The robot accomplishes all this in one place: the simulator. Nvidia's simulation world, Omniverse (the company's virtual environment platform), serves as the environment where robots are "born." It functions as a cognitive kindergarten where humanoid robots learn to walk, operate, understand, react, fall, and rise. Just as an infant develops cumulative motor and cognitive abilities, the robot learns within an artificial world governed by real-world physical laws.

The simulator generates thousands of situational variations: a glass falling at a different angle, a slightly higher step, weak lighting, a person crossing too quickly in the movement path – to teach the robot to react to as many scenarios as possible.

"If we want to build intelligence that understands the physical world and operates within it, we need to teach it in a world similar enough to reality so it can function within it safely, efficiently, and controllably," Rev Lebaredian, Nvidia's vice president of simulation technologies and Omniverse, said in an exclusive conversation with Israel Hayom.

A defining moment in the journey

Lebaredian joined Nvidia in 2002, after working in the film industry. Early in his career, he worked at production houses like Disney and Warner Bros., and later founded a startup developing advanced rendering technologies. In cinema, the rendering process transforms raw graphics into realistic images that appear as if filmed by a camera – a process that was particularly slow and demanding in the early 2000s, sometimes requiring hours of computation for each frame.

As part of his work, he contributed to creating effects in films like "Armageddon," "X-Men," "The Sum of All Fears," and Disney's "Mighty Joe Young," a film nominated for an Oscar for effects thanks to the digital gorilla character at the story's center.

In the early 2000s, Nvidia was primarily a gaming chip manufacturer, far from the AI giant it is today, valued at approximately $5 trillion. Lebaredian joined exactly when Nvidia's flagship product, the graphics processing unit (GPU), began transforming, and he accompanied the company from the crude computer games era of the early 2000s to today's AI revolution, changing the world at rapid speed.

"I joined Nvidia at a defining moment in its journey, precisely when we launched the ability to program shaders (programmable graphics functions) directly on the GPU. This significantly accelerated rendering capabilities, but more importantly, this was the moment the GPU opened for the first time to free programming. I worked then on the first programming language for graphics processors, CG, which became the first brick on the path to CUDA (Nvidia's parallel computing platform), the language dominating parallel computing today," he recounted.

Today, as head of the company's simulation division – Omniverse – Lebaredian is among the handful of senior executives leading simulation and physical intelligence at the company. Nvidia believes this field will drive the next major technological revolution, bringing artificial intelligence into the physical space of daily life. In this revolution, the division Lebaredian heads will have one of the most significant roles.

"Nvidia CEO and founder Jensen Huang said years ago that the most important algorithms will be those understanding the physical world and capable of influencing it," Lebaredian stated.

From language understanding to world understanding

Those algorithms Huang discussed years ago are materializing today in a new field of artificial intelligence: the world model. Just as a language model learns from billions of sentences to predict which word will come next with the highest probability, and thus essentially understand language, meaning, and context – a world model learns to predict what will happen next in the physical world. Namely, how an object will move, how force will affect, what will happen if a door opens too quickly, or where an object placed at this or that angle will roll.

"A world model is the central foundation of the next revolution: physical intelligence, meaning AI that understands not just words, but the universe," Lebaredian explained. According to him, this is a statistical model developing a probabilistic understanding of dynamic reality, not of text. This model will essentially be the robot's "brain," decoding the environment's visual information and knowing how to operate, where to turn to avoid an obstacle, and what force to apply to crack an egg while making an omelet, for example.

But to do this, it needs data of a type that doesn't exist on the internet. Not words, but material, movement, acceleration, friction, light, temperature, interactions, human environments, and physical infrastructures. The training process is fundamentally similar to that of language models – learning from countless examples and situations – except that here the examples must come from the physical world itself.

"The major problem with physical intelligence," Lebaredian explained, "is that we don't have a digital archive of physics. We need to capture it from reality – and that's expensive, dangerous, and limited. The solution is to recreate reality in simulation, and then produce synthetic data from it."

According to Lebaredian, Nvidia's simulation world is not merely a three-dimensional model. It is an engine of natural laws. A city where every lamppost, sidewalk, car, and tree branch is coded to behave as in reality. In this environment, a robot can walk thousands of simulated years in a short time, accumulating experience impossible in the real world.

Releasing the "genie" from the GPU

To understand Nvidia's role in the AI revolution and the magnitude of the mission the company placed on Lebaredian's shoulders, one must return to the story's beginning – and trace the development of one of recent decades' most influential components: the graphics processing unit.

This development did not amount to gradual increases in performance. This is deep evolution, where each new GPU generation changed the computer's very nature. To such an extent that some believe that without Nvidia, not only would a large language model not function at the required speed, but we might not have imagined the very possibility.

Language models, world models, and advanced robotics all feed on enormous parallel computing power, the kind that needed to be born before theoretical thinking about them became possible. Twenty years ago, the GPU was a dedicated graphics unit designed to accelerate computer games. It was designed as a "drawing machine," receiving a series of fixed commands defining how a three-dimensional object should appear on screen. All stages were rigid: how light falls, how reflection forms, whether the material is shiny or matte. The processor could execute these tasks quickly, but nothing existed beyond this.

"In the early 2000s, everything was very simple and limited," Lebaredian recalled. "You couldn't write your own code. Performance was high, but flexibility didn't exist." According to him, the field's first significant revolution occurred when Nvidia opened the shading stage to programming. Instead of built-in models, developers could write their own functions, recreate light and material laws, and build graphic worlds as they imagined them. The change then appeared as a breakthrough for the gaming world alone, but in practice, it freed the GPU from its initial engineering constraints.

The drawing machine became a machine that understood somewhat more about how the world behaves. The hardware ceased being a black box and became an open platform. This was the moment the seed was planted that later became a computing superplatform.

"I've been at Nvidia for 23 years," Lebaredian said, "and almost throughout this entire period, the company has dealt with the question of what else the GPU can be beyond what it was designed for."

"Far beyond what we imagined"

Lebaredian recounted that as shader programs became more flexible, more and more developers identified potential within the GPU far exceeding graphics. Thus, for example, academic researchers began using the graphics processor for physics calculations – they took the same shading function that calculates light and adapted it to compute airflow, water movement, or particle dynamics. The graphics processor's essence as a computer with powerful parallel computing capabilities gradually became clear.

"We saw researchers using it for things completely unrelated to graphics – physical simulations, fluid dynamics, molecules. This was the moment we understood our processors could serve far beyond what we imagined," he stated.

At this stage, Nvidia understood it must change direction and give this computing body a new form. In 2006, CUDA (Nvidia's parallel computing platform) launched, a software environment allowing regular code to run on the GPU. No more disguising scientific problems as graphics, no more manipulating textures or pixels – but a complete computer capable of processing large arrays, running loops, and executing complex algorithms quickly. Historically, this was the turning point at which the GPU ceased to be a graphics accelerator and became a general-purpose computing engine.

The network that learned to "see"

Here arrived another defining moment in the development of artificial intelligence, made possible by Nvidia's programming language. AlexNet – that groundbreaking 2012 neural network learning to identify objects in images with high accuracy like cats, dogs, cars – ran on CUDA. AlexNet marked the beginning of the past decade's computer vision era, with countless applications from smart security cameras to facial recognition systems in smartphones. That same processor, previously drawing shadows, became a machine learning model to identify complex patterns – learning to "see."

Here, it became clear how critical this link was. Those telling AI's history usually emphasize algorithmics but almost always ignore the fact that behind all this stood infrastructure that realized the vision: parallel computation of enormous data quantities at speeds and prices that enabled the very idea of large models.

In a sense, had the GPU not first freed itself from its graphic constraints, we might not have been able to think about a language model as a feasible project. In retrospect, the GPU appears to have undergone the most dramatic transformation chain in computing history: from drawing machine to scientific computer, from graphics accelerator to global AI engine, and from imaging system to virtual reality source, raising the next generation's robots.

Nvidia did not merely improve the GPU. It reinvented it repeatedly until it became the foundation supporting today's entire artificial intelligence revolution – and likely will be tomorrow's as well. "We are only at the beginning of the process of creating foundational world models. No one will 'own' them or be their exclusive owner – this is a project all humanity will need to contribute to," Lebaredian concluded.

The post How Nvidia plans to teach AI to live in the real world appeared first on www.israelhayom.com.

The meeting was organized by Amit Krig, senior vice president and head of Nvidia's development center in Israel. The emotional gathering at the company's US headquarters included the Israeli management team, who were at headquarters for professional meetings.

The post Nvidia founder meets former hostage employee appeared first on www.israelhayom.com.

These processors – ranked second in power within Nvidia's inventory – are critical components for artificial intelligence workloads. However, the president clarified that the agreement does not cover Nvidia's highly desired Blackwell series or the next-generation Rubin units.

"I have informed President Xi, of China, that the United States will allow NVIDIA to ship its H200 products to approved customers in China, and other countries, under conditions that allow for continued strong National Security. President Xi responded positively!" Trump wrote.

Nvidia, currently the most valuable corporation globally, has surged due to booming AI demand, yet this success has positioned it directly within geopolitical tensions over technological supremacy.

Trump's message included the stipulation: "25% will be paid to the United States of America," seemingly indicating the federal government will claim a quarter of the revenue Nvidia secures from these sales, according to CNN.

The announcement follows a meeting between Trump and Nvidia CEO Jensen Huang, amidst the president's repeated assertions that America must secure victory in the global AI race against heavy Chinese investment.

"We applaud President Trump's decision to allow America's chip industry to compete to support high paying jobs and manufacturing in America. Offering H200 to approved commercial customers, vetted by the Department of Commerce, strikes a thoughtful balance that is great for America," an Nvidia representative told CNN. Additionally, Trump revealed that the Commerce Department is finalizing similar protocols for Intel, AMD, and other American manufacturers.

"AMD commends President Trump's leadership in finding a thoughtful approach to export policies that allows for US companies to compete globally," an AMD spokesperson stated. "The president's decision strengthens American competitiveness, supports high-value domestic jobs, and drives American investment and growth in the semiconductor industry."

CNN noted that Intel did not immediately reply to a request for comment. This authorization follows earlier agreements Trump established this year, including a deal for AMD and Nvidia to remit 15% of their China-sales revenue to the US government, while he also stated in August that the state plans to take a 10% equity position in Intel.

The post US to allow Nvidia H200 sales to China under new deal appeared first on www.israelhayom.com.

Like so many stories worth telling these days, Rosenberg's also begins in the early morning hours of that cursed Saturday. "Right after I understood the dimensions of the event, I realized it would also affect our employees," he said. "Nvidia has more than 5,000 employees in Israel, many of whom live and work in the south, and we started trying to find out what was happening with them."

"We were always there with them in the evening, from seven to nine, in sirens and missiles, and all this time we also had to take care of other employees who were affected, evacuated from home, or who lost family members and friends," he said. "It was a difficult and somewhat crazy routine. Nvidia had five employees whose family members were kidnapped to Gaza, and some were murdered there, and we even recruited new employees over time who also have relatives who are hostages. In addition, employees lost brothers and friends in the war, and company employee Amit Chayut fell in battle. We understood that we had to do everything we could to help them. It was clear to me that this was my most important mission and that of the company."

These years have been dramatic not only for Nvidia itself, but for the entire tech world. "I remember the pivotal day when they announced OpenAI's ChatGPT, exactly three years ago," Rosenberg said. "We all at the company understood that something had fallen, that the AI field was really breaking through, as we hoped would happen. This, of course, didn't happen in one day. The company built itself toward this moment. OpenAI worked with Mellanox on the technology back then, and we knew how important our products were for the AI era. It was a gradual rise until explosion – and when it happened, it happened fast and in big leaps, and it was important to preserve the organization's identity."

"Satisfaction is not just good conditions," Rosenberg explained. "Money is, of course, important and critical – salary, stocks, financial horizon – but a leading company needs to create satisfaction and interest and security for employees. From the CEO to the most junior manager, it's clear to everyone that we need to ensure our employees have it good and that they will want to continue working with us – and we invest a lot in this."

"On October 7, I didn't have a 'playbook' that says what to do if a company employee is kidnapped. We didn't know how to deal with something like this, but I hope I did the right things along the way. I also have no idea if anything I did somehow helped bring Avinatan home, but I tried to give his family as much strength as possible, because they were in a very lonely and difficult place."

The post Why Nvidia exec became hostage families' voice appeared first on www.israelhayom.com.

This significant upswing demonstrates a marked shift in attitudes toward Alphabet after the 2022 introduction of ChatGPT led certain investors to worry the firm had lost its AI advantage, despite having invented much of the foundational technology for generative AI. Alphabet recovered its momentum this year by making its cloud division a key contributor to growth, which attracted an investment from Warren Buffett's Berkshire Hathaway, and its new Gemini 3 model is garnering excellent initial reviews.

The milestone, however, could intensify anxieties among some executives who caution that rising valuations have detached market trends from business reality, prompting concerns over an economic bubble reminiscent of the 1990s dot-com era. These bubble fears are also amplified by circular transactions involving OpenAI and Nvidia, two prominent firms in the AI sector. Analysts, nevertheless, maintain that Google is strongly positioned in the AI competition because of its ample cash reserves, its own in-house chip production offering an alternative to Nvidia's expensive processors, and its massive internet search operation, which is already experiencing benefits from AI incorporation.

In October, the moment of truth arrived for the AI tech titans as investors worldwide held their breath after Wall Street's close when Microsoft, Alphabet (Google), and Meta (Facebook) – collectively worth nearly 10 trillion dollars – began releasing their quarterly earnings reports in another attempt to beat forecasts.

Google (through its parent company Alphabet) beat forecasts by 26% ($2.87 per share compared to the $2.27 expected) with revenues of 100 billion dollars. Microsoft also beat forecasts by 14% ($3.72 per share compared to the $3.6 expected). Meta on the other hand had to pay 15 billions in a one-time payment, which resulted in a miss of 84% in the earnings.

Alphabet reported more than $100 Billion of revenue in a quarter for the first time ever. Google parent company Alphabet also reported strong third-quarter results, with revenue climbing 16% year-over-year. Google Search & Other grew 15%, while YouTube Ads increased 15% during the period. Google Cloud posted the strongest growth at 34%, though Google Network saw a 3% decline. The company's EBIT rose 9.5% with a margin of 31%, and earnings per share jumped 35%.

The head of Google's parent firm Alphabet, Sundar Pichai, has recently cautioned the BBC that every company would be impacted if the AI bubble were to burst. Speaking exclusively to BBC News, Pichai acknowledged that while AI investment growth is an "extraordinary moment," there is some "irrationality" in the current boom. Amid fears in Silicon Valley of soaring valuations, Pichai warned, "I think no company is going to be immune, including us."

His wide-ranging interview at Google's California headquarters, reported by the BBC, touched on energy needs, climate targets, UK investment, and AI's effect on jobs, coming as market scrutiny intensifies. Alphabet's shares have doubled in seven months to $3.5 trillion as market confidence in its ability to counter OpenAI grows. A specific focus remains on Alphabet's competition with Nvidia, run by Jensen Huang, which recently hit a $5 trillion valuation, even as analysts question the $1.4 trillion in deals surrounding OpenAI.

Pichai's remarks about "irrationality" echoed Alan Greenspan's 1996 "irrational exuberance" warning during the dotcom boom. Pichai told the BBC the industry can "overshoot" in such cycles. "We can look back at the internet right now. There was clearly a lot of excess investment, but none of us would question whether the internet was profound," he said. "I expect AI to be the same. So I think it's both rational and there are elements of irrationality through a moment like this." His comments follow a similar warning from JP Morgan's Jamie Dimon, who told the BBC some AI investments would "probably be lost." Pichai argued Google's "full stack" model provides a better position to handle turbulence.

The post Alphabet's market cap approaches $4 trillion amid AI rally appeared first on www.israelhayom.com.

NVIDIA just shattered records again. $NVDA reports Q3 Revenue of $57.0 Billion, up 62% year-over-year. • GAAP EPS: $1.30 (+67% YoY) • Net Income: $31.9B The AI boom isn't slowing down—it's accelerating. https://t.co/tskrzW9jNg#NVIDIA $nvda

— Israel Hayom English (@IsraelHayomEng) November 19, 2025

NVIDIA (NASDAQ: NVDA) continued its dominance of the artificial intelligence sector, reporting record-breaking revenue for the third quarter that significantly outperformed Wall Street projections.

The chip giant posted revenue of $57.0 billion, marking a staggering 62% increase compared to the same period last year and comfortably beating the analyst consensus of $55.09 billion.

NVIDIA achieved a gross margin of 73.4% and an operating income of $36.0 billion, translating to an exceptional operating margin of 63.2%. The company's profitability was equally striking, with operating income reaching $36.0 billion, demonstrating exceptional operational efficiency even as it scales. Net income followed suit, jumping 65% year-over-year to nearly $31.9 billion (or $1.30 per share). Looking forward, the company signaled that the AI boom is far from over, issuing guidance for fourth-quarter revenue of approximately $65 billion and noting that demand for its next-generation Blackwell chips is already "off the charts."

"During the first nine months of fiscal 2026, NVIDIA returned $37.0 billion to shareholders in the form of shares repurchased and cash dividends. As of the end of the third quarter, the company had $62.2 billion remaining under its share repurchase authorization," the company said in a statement.

Smashing the projections

NVIDIA didn't just meet expectations; it surpassed them by nearly $2 billion on the top line.

• Revenue Beat: Actual revenue of $57.0 billion vs. Consensus of $55.09 billion (a beat of $1.91 billion).

• EPS Beat: Non-GAAP earnings per diluted share came in at $1.30, beating the consensus estimate of $1.26.

The primary engine for this outperformance was the data center segment, which generated a record $51.2 billion in revenue alone: up 66% from a year ago. This single segment now accounts for the vast majority of the company's total intake.

Guidance blows past estimates

Perhaps more impressive than the current results is NVIDIA's outlook for the future. The company provided fourth-quarter revenue guidance of $65.0 billion (plus or minus 2%).

This forecast stands well above the consensus estimate of $61.84 billion, suggesting a difference of over $3 billion between NVIDIA's internal visibility and Wall Street's models. The company also forecasted strong non-GAAP gross margins of roughly 75.0% for the upcoming quarter.

NVIDIA Q3 Fiscal 2026: Actual vs. Consensus

Note: Q4 Revenue Outlook represents the midpoint of the provided guidance range (+/- 2%).

"Insatiable" Demand for AI

The driving force behind the surge remains the company's next-generation hardware. In the press release, NVIDIA founder and CEO Jensen Huang emphasized that demand is outstripping supply.

"Blackwell sales are off the charts, and cloud GPUs are sold out," Huang stated. "Compute demand keeps accelerating and compounding across training and inference, each growing exponentially."

Huang described the current market environment as a "virtuous cycle of AI," noting that the ecosystem is scaling rapidly across various industries and countries. "AI is going everywhere, doing everything, all at once," he added.

BREAKING: Nvidia $NVDA earnings

EPS $1.3 vs $1.26 expected
Revenue $57 Billion vs $55 billion expected

We are breaking it down LIVE at https://t.co/b1CM1ZxP19 pic.twitter.com/qTZEcDXqSy

— unusual_whales (@unusual_whales) November 19, 2025

The corporation published its third-quarter numbers and future outlook on the investor relations segment of its web portal at 4:20 p.m. ET, about half an hour after Wall Street trading concluded. A subsequent discussion with management began at around 5 p.m. ET via the same platform, arriving as anxiety regarding the immense capital expenditures on artificial intelligence by Silicon Valley giants increases. The stunning beat appeared to soothe the concerns of circular funding between the major AI players, with after hours trading showing green candles for the 5-trillion company. 

Before the smashing earnings report, observers questioned if CEO Jensen Huang would validate the AI revolution's ongoing surge or perhaps warn us that demand for the GPUs (its processing units that allowed fast computations with AI capacities) had plateaued, less than a decade after his company made perhaps the most important decision in its history: buying a small Israeli company named Mellanox, from Yoqne'am.

Gaining essential Ethernet and InfiniBand tools for high-performance AI centers made the 2019 Mellanox deal a pivotal moment. That acquisition rendered the Jewish state and the tech giant "inextricably linked", establishing Israel as the company's second-biggest R&D hub outside America.

Nvidia controls roughly 80% of global AI GPU spending in 2025. Its data center unit generated $41.1 billion in Q2. Reports provide insights into AI adoption and cloud spending. CEO Jensen Huang projects $3-4 trillion in infrastructure spending by 2030. Financial Times noted that the company's performance is a barometer for the sector.

The report was a a beat across the board, and a record, just weeks after the company has recently reached a record market cap of 5 trillion dollars, the first company ever to do so.

Transitioning from a graphics processor manufacturer to an AI infrastructure titan marks the firm's successful metamorphosis, driven by the stagnation of traditional silicon progress known as Moore's Law.

NVIDIA just shattered records again. $NVDA reports Q3 Revenue of $57.0 Billion, up 62% year-over-year. • GAAP EPS: $1.30 (+67% YoY) • Net Income: $31.9B The AI boom isn't slowing down—it's accelerating. https://t.co/tskrzW9jNg#NVIDIA $nvda

— Israel Hayom English (@IsraelHayomEng) November 19, 2025

Recent performance history shows the equity has consistently surpassed Wall Street predictions in its previous three financial summaries, bolstering shareholder belief in operational fulfillment amidst unprecedented requests for AI frameworks. Yet, the last profit victory, the August earnings report for Q2,  failed to calm fears regarding a deceleration after data center revenues of $41.1 billion missed projections marginally, causing a sell-off, even though the revenue fell short only because China was denied access to its chips because of newly imposed US restrictions. The stock subsequently recovered losses to hit fresh peaks. 

The post NVIDIA crushes analyst expectations with $57 billion quarter; guides for massive Q4 appeared first on www.israelhayom.com.

Deployment of the GPUs is expected in phases through 2026. This rollout will occur at IREN's 750MW Childress, Texas campus, alongside new liquid-cooled data centers supporting 200MW of IT load. IREN anticipates funding these capital expenditures through existing cash, customer prepayments, operating cashflows, and other financing initiatives.

"This agreement not only validates IREN's position as a trusted provider of AI Cloud services, but also opens access to a new customer segment among global hyperscalers," Roberts continued, according to GLOBE NEWSWIRE. "It marks another major step forward for IREN as we continue to expand large-scale GPU deployments across our 3GW secured power portfolio in North America, reinforcing our position as a leading AI Cloud Service Provider."

Jonathan Tinter, Microsoft's President of Business Development and Ventures, also provided commentary, GLOBE NEWSWIRE reported. "Together with IREN, Microsoft is delivering cutting-edge AI infrastructure for our customers.

"IREN's expertise in building and operating a fully integrated AI cloud – from data centers to GPU stack – combined with their secured power capacity makes them a strategic partner," Tinter stated, according to GLOBE NEWSWIRE. "This collaboration unlocks new growth opportunities for both companies and the customers we serve," he concluded, as per GLOBE NEWSWIRE.

Meanwhile, Microsoft Corp. said on Monday that it has committed to a substantial $7.9 billion investment in the United Arab Emirates over the next four years, a move set to significantly advance the nation's status as a global technology hub, according to reporting by Bloomberg.

Microsoft stated it intends to expend in excess of $7.9 billion on data centers, cloud-computing, and personnel within the United Arab Emirates during the upcoming four years, Bloomberg reported. This initiative supports the Gulf state's objective of transforming into an international technology center.

The commitment was announced by Microsoft president Brad Smith on Monday in Abu Dhabi, according to Bloomberg. This pledge encompasses intentions to nearly treble the quantity of Nvidia Corp. advanced chips that Microsoft utilizes in the country, importing essential equipment that has faced restrictions from the US government.

"This is not money we're raising here. It's money we're investing and spending here," Smith conveyed to Bloomberg Television during the Adipec oil conference in Abu Dhabi. "We are seeing demand here explode," the Bloomberg Television interview noted.

Access to leading semiconductors in the Gulf state remains a complex issue. Bloomberg reported in October the US approved chip exports to American firms in the UAE following a deal that sparked security concerns, though not yet to Emirati firms like G42. Some US officials have criticized placing critical equipment in the Middle East, fearing the tech could move to China. Microsoft, however, said it received US licenses in September to ship AI chips to the UAE. "They're not just acts of faith," Smith stated, per Bloomberg. "We had to satisfy very strict conditions about the cybersecurity, the physical security, the other security protection of these chips to ensure that they stay under our control."

The company previously deployed 21,500 Nvidia A100-equivalent chips in the UAE and plans to ship 60,400 more, including the GB300, arriving "in months, not years," according to Smith, as cited by Bloomberg. In a separate move reported by Reuters, Microsoft struck a $9.7 billion deal with data-center operator IREN for Nvidia's advanced chips. That agreement, aimed at easing the AI boom's computing crunch, sent IREN shares up over 20%. Dell will provide IREN with $5.8 billion in equipment, including GB300 chips, for Microsoft's use.

The five-year IREN deal highlights the AI industry's need for computing power, Reuters noted, as capacity shortages limit major tech firms. The partnership allows Microsoft to expand capacity without building new data centers or securing power, and it avoids heavy spending on chips that will quickly lose value. IREN, valued at $16.52 billion, operates renewable-energy-powered data centers in North America. IREN said the new processors will be deployed at its Texas campus by 2026, alongside new liquid-cooled data centers. A filing indicated Microsoft's prepayment helps finance IREN's $5.8 billion Dell deal.

Microsoft CFO Amy Hood stated last week that the company's AI capacity crunch is now expected to extend until at least mid-2026, revising an earlier prediction, according to Reuters. Reporting was provided by Deborah Sophia and Aditya Soni in Bengaluru, and the piece was edited by Arun Koyyur for Reuters.

The post Microsoft commits $7.9B to UAE tech hub; $9.7B IREN deal aims to ease AI computing crunch appeared first on www.israelhayom.com.

This marks Nvidia's southernmost location in Israel, complementing the established development centers in Tel Aviv, Ra'anana, Yokneam, Mevo Carmel, and Tel Hai. Alongside the expansion, Nvidia intends to hire hundreds of additional staff in the southern area, including chip developers, hardware and software engineers, architects, students, and advanced degree holders.

The existing teams at the facility and incoming personnel will participate in developing cutting-edge hardware and software for AI networking, including NVIDIA Spectrum-X Ethernet, Quantum-X InfiniBand, NVLink, ConnectX and BlueField DPUs products, along with central processing units for data centers and additional technologies.

Nvidia employs over 5,000 people in Israel. According to the company, since purchasing Mellanox in 2020, Nvidia's Israeli workforce has more than doubled, with the company maintaining expansion through hundreds of available positions nationwide.

"Expanding Nvidia's development center in Beersheba demonstrates our dedication to accessing the finest engineers, regardless of their location," said Amit Krig, senior vice president at Nvidia and director of Nvidia's development center in Israel. "The new facility will function as a professional home for hundreds of additional developers from Beersheba and surrounding communities, who will participate in creating groundbreaking hardware and software technologies and drive global innovation in artificial intelligence."

"Opening Nvidia's new facility and tripling its activities in the city constitutes significant and vital news for Beersheba and the Negev," said Ruvik Danilovich, mayor of Beersheba. "This choice reflects trust in the Beersheba ecosystem, and will generate hundreds of new employment opportunities that will bolster the city's human capital and cement Beersheba's position as a premier innovation hub."

The post Nvidia's massive Israel expansion: New hub to triple size appeared first on www.israelhayom.com.

Taiwan's leading semiconductor manufacturer TSMC reported record-breaking financial performance for the quarter ending September 30, 2025, with consolidated revenues reaching NT$989.92 billion. The company achieved net profits of NT$452.30 billion and diluted earnings per share of NT$17.44, equivalent to US$2.92 per American Depositary Receipt unit.
The chipmaker's third-quarter results demonstrated robust growth momentum, with revenues climbing 30.3% compared to the same period last year. Net income surged even more dramatically, posting a 39.1% year-over-year increase, while diluted earnings per share rose by 39.0%. Sequential quarterly growth also remained strong, showing a 6.0% revenue boost and 13.6% net income improvement over the second quarter of 2025.

When converted to US dollars, TSMC's third-quarter revenues totaled $33.10 billion, marking a substantial 40.8% annual increase and 10.1% quarterly growth. The company maintained impressive profitability metrics, including a gross margin of 59.5%, an operating margin of 50.6%, and a net profit margin of 45.7%. Leading financial publications have verified that these earnings represent TSMC's strongest quarterly profit performance in the company's history.

TSMC faces significant geopolitical threats from mainland China that extend beyond traditional business competition. The constant pressure from China creates strategic vulnerabilities for both TSMC and Taiwan, as the company's dominance in advanced semiconductor manufacturing has become a critical factor in cross-strait tensions. If China were to invade the island, the world would face an immediate supply shock with widespread delays in technology manufacturing, as many tech companies depend on components produced in Taiwan. China's expanding semiconductor capabilities, particularly through companies like SMIC (Semiconductor Manufacturing International Corporation), represent a long-term competitive challenge. SMIC has made significant progress in mature process nodes (28nm and above), with Chinese foundries expected to account for over 25% of global capacity among top mature-node foundries by the end of 2025. While mainland China lags behind in advanced AI chip manufacturing, its push for technological autonomy and domestic substitution – especially in automotive and industrial semiconductors – could gradually erode Taiwan's strategic advantage. The threat is compounded by concerns that TSMC's diversification of operations to locations like Arizona, while mitigating supply chain risks, could diminish Taiwan's "silicon shield" protection by reducing the strategic importance that deters Chinese aggression.​

Strong Demand for advanced technologies

"Our business in the third quarter was supported by strong demand for our leading-edge process technologies," Senior Vice President and Chief Financial Officer Wendell Huang said.

The remaining technology nodes contributed as follows: 16/20-nanometer represented 7% of wafer revenue, 28-nanometer accounted for 7%, 40/45-nanometer contributed 3%, 65-nanometer made up 4%, 90-nanometer was 1%, 0.11/0.13-micrometer represented 1%, 0.15/0.18-micrometer accounted for 3%, and 0.25-micrometer and above contributed less than 1%.​

AI chip demand drives growth

TSMC's record performance reflects surging demand from major AI chip designers, particularly NVIDIA and AMD, who rely heavily on TSMC's advanced manufacturing capabilities for their cutting-edge AI accelerators. NVIDIA is expected to overtake Apple as TSMC's biggest customer in 2025, underscoring the massive shift toward AI infrastructure spending. Both NVIDIA and AMD depend on TSMC's most advanced process nodes – 3nm and below – along with sophisticated packaging technologies like CoWoS (Chip-on-Wafer-on-Substrate) to produce the high-performance chips powering generative AI applications and data centers. AMD has committed to an annual release cadence for its AI accelerators, with future chips expected to utilize TSMC's cutting-edge 2nm technology. The company controls over 70% of the global foundry market and serves as the indispensable manufacturing partner for the AI revolution.​

Revenue from Smartphone increased 19%, IoT increased 20%, and Automotive increased 18% from the second quarter. HPC remained flat, while DCE decreased 20% and Others declined 8% compared to the previous quarter.​

From a geographic perspective, revenue from customers based in North America accounted for 76% of total net revenue in the third quarter. Revenue from Asia Pacific, China, Japan, and EMEA (Europe, Middle East, and Africa) accounted for 9%, 8%, 4%, and 3% of total net revenue respectively.​

TSMC's third-quarter gross margin reached 59.5%, representing a 0.9 percentage point improvement from the previous quarter. This enhancement stemmed mainly from cost reduction initiatives and increased facility utilization rates, though these gains were somewhat diminished by adverse currency fluctuations and dilutive effects from international manufacturing operations.

Operating expenditures rose by NT$3.25 billion to NT$87.76 billion during the quarter, accounting for 8.9% of net revenues versus 9.1% in the prior quarter, reflecting improved operational efficiency. The company's operating margin strengthened by 1.0 percentage point quarter-over-quarter to 50.6%. Research and development investments totaled NT$63.74 billion, while sales, general and administrative costs amounted to NT$24.02 billion.

TSMC's annualized return on equity climbed to 37.8%, marking a 3.0 percentage point sequential increase and a 4.4 percentage point year-over-year improvement.Retry

Financial position and cash flow

TSMC's total current assets grew by NT$171.10 billion from the previous quarter, driven primarily by a NT$116.63 billion expansion in cash and marketable securities holdings. By the conclusion of the third quarter, the company's combined cash and marketable securities reached NT$2,751.06 billion. Meanwhile, total current liabilities contracted by NT$101.40 billion, largely attributed to a NT$111.70 billion reduction in accrued liabilities and other obligations. The semiconductor giant maintained net working capital of NT$2,160.11 billion with a current ratio of 2.7 times during the quarter.

The company's net cash reserves expanded by NT$100.07 billion to reach NT$1,756.61 billion in the third quarter, reflecting the growth in cash and marketable securities positions. Outstanding interest-bearing debt stood at NT$994.45 billion.Retry

"Moving into fourth quarter 2025, we expect our business to be supported by continued strong demand for our leading-edge process technologies," Huang stated.​

Drawing from current market conditions and business projections, TSMC's leadership anticipates fourth-quarter revenues will fall within the US$32.2 billion to US$33.4 billion range. Using an exchange rate projection of 30.6 New Taiwan dollars per US dollar, company executives forecast gross profit margins between 59% and 61%, with operating profit margins expected to span 49% to 51%.

Understanding the results: A simplified explanation

For readers less familiar with financial terminology, here's what these results mean in everyday terms: TSMC operates as a specialized manufacturer – it doesn't design or sell its own chips, but instead produces semiconductors based on designs provided by technology companies around the world. This "pure-play foundry" business model, which TSMC pioneered, means the company focuses exclusively on manufacturing rather than competing with its customers.​

The company's "nanometer" measurements refer to the size of transistors on computer chips – smaller numbers mean more advanced technology that can pack more computing power into the same space. TSMC manufactures about 60% of the world's contracted semiconductor production, making it the dominant player in this specialized manufacturing sector.​

The strong financial results reflect several key trends: High-Performance Computing (which includes data centers and artificial intelligence systems) now represents more than half of TSMC's business, while smartphones contribute about one-third. The company's ability to maintain gross margins near 60% indicates strong pricing power and operational efficiency – for every dollar in sales, TSMC keeps approximately 60 cents after covering direct manufacturing costs.​

TSMC's substantial capital expenditures of nearly $30 billion year-to-date represent ongoing investments in new factories and equipment to maintain its technological leadership and expand production capacity. The company was founded in 1987 in Taiwan and remains headquartered in Hsinchu, with operations expanding globally to serve customers across multiple continents.​​

The post TSMC crushes earnings, but will 'Silicone Shield' last? appeared first on www.israelhayom.com.

The partnership represents one of the largest AI infrastructure investments announced to date, with the first phase targeted to come online in the second half of 2026 using NVIDIA's Vera Rubin platform. The 10-gigawatt deployment will encompass millions of GPUs across AI data centers.

"NVIDIA and OpenAI have pushed each other for a decade, from the first DGX supercomputer to the breakthrough of ChatGPT," said Jensen Huang, founder and CEO of NVIDIA. "This investment and infrastructure partnership mark the next leap forward – deploying 10 gigawatts to power the next era of intelligence."

The announcement comes as competition intensifies in the artificial intelligence sector, with companies racing to secure the massive computing resources needed to train increasingly sophisticated AI models. OpenAI has grown to over 700 million weekly active users.

Sam Altman, cofounder and CEO of OpenAI, emphasized the fundamental importance of computational power in AI development. "Everything starts with compute," Altman said. "Compute infrastructure will be the basis for the economy of the future, and we will utilize what we're building with NVIDIA to both create new AI breakthroughs and empower people and businesses with them at scale."

The partnership builds on a decade-long collaboration between the two companies, dating back to OpenAI's early development phases. Greg Brockman, cofounder and president of OpenAI, highlighted this historical relationship in announcing the expanded partnership.

"We've been working closely with NVIDIA since the early days of OpenAI," Brockman said. "We've utilized their platform to create AI systems that hundreds of millions of people use every day. We're excited to deploy 10 gigawatts of compute with NVIDIA to push back the frontier of intelligence and scale the benefits of this technology to everyone."

Under the agreement, OpenAI will work with NVIDIA as a preferred strategic compute and networking partner for its AI infrastructure expansion plans. The companies will co-optimize their development roadmaps, aligning OpenAI's model and infrastructure software with NVIDIA's hardware and software platforms.

The partnership operates alongside OpenAI's existing collaborations with technology giants including Microsoft, Oracle, SoftBank and Stargate partners, all focused on building advanced AI infrastructure. This multi-partner approach reflects the enormous scale and complexity of modern AI development, which requires coordination across hardware manufacturers, cloud providers, and software developers.

NVIDIA's investment structure will be progressive, with funds deployed as each gigawatt of computing capacity comes online. This phased approach allows both companies to scale the infrastructure incrementally while managing the massive capital requirements involved in such a large-scale deployment.

The 10-gigawatt target represents a substantial increase in AI computing capacity. For context, large data centers typically operate in the range of hundreds of megawatts, making this deployment roughly equivalent to dozens of major facilities dedicated specifically to AI workloads.

Both companies indicated they expect to finalize the detailed terms of this strategic partnership in the coming weeks. The agreement supports OpenAI's stated mission to develop artificial general intelligence that benefits humanity while providing NVIDIA with a major customer for its advanced GPU systems. Immediately following the news, NVIDIA's stock shot up by about 4 percentage points.

The post NVIDIA commits $100 billion investment in OpenAI partnership for massive AI infrastructure expansion appeared first on www.israelhayom.com.