Jensen Huang

Money Moves

Leading Nvidia's ecosystem investment strategy

Since May 2025, Nvidia has committed more than $40 billion to companies building AI infrastructure, a total dominated by a $30 billion stake in OpenAI confirmed in February 2026. May brought two more deals: $3.2 billion for glass and fiber maker Corning, and $2.1 billion for data center operator IREN.

Updated Jul 2

New Capabilities

Faces a major customer building an alternative

Every time you ask ChatGPT a question, OpenAI rents the chips that answer it, mostly from Nvidia. On June 24, OpenAI and Broadcom unveiled Jalapeño, OpenAI's first chip of its own, built to do that work for roughly half the cost.

Updated Jun 25

New Capabilities

Largest buyer of high-bandwidth memory for AI accelerators

Modern AI chips can crunch numbers faster than memory can feed them data. On June 18, 2026, SK hynix said it shipped samples of HBM4E, a stacked memory chip built to narrow that gap, to major customers.

Updated Jun 18

New Capabilities

Unveiled RTX Spark Superchip at Computex 2026; confirmed three-generation roadmap to 2030

On June 1 in Taipei, Nvidia CEO Jensen Huang unveiled what the company is calling the RTX Spark Superchip, a 20-core Arm processor co-designed with MediaTek carrying a Blackwell GPU with 6,144 CUDA cores. Microsoft confirmed Windows on Arm support the same morning. ASUS, Dell, HP, Lenovo, Microsoft Surface, and MSI committed to shipping RTX Spark laptops this fall, with Acer and GIGABYTE announced as follow-on brands.

Updated Jun 16

Money Moves

Guided Q2 to $91 billion after Q1 beat; projects combined Blackwell and Rubin revenue of $1 trillion across 2026 and 2027

Nvidia reported Q1 fiscal-2027 revenue of $81.6 billion on May 20, beating Wall Street's $78 billion consensus by $3.6 billion. Data center revenue hit $75 billion, up 92% from a year earlier. The company guided Q2 to $91 billion, above the $85 billion estimate, but the stock closed down 1.8% the next day as analysts said the beat was already priced in.

Updated Jun 3

Money Moves

Shifted from $100 billion deployment deal to $30 billion equity investment in OpenAI

Four months ago, Sam Altman told the world OpenAI had $1.4 trillion in data center commitments. Now the company is telling investors the real number is $600 billion — and that it would rather rent computing power than build its own facilities. The retreat, disclosed to investors in February 2026 and detailed publicly on March 22, marks the sharpest pivot in the short history of the artificial intelligence spending boom.

Updated May 30

New Capabilities

Leading Nvidia's dominance in AI chip market

Every company designing custom artificial intelligence chips today (Apple, Google, Amazon, Microsoft) pays someone else to manufacture them. Tesla just announced it will build and operate its own semiconductor fabrication plant, a $20 billion facility called TeraFab targeting the 2-nanometer process node, the most advanced manufacturing technology in existence. No company without decades of chipmaking experience has ever attempted this.

Updated May 30

New Capabilities

Announced Space-1 platform at GTC 2026

Earth observation satellites generate petabytes of imagery every day, but only about two percent of it ever reaches the ground. The bottleneck is physics: a satellite in low Earth orbit gets maybe ten minutes of ground-station contact per pass, and radio bandwidth cannot keep up with sensor resolution that doubles every few years. Nvidia's answer, announced at its annual developer conference on March 17, 2026, is to stop trying to move the data down and instead move the AI up. The Vera Rubin Space-1 Module packs 25 times the compute power of Nvidia's H100 chip into a radiation-hardened package designed to run large language models and foundation models directly in orbit.

Updated May 30

New Capabilities

Keynote presenter at GTC 2026; positioning Nvidia as the computing backbone of the AV industry

Nvidia and Uber announced plans to deploy 100,000 Level 4 autonomous robotaxis across 28 cities on four continents by 2028, using Nvidia's new DRIVE Hyperion 10 platform and Alpamayo, an open-source reasoning model. Five automakers—BYD, Geely, Stellantis, Lucid, and Mercedes-Benz—will manufacture vehicles with Nvidia's hardware pre-installed. Commercial rides begin in Los Angeles and San Francisco in the first half of 2027.

Updated May 30

New Capabilities

Delivered GTC 2026 keynote, unveiled Vera Rubin and NemoClaw

Nvidia has spent four years on an annual architecture cadence that no semiconductor company has sustained before. At GTC 2026, Jensen Huang unveiled Vera Rubin (a single-GPU system delivering 50 petaflops, five times Blackwell's performance, at one-tenth the cost per token) and NemoClaw, an open-source platform letting companies deploy autonomous AI agents without cloud-provider lock-in.

Updated May 30

Money Moves

Finalized $30 billion equity investment in OpenAI; committed to providing 5GW of Vera Rubin capacity

After the $122 billion round closed in April, OpenAI ended its Azure cloud exclusivity and capped Microsoft's revenue share at $38 billion through 2030. On May 18, a jury dismissed Elon Musk's suit seeking $134 billion and the reversal of OpenAI's for-profit structure.

Updated May 29

Rule Changes

Making Davos debut amid AI governance debates

For 55 years, the World Economic Forum at Davos was neutral ground where adversaries brokered deals. This year, 65 heads of state and nearly 3,000 leaders arrived just 48 hours after Trump announced 10% tariffs on eight European allies. The tariffs escalate to 25% by June unless Denmark agrees to sell Greenland.

Updated May 22

Money Moves

TSMC's largest customer for AI chips

TSMC manufactures over 90% of the world's most advanced chips. On January 15, 2026, TSMC announced it would spend up to $56 billion this year (a 37% increase from 2025) to expand AI processor capacity.

Updated May 21

New Capabilities

Building DOE AI supercomputers

The White House mobilized America's 17 national laboratories and major tech companies—OpenAI, Anthropic, Google, Microsoft, NVIDIA. The Genesis Mission aims to double US research productivity in a decade by connecting supercomputers, quantum systems, and AI into one discovery platform. Energy Secretary Chris Wright announced 24 corporate partners at a January 11 summit.

Updated May 20

Built World

Leading the AI chip revolution powering datacenter expansion

ChatGPT's November 2022 launch triggered the fastest infrastructure buildout in tech history. Hyperscalers are now on track to spend over $1 trillion in 2026, exceeding the GDP of all but 10 countries.

Updated May 19

New Capabilities

Leading company with 90%+ share of AI chip market

Intel just shipped its first client processors built on 18A, the most advanced semiconductor process ever made in America. The Core Ultra Series 3 chips, unveiled January 5 at CES 2026, went on sale globally January 27 with over 200 PC designs, offering 60% faster performance and 27-hour battery life.

Updated May 19

New Capabilities

Leading AI infrastructure consolidation strategy

On Christmas Eve 2025, Nvidia paid $20 billion for Groq's assets—nearly triple the AI chip startup's $6.9 billion valuation from three months earlier. The deal brings Groq's founder Jonathan Ross, who created Google's original Tensor Processing Unit, and his breakthrough inference technology into Nvidia's fold. It's Nvidia's largest acquisition ever, nearly three times bigger than its $7 billion Mellanox purchase.

Updated May 16

Rule Changes

Lobbying beneficiary of the H200 opening; managing supply constraints and political risk

The Trump administration just did the thing Washington has spent years swearing it wouldn't do: let China buy a near-top-tier Nvidia AI chip again. Now a China hawk in Congress is demanding the Commerce Department explain, in detail, why this isn't a strategic own-goal.

Updated May 15

Money Moves

Sits atop the AI chip market every challenger is targeting

Nvidia sells roughly four out of every five chips running today's large AI models. Investors are now writing nine-figure checks on the bet that the workload coming next, running those models rather than training them, will move to different silicon.

Updated May 13