South Korea's Supreme Court has delivered what is being called the country's "Divorce of the Year." SK Group Chairman Chey Tae-won has been ordered to pay 944 billion won to his former wife, Roh So-young, in one of the largest divorce settlements in South Korean history. The landmark ruling has drawn attention to Chey's massive stake in SK Group, South Korea's second-largest conglomerate. Analysts believe the billionaire may need to sell shares or use them as collateral to fund the record payment.

Chey Tae-Won to Pay 944 Billion Won to Wife | Wion News 

DeepSeek founder Liang Wenfeng has laid out an unusually ambitious vision for the Chinese AI company: focus on artificial general intelligence (AGI), keep commercialisation secondary and help build an AI ecosystem less dependent on Nvidia. His remarks emerged from a lengthy discussion with investors and offer a rare look at how the normally low-profile entrepreneur thinks about the global AI race. While companies across the industry are spending heavily to turn AI into profitable products, Liang said DeepSeek's main objective remains AGI broadly referring to AI capable of performing intellectual tasks across many areas at or beyond human level.<h2>DeepSeek wants the 'watermelon', not the 'sesame seeds'</h2>Liang compared near-term revenue opportunities with “sesame seeds”, suggesting DeepSeek will pick some up without allowing them to distract the company from a much bigger prize. “Our goal should be AGI,” he said. The philosophy does not mean DeepSeek will ignore commercial opportunities. Rather, Liang argues that building more advanced intelligence should take priority over maximising revenue from today's products. He described AI development as a staircase. Language models provide the foundation for reasoning, reasoning enables more capable agents, and future systems could eventually learn and improve continuously. If an AI system can help develop its own successor, Liang believes progress could accelerate dramatically.<h2>Why Liang thinks Nvidia is 'digging its own grave'</h2>Perhaps his most provocative remarks concerned Nvidia. US restrictions have limited Chinese companies' access to some of Nvidia's most advanced AI hardware. But Liang argues that those restrictions are creating a powerful incentive for China to develop alternatives. “If Nvidia cards can't be bought, everyone is forced into it everyone has to do domestic chips,” he said. Liang went further, saying he believes “Nvidia is digging its own grave” by creating conditions that encourage Chinese companies to reduce their dependence on its hardware. DeepSeek is working closely with Huawei and expects to participate deeply in its AI computing ecosystem.<h2>Can Huawei really replace Nvidia?</h2>Liang's comments should not be mistaken for a claim that China has already eliminated Nvidia's technological advantage. He acknowledged a substantial efficiency gap, saying roughly four Huawei chips may be needed for the work of one comparable Nvidia chip, while China's hardware remains about two years behind. His broader argument is about direction rather than today's outright performance. DeepSeek has already demonstrated an interest in designing its software around hardware limitations. Its researchers have previously detailed how DeepSeek-V3 was trained using 2,048 Nvidia H800 GPUs while relying on several hardware-aware efficiency techniques. Liang believes the same pressure could ultimately produce a broader Chinese AI ecosystem built around domestic chips, open models and lower prices. That would turn Washington's restrictions into something of a long-term gamble: limiting China's access to America's best AI hardware today could also give Chinese companies a powerful reason to make sure they need less of it tomorrow.

DeepSeek founder Liang Wenfeng says AGI, not short-term profit, remains the company's main goal. He also argues that US restrictions on Nvidia chips are accelerating China's push towards domestic AI hardware, with DeepSeek working closely with Huawei.


DeepSeek founder Liang Wenfeng has laid out an unusually ambitious vision for the Chinese AI company: focus on artificial general intelligence (AGI), keep commercialisation secondary and help build an AI ecosystem less dependent on Nvidia. His remarks emerged from a lengthy discussion with investors and offer a rare look at how the normally low-profile entrepreneur thinks about the global AI race. While companies across the industry are spending heavily to turn AI into profitable products, Liang said DeepSeek's main objective remains AGI broadly referring to AI capable of performing intellectual tasks across many areas at or beyond human level. DeepSeek wants the 'watermelon', not the 'sesame seeds' Liang compared near-term revenue opportunities with “sesame seeds”, suggesting DeepSeek will pick some up without allowing them to distract the company from a much bigger prize. “Our goal should be AGI,” he said. The philosophy does not mean DeepSeek will ignore commercial opportunities. Rather, Liang argues that building more advanced intelligence should take priority over maximising revenue from today's products. He described AI development as a staircase. Language models provide the foundation for reasoning, reasoning enables more capable agents, and future systems could eventually learn and improve continuously. If an AI system can help develop its own successor, Liang believes progress could accelerate dramatically. Why Liang thinks Nvidia is 'digging its own grave' Perhaps his most provocative remarks concerned Nvidia. US restrictions have limited Chinese companies' access to some of Nvidia's most advanced AI hardware. But Liang argues that those restrictions are creating a powerful incentive for China to develop alternatives. “If Nvidia cards can't be bought, everyone is forced into it everyone has to do domestic chips,” he said. Liang went further, saying he believes “Nvidia is digging its own grave” by creating conditions that encourage Chinese companies to reduce their dependence on its hardware. DeepSeek is working closely with Huawei and expects to participate deeply in its AI computing ecosystem. Can Huawei really replace Nvidia? Liang's comments should not be mistaken for a claim that China has already eliminated Nvidia's technological advantage. He acknowledged a substantial efficiency gap, saying roughly four Huawei chips may be needed for the work of one comparable Nvidia chip, while China's hardware remains about two years behind. His broader argument is about direction rather than today's outright performance. DeepSeek has already demonstrated an interest in designing its software around hardware limitations. Its researchers have previously detailed how DeepSeek-V3 was trained using 2,048 Nvidia H800 GPUs while relying on several hardware-aware efficiency techniques. Liang believes the same pressure could ultimately produce a broader Chinese AI ecosystem built around domestic chips, open models and lower prices. That would turn Washington's restrictions into something of a long-term gamble: limiting China's access to America's best AI hardware today could also give Chinese companies a powerful reason to make sure they need less of it tomorrow.

DeepSeek founder Liang Wenfeng says AGI, not short-term profit, remains the company's main goal. He also argues that US restrictions on Nvidia chips are accelerating China's push towards domestic AI hardware, with DeepSeek working closely with Huawei.

'Nvidia is digging its own grave': DeepSeek CEO backs China's AI chip push

Nvidia CEO Jensen Huang has delivered a striking defence of Taiwan's semiconductor industry, saying the island “saved” America's chip and computing industries rather than taking them away. “Taiwan saved the American semiconductor industry, saved the American computing industry, not the opposite,” Huang told reporters during the opening of Taiwanese manufacturer Wistron's first US manufacturing facility in Fort Worth, Texas. The comments carry particular weight because Huang sits at the centre of the global AI boom. Nvidia designs the GPUs powering many of today's most advanced AI systems, while Taiwan remains a critical part of the supply chain that makes those systems possible.Jensen Huang: Without Taiwan, Japan could have taken the leadHuang argued that the relationship between Taiwan and America's technology industry should be viewed as a partnership rather than a story of one country taking manufacturing from another. Without Taiwan's rise as a technology manufacturing powerhouse, he suggested, Japan could have taken a much larger share of America's semiconductor industry. Huang also said Taiwanese companies expanding manufacturing in America are doing so because it makes business sense. “Taiwan is doing it voluntarily because of its own wisdom, not because it's held a gun to its head,” Huang said. He described the relationship between American and Taiwanese technology companies as one built over decades of cooperation and trust.<h2>A sharp contrast with Trump's 'stolen' chip claim</h2>Huang did not name US President Donald Trump. But his comments offer a sharply different interpretation of how Taiwan became a semiconductor powerhouse. Trump has repeatedly accused Taiwan of taking America's semiconductor business and argued that previous US governments should have used tariffs to prevent chip manufacturing from shifting overseas. Taiwan has rejected that characterisation, arguing that its semiconductor industry was built through decades of investment, engineering expertise and the development of a highly specialised manufacturing ecosystem. Huang's argument goes further: Taiwan's rise, in his view, helped American technology companies remain competitive.<h2>Nvidia's latest AI superchips are now being made in Texas</h2>The setting for Huang's comments was significant. Wistron's new D1 facility in Fort Worth is a 324,000-square-foot manufacturing plant backed by a $700 million investment. The facility is already mass-producing Nvidia's GB300 Grace Blackwell Ultra Superchip in the United States. It is also expected to manufacture Nvidia's next-generation Vera Rubin Superchip. Wistron says the site has created more than 500 jobs, with plans to expand that number to around 1,000 by the end of 2026. For Nvidia, this represents something bigger than opening another factory.The company is trying to build more of the physical infrastructure behind the AI boom inside America from chips and packaging to servers and complete AI systems.And there is an irony at the centre of that effort. As Washington pushes to bring advanced technology manufacturing back to American soil, some of the companies helping make that possible are precisely the Taiwanese manufacturers that Huang believes America should be thanking rather than blaming.

Nvidia CEO Jensen Huang says Taiwan “saved” America's semiconductor and computing industries, challenging claims that it took US chip manufacturing away. His remarks came as Taiwan's Wistron opened a $700 million Nvidia AI manufacturing facility in Texas.


Nvidia CEO Jensen Huang has delivered a striking defence of Taiwan's semiconductor industry, saying the island “saved” America's chip and computing industries rather than taking them away. “Taiwan saved the American semiconductor industry, saved the American computing industry, not the opposite,” Huang told reporters during the opening of Taiwanese manufacturer Wistron's first US manufacturing facility in Fort Worth, Texas. The comments carry particular weight because Huang sits at the centre of the global AI boom. Nvidia designs the GPUs powering many of today's most advanced AI systems, while Taiwan remains a critical part of the supply chain that makes those systems possible. Jensen Huang: Without Taiwan, Japan could have taken the lead Huang argued that the relationship between Taiwan and America's technology industry should be viewed as a partnership rather than a story of one country taking manufacturing from another. Without Taiwan's rise as a technology manufacturing powerhouse, he suggested, Japan could have taken a much larger share of America's semiconductor industry. Huang also said Taiwanese companies expanding manufacturing in America are doing so because it makes business sense. “Taiwan is doing it voluntarily because of its own wisdom, not because it's held a gun to its head,” Huang said. He described the relationship between American and Taiwanese technology companies as one built over decades of cooperation and trust. A sharp contrast with Trump's 'stolen' chip claim Huang did not name US President Donald Trump. But his comments offer a sharply different interpretation of how Taiwan became a semiconductor powerhouse. Trump has repeatedly accused Taiwan of taking America's semiconductor business and argued that previous US governments should have used tariffs to prevent chip manufacturing from shifting overseas. Taiwan has rejected that characterisation, arguing that its semiconductor industry was built through decades of investment, engineering expertise and the development of a highly specialised manufacturing ecosystem. Huang's argument goes further: Taiwan's rise, in his view, helped American technology companies remain competitive. Nvidia's latest AI superchips are now being made in Texas The setting for Huang's comments was significant. Wistron's new D1 facility in Fort Worth is a 324,000-square-foot manufacturing plant backed by a $700 million investment. The facility is already mass-producing Nvidia's GB300 Grace Blackwell Ultra Superchip in the United States. It is also expected to manufacture Nvidia's next-generation Vera Rubin Superchip. Wistron says the site has created more than 500 jobs, with plans to expand that number to around 1,000 by the end of 2026. For Nvidia, this represents something bigger than opening another factory. The company is trying to build more of the physical infrastructure behind the AI boom inside America from chips and packaging to servers and complete AI systems. And there is an irony at the centre of that effort. As Washington pushes to bring advanced technology manufacturing back to American soil, some of the companies helping make that possible are precisely the Taiwanese manufacturers that Huang believes America should be thanking rather than blaming.

Nvidia CEO Jensen Huang says Taiwan “saved” America's semiconductor and computing industries, challenging claims that it took US chip manufacturing away. His remarks came as Taiwan's Wistron opened a $700 million Nvidia AI manufacturing facility in Texas.

'Not the opposite': Jensen Huang says Taiwan saved US chip industry

Nvidia has offered its clearest look yet at Vera Rubin, the AI platform it hopes will power the next generation of artificial intelligence. During a technical briefing at its headquarters in Santa Clara, California, the company revealed fresh performance figures for the new chip system ahead of AMD's annual AI event. Nvidia says the Vera Rubin NVL72 platform can process 10 times more AI tokens per watt than its current Grace Blackwell system, while delivering significantly higher memory bandwidth and easier deployment.The announcement highlights a major shift in Nvidia's strategy. The company no longer wants to be seen only as the world's leading GPU maker it also wants to become a supplier of complete AI computing systems.<h2>Nvidia is betting on CPUs too</h2>Graphics Processing Units (GPUs) remain the backbone of AI training, but modern AI agents also rely heavily on Central Processing Units (CPUs) to manage data, networking and software operations.Vera Rubin reflects that change.Each NVL72 rack combines 72 Rubin GPUs with 36 Vera CPUs, creating an integrated platform designed for large AI workloads. Nvidia is also planning to sell the Vera CPU separately, expanding its push into a market traditionally dominated by AMD and Intel."We're on a roadmap to crank out new architectures not just GPUs but CPUs," Nvidia Vice President Ian Buck said during the briefing.<h2>Faster, cooler and easier to install</h2>Nvidia says Vera Rubin introduces several practical improvements for data centres.The company has redesigned the platform to use 100 per cent liquid cooling, reducing energy needed for cooling. It has also dramatically reduced cabling, allowing server racks to be installed or replaced in minutes instead of hours.Another key improvement is memory performance. Nvidia claims Vera Rubin offers nearly three times the memory bandwidth of Grace Blackwell, an important advantage as AI models continue to grow in size. The company also revealed that OpenAI is already testing a Vera Rubin rack as an early customer.<h2>A crucial launch in the AI chip race</h2>Vera Rubin arrives at a critical moment for Nvidia. The company is competing aggressively with AMD, which is expected to showcase its Helios AI platform, while cloud providers including Microsoft, Oracle, Meta and Amazon continue investing billions of dollars in AI infrastructure.Nvidia also faces pressure to execute flawlessly after earlier reports of overheating issues affecting some Blackwell server configurations. According to Nvidia, Vera Rubin remains on schedule for full production in the second half of this year. As AI models become larger and more capable, the competition is no longer just about building the fastest GPU. Companies now need complete AI systems that combine processing power, networking, memory efficiency and energy savings and Nvidia is betting Vera Rubin will keep it ahead in that race.

Nvidia has unveiled new performance details for its Vera Rubin AI platform, claiming up to 10 times better token-per-watt efficiency than Grace Blackwell. The system combines CPUs and GPUs to power advanced AI workloads as competition with AMD intensifies.

Nvidia has offered its clearest look yet at Vera Rubin, the AI platform it hopes will power the next generation of artificial intelligence. During a technical briefing at its headquarters in Santa Clara, California, the company revealed fresh performance figures for the new chip system ahead of AMD's annual AI event. Nvidia says the Vera Rubin NVL72 platform can process 10 times more AI tokens per watt than its current Grace Blackwell system, while delivering significantly higher memory bandwidth and easier deployment. The announcement highlights a major shift in Nvidia's strategy. The company no longer wants to be seen only as the world's leading GPU maker it also wants to become a supplier of complete AI computing systems. Nvidia is betting on CPUs too Graphics Processing Units (GPUs) remain the backbone of AI training, but modern AI agents also rely heavily on Central Processing Units (CPUs) to manage data, networking and software operations. Vera Rubin reflects that change. Each NVL72 rack combines 72 Rubin GPUs with 36 Vera CPUs, creating an integrated platform designed for large AI workloads. Nvidia is also planning to sell the Vera CPU separately, expanding its push into a market traditionally dominated by AMD and Intel. "We're on a roadmap to crank out new architectures not just GPUs but CPUs," Nvidia Vice President Ian Buck said during the briefing. Faster, cooler and easier to install Nvidia says Vera Rubin introduces several practical improvements for data centres. The company has redesigned the platform to use 100 per cent liquid cooling, reducing energy needed for cooling. It has also dramatically reduced cabling, allowing server racks to be installed or replaced in minutes instead of hours. Another key improvement is memory performance. Nvidia claims Vera Rubin offers nearly three times the memory bandwidth of Grace Blackwell, an important advantage as AI models continue to grow in size. The company also revealed that OpenAI is already testing a Vera Rubin rack as an early customer. A crucial launch in the AI chip race Vera Rubin arrives at a critical moment for Nvidia. The company is competing aggressively with AMD, which is expected to showcase its Helios AI platform, while cloud providers including Microsoft, Oracle, Meta and Amazon continue investing billions of dollars in AI infrastructure. Nvidia also faces pressure to execute flawlessly after earlier reports of overheating issues affecting some Blackwell server configurations. According to Nvidia, Vera Rubin remains on schedule for full production in the second half of this year. As AI models become larger and more capable, the competition is no longer just about building the fastest GPU. Companies now need complete AI systems that combine processing power, networking, memory efficiency and energy savings and Nvidia is betting Vera Rubin will keep it ahead in that race.

Nvidia has unveiled new performance details for its Vera Rubin AI platform, claiming up to 10 times better token-per-watt efficiency than Grace Blackwell. The system combines CPUs and GPUs to power advanced AI workloads as competition with AMD intensifies.

Nvidia says its next AI superchip is 10 times more efficient than Blackwell

Meta is preparing for one of its biggest artificial intelligence infrastructure upgrades yet. According to an internal company memo reviewed by Reuters, the company plans to begin manufacturing its next-generation AI chip, codenamed Iris, in September 2026.The chip is part of Meta's long-term Meta Training and Inference Accelerator (MTIA) programme, under which the company is developing its own AI processors instead of relying entirely on third-party suppliers. The goal is to improve the AI systems powering Facebook, Instagram and other Meta products while reducing computing costs.The reported production follows six weeks of successful testing, during which engineers found no major issues with the chip.<h2>Why is Meta building its own AI chip?</h2>Running advanced AI models requires enormous computing power, and buying large numbers of graphics processing units (GPUs) from companies such as Nvidia and AMD has become increasingly expensive.Meta believes custom-designed chips can perform many AI tasks more efficiently while giving the company greater control over its infrastructure.The Iris processor has been designed with help from Broadcom, while Taiwan Semiconductor Manufacturing Co. (TSMC) will manufacture the chip. Industry analysts say nearly every major AI company is now pursuing custom silicon to reduce costs and avoid dependence on external chip suppliers.<h2>Meta plans to double computing capacity</h2>The Reuters memo shows Meta expects to deploy around 7 gigawatts (GW) of computing infrastructure by the end of 2026 before doubling that figure to 14GW in 2027.For comparison, 1GW of electricity can power roughly 800,000 homes. Such a rapid expansion highlights the enormous energy requirements of modern AI systems. Meta also expects to spend up to $145 billion this year on AI infrastructure, making it one of the biggest investors in artificial intelligence globally.<h2>The AI hardware race is accelerating</h2>Meta's chip strategy reflects a broader industry trend. Google has its Tensor Processing Units (TPUs), Amazon has Trainium and Inferentia, while Microsoft, OpenAI and Anthropic are also exploring custom AI hardware.According to the memo, Meta plans to introduce a new AI chip roughly every six months through 2027, a much faster release cycle than the industry's traditional annual updates. The company has also secured long-term supply agreements with Samsung Electronics for memory chips, Sandisk for storage and Sumitomo Electric for fibre-optic equipment as it expands its global data centre network. With AI demand continuing to grow, owning more of its hardware stack could become one of Meta's biggest competitive advantages in the years ahead.&nbsp;

Meta will reportedly begin producing its new Iris AI chip in September after successful testing. The custom processor is part of the company's plan to double computing capacity to 14GW by 2027, reduce dependence on Nvidia and support growing AI services across its platforms.

Meta is preparing for one of its biggest artificial intelligence infrastructure upgrades yet. According to an internal company memo reviewed by Reuters, the company plans to begin manufacturing its next-generation AI chip, codenamed Iris, in September 2026. The chip is part of Meta's long-term Meta Training and Inference Accelerator (MTIA) programme, under which the company is developing its own AI processors instead of relying entirely on third-party suppliers. The goal is to improve the AI systems powering Facebook, Instagram and other Meta products while reducing computing costs. The reported production follows six weeks of successful testing, during which engineers found no major issues with the chip. Why is Meta building its own AI chip? Running advanced AI models requires enormous computing power, and buying large numbers of graphics processing units (GPUs) from companies such as Nvidia and AMD has become increasingly expensive. Meta believes custom-designed chips can perform many AI tasks more efficiently while giving the company greater control over its infrastructure. The Iris processor has been designed with help from Broadcom, while Taiwan Semiconductor Manufacturing Co. (TSMC) will manufacture the chip. Industry analysts say nearly every major AI company is now pursuing custom silicon to reduce costs and avoid dependence on external chip suppliers. Meta plans to double computing capacity The Reuters memo shows Meta expects to deploy around 7 gigawatts (GW) of computing infrastructure by the end of 2026 before doubling that figure to 14GW in 2027. For comparison, 1GW of electricity can power roughly 800,000 homes. Such a rapid expansion highlights the enormous energy requirements of modern AI systems. Meta also expects to spend up to $145 billion this year on AI infrastructure, making it one of the biggest investors in artificial intelligence globally. The AI hardware race is accelerating Meta's chip strategy reflects a broader industry trend. Google has its Tensor Processing Units (TPUs), Amazon has Trainium and Inferentia, while Microsoft, OpenAI and Anthropic are also exploring custom AI hardware. According to the memo, Meta plans to introduce a new AI chip roughly every six months through 2027, a much faster release cycle than the industry's traditional annual updates. The company has also secured long-term supply agreements with Samsung Electronics for memory chips, Sandisk for storage and Sumitomo Electric for fibre-optic equipment as it expands its global data centre network. With AI demand continuing to grow, owning more of its hardware stack could become one of Meta's biggest competitive advantages in the years ahead.

Meta will reportedly begin producing its new Iris AI chip in September after successful testing. The custom processor is part of the company's plan to double computing capacity to 14GW by 2027, reduce dependence on Nvidia and support growing AI services across its platforms.

Meta plans a new AI chip every six months: Here's how its next chip could reduce dependence on Nvidia

Global tech stocks are under pressure, but Nvidia’s boss says: don’t panic. In fact, he says, now is the time to buy.

Jensen Huang Shrugs Off Global Tech Rout

NVIDIA is drawing strong attention on Wall Street after reports suggest the company now holds more cash than it owes, strengthening its financial position. Investors are increasingly betting on NVIDIA’s growth potential, with some analysts even comparing its market influence to that of governments. The surge highlights growing confidence in the company’s dominance in AI, chips, and next-generation computing technologies.


NVIDIA Holds More Cash Than It Owes, Wall Street Bets on NVIDIA Over the US Government 

Something extraordinary is happening on Wall Street. For the first time, investors consider NVIDIA to be less likely to default on its debts,
Than the United States federal government. In this report, We dive into the details of why Wall Street is betting big on the AI darling.

NVIDIA Becomes Wall Street’s Safe Haven Amid US Debt Fears

In a remarkable sign of investor confidence, chipmaker NVIDIA is now being viewed by parts of the market as a safer credit bet than the US government. Fueled by the global AI boom and strong demand for its advanced chips, Nvidia's financial standing has strengthened dramatically. The development highlights how rapidly the company has risen from a semiconductor manufacturer to one of the world's most influential technology firms, reshaping discussions around market confidence, risk and the future of artificial intelligence.


Nvidia Overtakes US Government in Market Credit Rankings as Investor Confidence Soar

As most of the Silicon Valley giants are carrying out a massive exodus of employees, NVIDIA is on a hiring boom with huge paychecks. The majority of them are immigrant workers. According to the Federal Labour filings, NVIDIA has secured approximately 1,200 visa certifications during the first two quarters of the fiscal year 2026. This represents a 20 per cent increase from roughly 1000 applications approved during the same time frame the previous year. While this marks an increase in the H1B hiring for NVIDIA, it remains a long way off from other Silicon Valley companies like Alphabet and Amazon, which have 2,200 and 4,300 certifications in the H1FY26, down from 5,100 and 6100 in the same period the previous year, respectively.<h2>How much are Indians benefiting from the NVIDIA hiring boom?</h2>Indian technology professionals are the primary beneficiaries of the NVIDIA hiring boom both in the United States and within India's domestic tech hubs. Indian nationals historically secured 71-73 per cent of all H-1B visas in the US, so NVIDIA's rapid expansion of H1B hiring will likely disproportionately benefit Indian talent. According to the Federal Filings, NVIDIA is offering lucrative packages in basic salaries, excluding stock grants and bonuses, which can significantly increase overall compensation. An individual contributor can earn from a range of $356,500- $391,000 per annum, for roles like software engineer, research scientist, product manager, and hardware engineering manager. While Director-level roles are more lucrative, like architecture directors can earn up to $488,750, in base salary alone. However, the whole H1B segment has seen a structural overhaul, and the $100,000 "entry restriction" fee has made the immigration process move from a random lottery to a high-wage, high-skill selection model. This has helped Silicon Valley giants like NVIDIA, Alphabet and Amazon while pushing others like TCS, Infosys and Wipro out of the market.&nbsp;Also Read: <a href="https://www.wionews.com/world/trump-one-nation-under-god-christian-nationalism-debate-1779189316728">‘Make America Christian’: How Trump’s Christian nationalist messaging challenges America’s civic identity</a><h2>What is driving this hiring boom at NVIDIA?</h2>NVIDIA, which has been the leading beneficiary of the AI boon, posted its Q1 Fiscal Year 2027 financial results on May 20, 2026. It has recorded a massive year-over-year revenue growth of 85 per cent. It jumped to $81.62 billion from the $44.06 billion it reported in the same quarter last year. The data centre segment has recorded $75.2 billion in a single quarter. This is more than most Fortune 500 companies. NVIDIA is not just a supplier of the current AI wave; it is building the dedicated AI infrastructure for the AI wave.&nbsp;

NVIDIA is ramping up H-1B hiring and offering lucrative salaries as its AI-driven growth accelerates. Indian tech professionals are among the biggest beneficiaries of the recruitment surge.

As most of the Silicon Valley giants are carrying out a massive exodus of employees, NVIDIA is on a hiring boom with huge paychecks. The majority of them are immigrant workers. According to the Federal Labour filings, NVIDIA has secured approximately 1,200 visa certifications during the first two quarters of the fiscal year 2026. This represents a 20 per cent increase from roughly 1000 applications approved during the same time frame the previous year. While this marks an increase in the H1B hiring for NVIDIA, it remains a long way off from other Silicon Valley companies like Alphabet and Amazon, which have 2,200 and 4,300 certifications in the H1FY26, down from 5,100 and 6100 in the same period the previous year, respectively. How much are Indians benefiting from the NVIDIA hiring boom? Indian technology professionals are the primary beneficiaries of the NVIDIA hiring boom both in the United States and within India's domestic tech hubs. Indian nationals historically secured 71-73 per cent of all H-1B visas in the US, so NVIDIA's rapid expansion of H1B hiring will likely disproportionately benefit Indian talent. According to the Federal Filings, NVIDIA is offering lucrative packages in basic salaries, excluding stock grants and bonuses, which can significantly increase overall compensation. An individual contributor can earn from a range of $356,500- $391,000 per annum, for roles like software engineer, research scientist, product manager, and hardware engineering manager. While Director-level roles are more lucrative, like architecture directors can earn up to $488,750, in base salary alone. However, the whole H1B segment has seen a structural overhaul, and the $100,000 "entry restriction" fee has made the immigration process move from a random lottery to a high-wage, high-skill selection model. This has helped Silicon Valley giants like NVIDIA, Alphabet and Amazon while pushing others like TCS, Infosys and Wipro out of the market. Also Read: ‘Make America Christian’: How Trump’s Christian nationalist messaging challenges America’s civic identity What is driving this hiring boom at NVIDIA? NVIDIA, which has been the leading beneficiary of the AI boon, posted its Q1 Fiscal Year 2027 financial results on May 20, 2026. It has recorded a massive year-over-year revenue growth of 85 per cent. It jumped to $81.62 billion from the $44.06 billion it reported in the same quarter last year. The data centre segment has recorded $75.2 billion in a single quarter. This is more than most Fortune 500 companies. NVIDIA is not just a supplier of the current AI wave; it is building the dedicated AI infrastructure for the AI wave.

NVIDIA is ramping up H-1B hiring and offering lucrative salaries as its AI-driven growth accelerates. Indian tech professionals are among the biggest beneficiaries of the recruitment surge.

NVIDIA expands H-1B hiring while other Silicon Valley giants cut back

NVIDIA is expanding its push into the AI PC market with the launch of a new chip designed to bring advanced artificial intelligence capabilities directly to personal computers. The move highlights growing competition in the AI hardware space as tech companies race to power the next generation of AI-driven devices and applications.


NVIDIA Gets Big On AI PCs With New Chip

Nvidia is overtaking traditional chipmakers by powering the Microsoft Surface Laptop Ultra with its RTX Spark superchip. Featuring up to 128GB of unified memory and 1 petaflop of AI compute, the chip allows users to run massive 120-billion parameter models locally.


‘Nvidia vs traditional chipmakers’: How Nvidia is winning the race that traditional chipmakers started

Microsoft has introduced the Surface Laptop Ultra, a new premium laptop developed in partnership with Nvidia that the company describes as its most powerful Surface device to date. The announcement marks a significant step in Microsoft's AI PC strategy as the company looks to bring advanced artificial intelligence capabilities directly onto personal computers.

<blockquote class="twitter-tweet">Introducing Surface Laptop Ultra. Built for world makers. Designed for what&#39;s next. The most powerful Surface laptop ever. Coming Fall 2026. Sign up to learn more: <a href="https://t.co/k8aEX2pTAy">https://t.co/k8aEX2pTAy</a> <a href="https://t.co/bY1NdzNnie">pic.twitter.com/bY1NdzNnie</a>&mdash; Microsoft Surface (@surface) <a href="https://x.com/surface/status/2061329225886453989?ref_src=twsrc%5Etfw">June 1, 2026</a></blockquote> <script async src="https://platform.x.com/widgets.js" charset="utf-8"></script>

The new device is powered by Nvidia's RTX Spark processor, an Arm-based chip designed to handle demanding AI workloads while maintaining the portability and battery life expected from modern laptops. Microsoft says the Surface Laptop Ultra represents years of collaboration between the two companies on Windows on Arm and AI-focused computing.<h2>What is the Surface Laptop Ultra?</h2>The Surface Laptop Ultra is a 15-inch laptop built around Nvidia's new RTX Spark platform. It is the first major Surface device to combine Microsoft's Windows ecosystem with Nvidia's latest Arm-based AI computing architecture. The launch is particularly notable because it marks Microsoft's renewed effort to build premium Arm-powered computers. Earlier attempts faced challenges, but advances in AI processing, chip design and software optimisation have created new opportunities for Arm-based Windows devices.Microsoft says the laptop has been designed for creators, developers, AI researchers and professionals who need high-performance computing in a portable form factor.RTX Spark: The chip at the centre of Microsoft's AI pushThe biggest talking point is Nvidia's RTX Spark processor.According to Microsoft and Nvidia, the chip can feature:Up to 20 CPU coresUp to 6,144 GPU coresUp to 128GB unified memoryAI performance approaching 1 petaflopDedicated AI acceleration capabilitiesThe architecture is based on technology previously used in Nvidia's DGX Spark systems for AI developers. It has now been adapted for Windows devices, allowing advanced AI applications to run locally on the machine rather than relying entirely on cloud infrastructure. Industry observers see this as part of a wider trend where AI workloads are increasingly moving closer to the user rather than being processed exclusively in remote data centres.<h2>Designed for AI, creators and developers</h2>Microsoft says the Surface Laptop Ultra has been built for users handling demanding workloads such as AI model development, video editing, software development, 3D design and content creation. The company claims graphics performance is comparable to laptops equipped with Nvidia RTX 5070-class hardware, while AI processing capabilities are designed to support increasingly complex local AI applications. As businesses and consumers adopt more AI-powered tools, hardware manufacturers are focusing on devices capable of running these workloads efficiently without sacrificing portability.<h2>Display, design and battery life</h2>The Surface Laptop Ultra features a 15-inch mini-LED display with a pixel density of 262 pixels per inch. Microsoft says it is the brightest display ever used in a Surface device, with peak HDR brightness reaching 2,000 nits. The company has also introduced its largest Surface trackpad to date, complete with haptic feedback technology. The laptop weighs around 2 kilograms and will be available in silver and dark grey finishes.Microsoft also says the device is designed to deliver all-day battery life, although detailed battery performance figures have not yet been released.<h2>Ports and connectivity</h2> Unlike many premium laptops that have reduced port options, the Surface Laptop Ultra includes a broad selection of connectivity features.The company has confirmed support for:USB-C USB-A HDMI Full-size SD card slot 3.5mm headphone jackMicrosoft has not yet disclosed the full technical specifications for these ports, including transfer speeds and supported standards.<h2>Why this launch matters</h2>The launch is important not only because of the hardware itself but also because it highlights a deeper partnership between Microsoft and Nvidia. The two companies have spent years working on Windows on Arm and AI-focused computing. The Surface Laptop Ultra is one of the first major products to emerge from that collaboration. It also reflects a growing industry shift towards AI PCs. Companies including Microsoft, Apple, Qualcomm, AMD and Intel are all investing heavily in devices designed specifically for artificial intelligence workloads.Rather than focusing only on traditional performance metrics, manufacturers are increasingly highlighting AI processing power, memory bandwidth and on-device AI capabilities.<h2>More RTX Spark devices are expected</h2>Microsoft has indicated that the Surface Laptop Ultra will not be the only product based on Nvidia's RTX Spark platform. According to the companies, the architecture is expected to appear in additional laptops and compact desktop systems in the future. This suggests that RTX Spark could become a broader ecosystem rather than a single flagship device.As AI becomes a larger part of everyday computing, Microsoft and Nvidia appear to be positioning themselves at the centre of the next generation of personal computers. The Surface Laptop Ultra is expected to launch later in 2026, although Microsoft has not yet announced pricing or exact availability dates. For now, the announcement provides a glimpse into how Microsoft sees the future of computing: powerful AI capabilities running directly on devices, supported by specialised hardware and deep integration between software and silicon. Whether the Surface Laptop Ultra can reshape the Windows laptop market remains to be seen, but it clearly signals Microsoft's determination to compete aggressively in the emerging AI PC era.&nbsp;

Microsoft has introduced the Surface Laptop Ultra, a new premium laptop developed in partnership with Nvidia that the company describes as its most powerful Surface device to date. 

Microsoft has introduced the Surface Laptop Ultra, a new premium laptop developed in partnership with Nvidia that the company describes as its most powerful Surface device to date. The announcement marks a significant step in Microsoft's AI PC strategy as the company looks to bring advanced artificial intelligence capabilities directly onto personal computers.

Microsoft has introduced the Surface Laptop Ultra, a new premium laptop developed in partnership with Nvidia that the company describes as its most powerful Surface device to date.&nbsp;

Microsoft unveils Surface Laptop Ultra with Nvidia RTX Spark chip: Key things to know

Nvidia on Monday (Jun 1) unveiled a powerful laptop chip for Windows laptops, entering the market for AI-powered PC that is dominated by established players such as Intel, AMD and Qualcomm. The move marks Nvidia’s most significant push into personal computing in more than a decade and comes as the company seeks to extend its dominance beyond data centres and into devices.According to analysts, Nvidia’s entry into the personal computer processor market puts it in direct competition with industry heavyweights such as Apple, Intel and AMD. However, they expect the AI-focused devices to launch at premium price points. Although the company also plans to introduce more affordable versions of the technology in the future.The move also reflects Nvidia's broader strategy to expand beyond its dominant data centre business and strengthen its presence in the consumer technology market. The company, which has emerged as the world’s most valuable firm amid the artificial intelligence boom, continues to benefit from surging demand for its AI chips from major global technology companies.Speaking at the Computex technology exhibition, Nvidia CEO Jensen Huang described the new RTX Spark Superchip as a transformative step for personal computing.“Microsoft and Nvidia are going to reinvent the PC. This is going to be the new PC,” Huang said during the launch event.Highlighting the system’s capabilities, Huang said the platform would be powerful enough to handle a wide range of demanding workloads, from digital biology and seismic analysis to astrophysics research.“If you want to run digital biology, no problem. If you want to do seismic processing, no problem. You want astrophysics, no problem,” Huang said.He added that years of collaboration between Microsoft and Nvidia had resulted in a platform capable of running virtually all existing software while also supporting advanced AI agents and next-generation artificial intelligence applications.“Microsoft and Nvidia meticulously optimised everything so that this computer literally runs everything the world has ever created, while also enabling powerful AI agents,” Huang said, calling it “an incredible computer.”

Nvidia unveils AI-powered laptop chip for Windows PCs, challenging Intel, AMD and Qualcomm, as CEO Jensen Huang calls it the “new PC” revolution.

Nvidia on Monday (Jun 1) unveiled a powerful laptop chip for Windows laptops, entering the market for AI-powered PC that is dominated by established players such as Intel, AMD and Qualcomm. The move marks Nvidia’s most significant push into personal computing in more than a decade and comes as the company seeks to extend its dominance beyond data centres and into devices. According to analysts, Nvidia’s entry into the personal computer processor market puts it in direct competition with industry heavyweights such as Apple, Intel and AMD. However, they expect the AI-focused devices to launch at premium price points. Although the company also plans to introduce more affordable versions of the technology in the future. The move also reflects Nvidia's broader strategy to expand beyond its dominant data centre business and strengthen its presence in the consumer technology market. The company, which has emerged as the world’s most valuable firm amid the artificial intelligence boom, continues to benefit from surging demand for its AI chips from major global technology companies. Speaking at the Computex technology exhibition, Nvidia CEO Jensen Huang described the new RTX Spark Superchip as a transformative step for personal computing. “Microsoft and Nvidia are going to reinvent the PC. This is going to be the new PC,” Huang said during the launch event. Highlighting the system’s capabilities, Huang said the platform would be powerful enough to handle a wide range of demanding workloads, from digital biology and seismic analysis to astrophysics research. “If you want to run digital biology, no problem. If you want to do seismic processing, no problem. You want astrophysics, no problem,” Huang said. He added that years of collaboration between Microsoft and Nvidia had resulted in a platform capable of running virtually all existing software while also supporting advanced AI agents and next-generation artificial intelligence applications. “Microsoft and Nvidia meticulously optimised everything so that this computer literally runs everything the world has ever created, while also enabling powerful AI agents,” Huang said, calling it “an incredible computer.”

Nvidia unveils AI-powered laptop chip for Windows PCs, challenging Intel, AMD and Qualcomm, as CEO Jensen Huang calls it the “new PC” revolution.

‘Reinventing PC’: Nvidia unveils new chip for Windows laptops, challenging Intel, AMD

Nvidia CEO Jensen Huang has gone viral after videos showed him dancing alongside employees during a company event in Taipei, Taiwan.The clips, which have been widely shared across social media platforms, show Huang joining staff members on stage during Nvidia's Constellation All-Employee Celebration. The videos quickly attracted attention online, with many users praising the technology executive's relaxed and approachable personality. The moment comes at a time when Nvidia remains one of the most closely watched companies in the global artificial intelligence industry, making Huang one of the most recognised business leaders in the world.

<blockquote class="twitter-tweet" data-media-max-width="560">🇺🇸Jensen Huang is out there living his best life, dancing at the NVIDIA all-employee celebration event in Taipei, Taiwan You&#39;d never guess he&#39;s the CEO 😂<a href="https://t.co/LsLTsMfPqd">pic.twitter.com/LsLTsMfPqd</a>&mdash; Mario Nawfal (@MarioNawfal) <a href="https://x.com/MarioNawfal/status/2060683137324126491?ref_src=twsrc%5Etfw">May 30, 2026</a></blockquote> <script async src="https://platform.x.com/widgets.js" charset="utf-8"></script>

<h2>What happened at the Nvidia event?</h2>During the employee celebration in Taipei, Huang stepped onto the stage and joined a dance performance with Nvidia staff members. Videos from the event show the Nvidia chief matching dance moves with employees while interacting with the audience. The performance drew applause and cheers from attendees and soon spread across social media platforms including X and Instagram. Many viewers were surprised to see the leader of one of the world's most valuable technology companies taking part in such a light-hearted moment.The clips quickly generated millions of views and became one of the most discussed moments from Nvidia's activities in Taiwan this week.<h2>Why are people talking about the video?</h2>Much of the online reaction focused on Huang's leadership style and his relationship with employees. Many users said the video reflected a workplace culture where senior leadership remains accessible and engaged with staff. Others pointed to the contrast between Huang's role as the head of a company worth trillions of dollars and his willingness to participate in informal employee activities.Comments on social media described Huang as "down-to-earth", while others said the video showed a more personal side of one of the technology industry's most influential figures. The reaction also reflects Huang's growing popularity beyond the technology sector. Over the past two years, his public profile has risen significantly alongside Nvidia's success in artificial intelligence and advanced computing.<h2>How Jensen Huang became one of tech's most recognisable leaders</h2>Huang co-founded NVIDIA in 1993 and has led the company for more than three decades. Under his leadership, Nvidia transformed from a graphics chip manufacturer into one of the most important companies powering the global AI boom. The company's processors are widely used for training and running advanced artificial intelligence models. As demand for AI computing increased, Nvidia's market value surged, making it one of the world's most valuable publicly traded companies. Unlike many technology executives, Huang has also become known for his public appearances, interactions with customers and regular engagement with employees.The viral dance video is not the first time Huang has attracted attention outside the boardroom During previous visits to Asia, he has been seen participating in cultural activities, visiting local markets and interacting with the public. In Taiwan, he has frequently been spotted at popular night markets and restaurants, where crowds often gather to take photographs and speak with him.These appearances have helped build his reputation as one of the more approachable leaders in the technology industry. Industry observers say Huang's public image has become an important part of Nvidia's brand as the company continues expanding its influence across AI, cloud computing and data centre technologies. Huang is currently in Taiwan attending major artificial intelligence events and meetings with industry leaders. According to local reports, he is expected to travel to South Korea next week, where he will meet executives from companies including SK Group, Hyundai Motor Group, LG Corp and Naver. Discussions are expected to focus on AI infrastructure, robotics, semiconductor technology and the future of physical AI systems. These meetings come as countries and companies across Asia continue investing heavily in artificial intelligence and next-generation computing technologies.

Nvidia CEO Jensen Huang has gone viral after videos showed him dancing alongside employees during a company event in Taipei, Taiwan.


Nvidia CEO Jensen Huang has gone viral after videos showed him dancing alongside employees during a company event in Taipei, Taiwan. The clips, which have been widely shared across social media platforms, show Huang joining staff members on stage during Nvidia's Constellation All-Employee Celebration. The videos quickly attracted attention online, with many users praising the technology executive's relaxed and approachable personality. The moment comes at a time when Nvidia remains one of the most closely watched companies in the global artificial intelligence industry, making Huang one of the most recognised business leaders in the world.

Nvidia CEO Jensen Huang has gone viral after videos showed him dancing alongside employees during a company event in Taipei, Taiwan.

Nvidia CEO Jensen Huang goes viral after dancing with employees in Taiwan

NVIDIA, which has been a leading beneficiary of the AI boon, reported its Q1 Fiscal Year 2027 financial results on May 20, 2026. It has recorded a massive year-over-year revenue growth of 85 per cent, jumping to $81.62 billion from the $44.06 billion it reported in the same quarter last year. As of May 2026, its market cap is $5.41 trillion, solidifying its position as the most valuable company in the world, closely followed by Alphabet at $4.6 trillion and Apple at $4.3 trillion. These are historic numbers. For the Q1FY27, the reported net income is $58.3 billion, a 211 per cent jump from $18.8 billion a year ago.<h2>Why is NVIDIA the biggest winner?</h2>The major revenue driver for NVIDIA was the data centre segment, $75.2 billion in a single quarter, up by 92 per cent year-on-year. This is more than most Fortune 500 companies earn in an entire financial year. This implies that the majority of the private capital raised by AI companies flows directly to NVIDIA's bottom line, and it then reinvests the margin into the AI companies. NVIDIA is not just a supplier of the current AI wave; it is building the dedicated AI infrastructure for the AI wave. It exemplifies the ouroboros of the AI ecosystem.&nbsp;Also Read: <a href="https://www.wionews.com/world/who-is-vanessa-trump-breast-cancer-diagnosis-donald-trump-jr-1779365736602">Who Is Vanessa Trump? Former model and Donald Trump Jr ex-wife diagnosed with breast cancer</a>This is further evident from the Cerebras system's IPO debut last week. The company’s market cap swelled to almost $100 billion on its first day of trading. The company makes ASIC application-specific integrated circuits, programmed for more specific tasks. While these are not as powerful as GPUs used for Large Language Models, they are also efficient for Agentic AI, with the growing computing shift towards inference. The space is increasingly becoming crowded with &nbsp;Google, Amazon, Meta and Microsoft all making ASCIs. Over 1,000 startups are available in the Agentic AI segment, while 20 are public. Among them, 13 are making real profit, which are legacy companies such as Microsoft, Salesforce, ServiceNow, and IBM, which have enterprise software monopolies or hardware giants. About 7 of the breakout companies in this cohort are still losing money on a net basis.&nbsp;What makes the number more troubling is that in the years before the generative AI craze, Nvidia was primarily known for its gaming chips. In fiscal 2020, over half its revenue came from gaming, while just 27 per cent came from the data centre. The SpaceX SEC filings also shed light on AI infrastructure and its burn rate. Over all its operating at a nearly $4.3 billion loss in the quarter, the multi-billion dollar losses are driven by massive capital expenditures. Starlink is the segment where the company generates actual operational profit. The loss-making parts are xAI, X, and Starship. It is seeking $75 billion at a valuation of $1.75 trillion to $2 trillion, 100 times more than its revenue, speculating on future potential. But the loss acceleration is humongous, $528 million quarterly to $4.3 billion in one year. The whole picture will become clearer with the public disclosure of OpenAI and Anthropic. Every company in the AI stack is an NVIDIA customer, and it is the only one that's unambiguously profitable, while others are seeking public money to survive.&nbsp;

NVIDIA reported record Q1 FY2027 revenue of $81.6 billion, driven by explosive AI data centre demand, as questions grow over whether the broader AI ecosystem is profitable beyond chipmakers.

NVIDIA, which has been a leading beneficiary of the AI boon, reported its Q1 Fiscal Year 2027 financial results on May 20, 2026. It has recorded a massive year-over-year revenue growth of 85 per cent, jumping to $81.62 billion from the $44.06 billion it reported in the same quarter last year. As of May 2026, its market cap is $5.41 trillion, solidifying its position as the most valuable company in the world, closely followed by Alphabet at $4.6 trillion and Apple at $4.3 trillion. These are historic numbers. For the Q1FY27, the reported net income is $58.3 billion, a 211 per cent jump from $18.8 billion a year ago. Why is NVIDIA the biggest winner? The major revenue driver for NVIDIA was the data centre segment, $75.2 billion in a single quarter, up by 92 per cent year-on-year. This is more than most Fortune 500 companies earn in an entire financial year. This implies that the majority of the private capital raised by AI companies flows directly to NVIDIA's bottom line, and it then reinvests the margin into the AI companies. NVIDIA is not just a supplier of the current AI wave; it is building the dedicated AI infrastructure for the AI wave. It exemplifies the ouroboros of the AI ecosystem. Also Read: Who Is Vanessa Trump? Former model and Donald Trump Jr ex-wife diagnosed with breast cancer This is further evident from the Cerebras system's IPO debut last week. The company’s market cap swelled to almost $100 billion on its first day of trading. The company makes ASIC application-specific integrated circuits, programmed for more specific tasks. While these are not as powerful as GPUs used for Large Language Models, they are also efficient for Agentic AI, with the growing computing shift towards inference. The space is increasingly becoming crowded with Google, Amazon, Meta and Microsoft all making ASCIs. Over 1,000 startups are available in the Agentic AI segment, while 20 are public. Among them, 13 are making real profit, which are legacy companies such as Microsoft, Salesforce, ServiceNow, and IBM, which have enterprise software monopolies or hardware giants. About 7 of the breakout companies in this cohort are still losing money on a net basis. What makes the number more troubling is that in the years before the generative AI craze, Nvidia was primarily known for its gaming chips. In fiscal 2020, over half its revenue came from gaming, while just 27 per cent came from the data centre. The SpaceX SEC filings also shed light on AI infrastructure and its burn rate. Over all its operating at a nearly $4.3 billion loss in the quarter, the multi-billion dollar losses are driven by massive capital expenditures. Starlink is the segment where the company generates actual operational profit. The loss-making parts are xAI, X, and Starship. It is seeking $75 billion at a valuation of $1.75 trillion to $2 trillion, 100 times more than its revenue, speculating on future potential. But the loss acceleration is humongous, $528 million quarterly to $4.3 billion in one year. The whole picture will become clearer with the public disclosure of OpenAI and Anthropic. Every company in the AI stack is an NVIDIA customer, and it is the only one that's unambiguously profitable, while others are seeking public money to survive.

NVIDIA reported record Q1 FY2027 revenue of $81.6 billion, driven by explosive AI data centre demand, as questions grow over whether the broader AI ecosystem is profitable beyond chipmakers.

NVIDIA posts record $81.6 billion revenue: Why NVIDIA is the biggest winner of the global AI boom

Alphabet is on the brink of overtaking NVIDIA as the world’s most valuable company.
The AI darling, NVIDIA, may be the leader in AI chips,
But Alphabet is emerging as big tech's broader winner in recent months.

Alphabet Close to Overtaking NVIDIA in Size

Nvidia has been known for its powerful graphics processing units (GPUs). These chips have become central to artificial intelligence. However, the company is now building much more than chips, and this shift is becoming increasingly important.Under CEO Jensen Huang, Nvidia has expanded into networking, infrastructure and full-stack AI systems that power modern data centres.<h2>Nvidia’s second-biggest business: Networking</h2>Nvidia’s networking division has quietly grown into one of its largest revenue drivers.According to the company’s latest earnings:$11 billion revenue in a single quarter267 per cent year-on-year growthOver $31 billion annual revenueThis makes networking Nvidia’s second-largest segment after compute. Analysts say this growth is directly linked to rising demand for AI infrastructure.Kevin Cook, a strategist at Zacks Investment Research, noted that Nvidia’s quarterly networking revenue is now comparable to what some traditional networking companies generate in a full year.<h2>What exactly is Nvidia building?</h2>Nvidia’s networking business focuses on connecting thousands of GPUs inside data centres.Key technologies include:NVLink: connects GPUs within serversInfiniBand switches: enable high-speed data transferSpectrum-X: Ethernet platform designed for AI workloadsPhotonics switches: improve speed and energy efficiencyThese tools ensure that AI systems can process massive amounts of data quickly and efficiently.Instead of working as separate parts, these technologies are designed to function together as a single system.<h2>The idea of an ‘AI factory’</h2>Nvidia describes modern data centres as “AI factories”. These are facilities designed to train and run AI models at scale.In this setup:GPUs act as the computing engineNetworking acts as the backboneStorage and software complete the systemNvidia’s strategy is to provide all these components as an integrated package.This approach allows companies to build large-scale AI systems more efficiently.Mellanox acquisition: The turning pointNvidia’s expansion into networking began with its acquisition of Mellanox in 2020 for $7 billion. Mellanox, an Israeli company, specialised in high-performance networking.At the time, the move did not attract much attention. However, it has since become a key part of Nvidia’s growth.Industry experts say the acquisition helped Nvidia turn its GPUs into a complete solution by adding the missing networking layer.<h2>Full-stack strategy: Why it matters</h2>Unlike companies that sell individual components, Nvidia is focusing on a full-stack approach.This means it offers:Hardware (GPUs and networking)Software toolsIntegrated systemsThe company also works through partners to deploy these systems globally.According to Nvidia executives, this integrated model gives the company an advantage, as AI workloads require tight coordination between compute and networking.<h2>New announcements at GTC</h2>At its recent GTC conference, Nvidia announced several updates to strengthen its AI infrastructure:New Rubin platform for AI supercomputingImproved Spectrum-X networking systemsInference memory storage solutionsThese developments aim to make AI systems faster and more efficient.Why this matters for the AI raceThe global AI race is no longer just about building better models. It is also about building the infrastructure that powers them.<h2>AI models require:</h2>Massive computing powerHigh-speed data transferEfficient system integrationNvidia’s networking business addresses these needs.Experts say the company’s success lies in understanding that networking is not just a support function it is central to how AI systems operate.<h2>The bigger picture</h2>Nvidia’s shift shows how the AI industry is evolving. Companies are moving from standalone tools to complete ecosystems. While GPUs remain critical, networking and infrastructure are becoming equally important. As demand for AI continues to grow, the ability to build and manage large-scale systems may define the next phase of the industry. Nvidia’s strategy suggests that the future of computing is not just about chips it is about how everything connects.

NVIDIA is evolving beyond GPUs into a full-stack AI infrastructure company, with its networking business emerging as a major growth driver. The division generated $11 billion in quarterly revenue and is now Nvidia’s second-largest segment. 

Nvidia has been known for its powerful graphics processing units (GPUs). These chips have become central to artificial intelligence. However, the company is now building much more than chips, and this shift is becoming increasingly important. Under CEO Jensen Huang, Nvidia has expanded into networking, infrastructure and full-stack AI systems that power modern data centres. Nvidia’s second-biggest business: Networking Nvidia’s networking division has quietly grown into one of its largest revenue drivers. According to the company’s latest earnings: $11 billion revenue in a single quarter 267 per cent year-on-year growth Over $31 billion annual revenue This makes networking Nvidia’s second-largest segment after compute. Analysts say this growth is directly linked to rising demand for AI infrastructure. Kevin Cook, a strategist at Zacks Investment Research, noted that Nvidia’s quarterly networking revenue is now comparable to what some traditional networking companies generate in a full year. What exactly is Nvidia building? Nvidia’s networking business focuses on connecting thousands of GPUs inside data centres. Key technologies include: NVLink: connects GPUs within servers InfiniBand switches: enable high-speed data transfer Spectrum-X: Ethernet platform designed for AI workloads Photonics switches: improve speed and energy efficiency These tools ensure that AI systems can process massive amounts of data quickly and efficiently. Instead of working as separate parts, these technologies are designed to function together as a single system. The idea of an ‘AI factory’ Nvidia describes modern data centres as “AI factories”. These are facilities designed to train and run AI models at scale. In this setup: GPUs act as the computing engine Networking acts as the backbone Storage and software complete the system Nvidia’s strategy is to provide all these components as an integrated package. This approach allows companies to build large-scale AI systems more efficiently. Mellanox acquisition: The turning point Nvidia’s expansion into networking began with its acquisition of Mellanox in 2020 for $7 billion. Mellanox, an Israeli company, specialised in high-performance networking. At the time, the move did not attract much attention. However, it has since become a key part of Nvidia’s growth. Industry experts say the acquisition helped Nvidia turn its GPUs into a complete solution by adding the missing networking layer. Full-stack strategy: Why it matters Unlike companies that sell individual components, Nvidia is focusing on a full-stack approach. This means it offers: Hardware (GPUs and networking) Software tools Integrated systems The company also works through partners to deploy these systems globally. According to Nvidia executives, this integrated model gives the company an advantage, as AI workloads require tight coordination between compute and networking. New announcements at GTC At its recent GTC conference, Nvidia announced several updates to strengthen its AI infrastructure: New Rubin platform for AI supercomputing Improved Spectrum-X networking systems Inference memory storage solutions These developments aim to make AI systems faster and more efficient. Why this matters for the AI race The global AI race is no longer just about building better models. It is also about building the infrastructure that powers them. AI models require: Massive computing power High-speed data transfer Efficient system integration Nvidia’s networking business addresses these needs. Experts say the company’s success lies in understanding that networking is not just a support function it is central to how AI systems operate. The bigger picture Nvidia’s shift shows how the AI industry is evolving. Companies are moving from standalone tools to complete ecosystems. While GPUs remain critical, networking and infrastructure are becoming equally important. As demand for AI continues to grow, the ability to build and manage large-scale systems may define the next phase of the industry. Nvidia’s strategy suggests that the future of computing is not just about chips it is about how everything connects.

NVIDIA is evolving beyond GPUs into a full-stack AI infrastructure company, with its networking business emerging as a major growth driver. The division generated $11 billion in quarterly revenue and is now Nvidia’s second-largest segment.&nbsp;

What is Nvidia building beyond chips, and why does it matter now?

Wall street is buzzing after tech giant Nvidia reported record-breaking quarterly results, fueled by surging demand for its artificial intelligence chips. The Santa Clara-based company has once again proven to be the backbone of the AI boom.


Nvidia Stuns Wall Street With AI Boom

Nvidia, the Company at the Centre of the Global Ai Boom, is Heading Into Earnings Trading at What Many Consider Unusually Low Valuations. The Stock is Priced at Under 24 Times Forward Earnings, Close to Its Lowest Price-to-earnings Multiple in Five Years and Well Below Its Five-year Average.


Why is Nvidia Looking ‘Cheap’? 

Nvidia Chief Executive Officer Jensen Huang will not attend the upcoming India AI Impact Summit next week, the company has confirmed. Huang was expected to be one of the most prominent speakers at the event, which is set to be inaugurated by Prime Minister Narendra Modi.In a brief statement issued on Saturday, Nvidia said Huang would not be travelling to India due to “unforeseen circumstances”.<h2>Why Jensen Huang is not attending the summit</h2>Huang was scheduled to travel to New Delhi and address the media ahead of the summit. However, Nvidia said the visit has been cancelled at short notice.“Due to unforeseen circumstances, Jensen Huang is unable to travel to India at this time,” the company said in an email statement. Nvidia did not provide further details on the reason behind the decision.The development comes just days before the start of the India AI Impact Summit, where senior leaders from technology, government and industry are expected to discuss artificial intelligence policy, infrastructure and innovation.<h2>Nvidia’s presence at the India AI Impact Summit</h2>While Huang will be absent, Nvidia said it remains fully committed to the summit and India’s growing AI ecosystem. The company confirmed that a senior delegation will attend the event.According to Nvidia, Executive Vice President Jay Puri will lead the delegation in India. The team will engage with Indian researchers, startups, developers and partners working on AI infrastructure and applications.The summit is expected to bring together global AI companies and policymakers, with a focus on how India can scale its role in the global artificial intelligence race.Huang’s planned appearance had drawn attention because of Nvidia’s central role in the global AI boom. The company’s chips are widely used to train and run advanced AI models, making Nvidia a key player in discussions around AI infrastructure and computing power.&nbsp;

Due to unforeseen circumstances, Nvidia CEO Jensen Huang has cancelled his India visit ahead of the India AI Impact Summit. NVIDIA says it remains committed, with EVP Jay Puri leading a senior delegation instead.


Nvidia Chief Executive Officer Jensen Huang will not attend the upcoming India AI Impact Summit next week, the company has confirmed. Huang was expected to be one of the most prominent speakers at the event, which is set to be inaugurated by Prime Minister Narendra Modi. In a brief statement issued on Saturday, Nvidia said Huang would not be travelling to India due to “unforeseen circumstances”. Why Jensen Huang is not attending the summit Huang was scheduled to travel to New Delhi and address the media ahead of the summit. However, Nvidia said the visit has been cancelled at short notice. “Due to unforeseen circumstances, Jensen Huang is unable to travel to India at this time,” the company said in an email statement. Nvidia did not provide further details on the reason behind the decision. The development comes just days before the start of the India AI Impact Summit, where senior leaders from technology, government and industry are expected to discuss artificial intelligence policy, infrastructure and innovation. Nvidia’s presence at the India AI Impact Summit While Huang will be absent, Nvidia said it remains fully committed to the summit and India’s growing AI ecosystem. The company confirmed that a senior delegation will attend the event. According to Nvidia, Executive Vice President Jay Puri will lead the delegation in India. The team will engage with Indian researchers, startups, developers and partners working on AI infrastructure and applications. The summit is expected to bring together global AI companies and policymakers, with a focus on how India can scale its role in the global artificial intelligence race. Huang’s planned appearance had drawn attention because of Nvidia’s central role in the global AI boom. The company’s chips are widely used to train and run advanced AI models, making Nvidia a key player in discussions around AI infrastructure and computing power.

Due to unforeseen circumstances, Nvidia CEO Jensen Huang has cancelled his India visit ahead of the India AI Impact Summit. NVIDIA says it remains committed, with EVP Jay Puri leading a senior delegation instead.

Nvidia CEO Jensen Huang will not attend India AI Summit next week

NVIDIA's blockbuster $100 billion investment plan in OpenAI has reportedly stalled amid internal doubts at the chip giant, raising questions about their high-stakes AI partnership.


NVIDIA's Investment in OpenAI Halted: Report

In a Reflection of How the Parent Company of Google Has Become One of the Most Significant Winners of Artificial Intelligence,
Alphabet Has Surpassed Apple to Become the Second Most Valuable Firm by Market Value.

Alphabet Becomes World's Second-Largest Firm

NVIDIA H200: Chinese tech giants ByteDance and Alibaba have approached NVIDIA to inquire about the supply of its advanced H200 AI chips, highlighting the intense global demand for high-performance computing hardware. The H200, designed for cutting-edge artificial intelligence applications, is in high demand as companies race to build and upgrade their AI infrastructure. 

NVIDIA H200: Alibaba, ByteDance Seek Supply Details 

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