sought-after "golden goose" for crypto miners as they once were. However, the two fields are not entirely without overlap, and new points of convergence are emerging in different forms. Some companies that previously focused on cryptocurrency mining are shifting their business focus to AI computing power services, becoming new customers of Nvidia. Furthermore, traditional Bitcoin mining companies are also exploring using surplus electricity and space resources to undertake AI computing tasks. Some large mining companies have recently replaced some of their equipment with GPU hardware for training AI models, believing that AI training offers a more stable and reliable source of revenue compared to the volatile cryptocurrency mining industry. The person who made the most money in the AI gold rush — Nvidia, the company that sells "shovels" In November 2022, OpenAI's ChatGPT emerged, causing a huge sensation worldwide with its large-scale AI models. For NVIDIA, this was undoubtedly another once-in-a-century opportunity. The world suddenly realized that to power these computationally intensive AI monsters, NVIDIA's GPU hardware support was indispensable. Following ChatGPT's explosive popularity, major tech companies and startups flocked to the "large model" track, leading to an explosive growth in the computing power required to train AI models. NVIDIA astutely recognized this fundamental truth: regardless of technological advancements, computing power will always be the basic currency of the digital world. Currently, Nvidia holds over 90% of the market share for large-scale model training chips. Its A100, H100, and next-generation Blackwell/H200 GPUs have become industry standards for AI acceleration computing. Due to demand far exceeding supply, Nvidia possesses extraordinary pricing power and profit margins in high-end AI chips. Goldman Sachs predicts that from 2025 to 2027, the capital expenditures of just the five major cloud service providers—Amazon, Meta, Google, Microsoft, and Oracle—are expected to approach $1.4 trillion, nearly tripling compared to the previous three years. These massive investments have laid the foundation for Nvidia's astronomical market capitalization. However, the AI field once experienced a shockwave of "cost reduction and efficiency improvement"—the explosive popularity of the open-source large model DeepSeek. The DeepSeek project claimed to have trained the DeepSeek V3 model with performance comparable to GPT-4 at an extremely low cost of only about $5.576 million, and subsequently released the R1 model with ultra-low inference cost. The industry was in an uproar at the time, with many predicting Nvidia's demise. They argued that the emergence of such low-cost AI models meant that small and medium-sized enterprises could deploy large models with fewer GPUs, potentially impacting demand for Nvidia's high-end GPUs. The question of whether "AI computing power demand will be replaced by an efficiency revolution" became a hot topic. Affected by this expectation, Nvidia's stock price plummeted, closing down about 17%, wiping out approximately $589 billion in market capitalization in a single day (considered one of the largest single-day market capitalization losses in US stock market history). However, just a few months later, it became clear that these concerns were short-sighted. DeepSeek did not reduce the demand for computing power; instead, it triggered a new surge in demand. Its technical approach essentially achieved "computing power equality"—through algorithmic innovation and model distillation, it significantly lowered the hardware barrier for large models, making AI applications more affordable for more institutions and enterprises. On the surface, it seemed that "less computing power was needed" due to improved model efficiency; but in reality, the DeepSeek phenomenon greatly popularized AI applications, leading to an exponential increase in computing power demand. A large number of enterprises rushed to adopt DeepSeek, triggering a wave of AI applications, with inference computing quickly becoming the new main driver of computing power consumption. This precisely illustrates the famous "Jeves' paradox"—increased technical efficiency actually accelerates resource consumption. DeepSeek lowered the barrier to AI and led to a surge in applications, resulting in even more insufficient computing resources. As it turns out, the emergence of a new AI model often translates into a surge of new GPU orders. The more AI innovation Nvidia produces, the stronger it becomes, a fact once again validated in the DeepSeek controversy. Nvidia's financial report released in February 2025 showed that its data center business significantly exceeded expectations. At a deeper level, the success of DeepSeek is not a threat to Nvidia; rather, it demonstrates that "cost reduction and efficiency improvement" can lead to larger-scale application expansion, thereby driving up total computing power demand. This time, DeepSeek has become new fuel for Nvidia's computing power empire. As AI pioneer Andrew Ng said, "AI is the new electricity." In the era where AI is electricity, computing power providers like Nvidia undoubtedly play the role of power companies. Through massive data centers and GPU clusters, they continuously supply "energy" to various industries, driving intelligent transformation. This is also the core logic behind Nvidia's market value soaring from $1 trillion to $5 trillion in just two years—a qualitative leap in global demand for AI computing power, with tech giants around the world investing in computing power in an arms race-like manner. After its market capitalization climbed to $5 trillion, Nvidia's influence and scale have surpassed even the economic influence of many national governments. Nvidia is no longer just a graphics card manufacturer that makes games run smoother; it has transformed into the fuel of the AI era, becoming the undisputed "shovel seller" in this gold rush. With its increasing size, the wealth creation stories of Nvidia employees have become legendary in the industry, with many employees holding stock worth more than their annual salaries. Nvidia itself has achieved one leap forward after another by continuously "telling" new technological narratives. Gaming graphics cards opened the first door for it, the mining boom provided a second wave of growth, and AI has propelled Nvidia to its true peak.