Brian Nichols is the co-founder of Angel Squad, a community where you’ll learn how to angel invest and get a chance to invest as little as $1k into Hustle Fund's top performing early-stage startups

Jensen Huang co-founded NVIDIA in 1993 with two engineers and a business plan sketched out at a diner. They were betting that graphics processing units would become the dominant computing hardware of the future, at a time when the entire industry was building around CPUs. That contrarian bet, made before deep learning, before cryptocurrency, before large language models existed, turned out to be one of the most prescient technological wagers in commercial history. In October 2025, NVIDIA became the first company to reach a $5 trillion market capitalization. Jensen Huang investments, deployed primarily through NVIDIA's NVentures corporate venture arm, are built on the same logic that made the original NVIDIA bet work: find the infrastructure layer that everything else will be built on top of, and get there early.

The NVentures Machine

NVIDIA doesn't invest passively. NVentures grew its portfolio from roughly $300 million in early 2023 to over $1.5 billion by late 2024, making more than 20 new investments in a single year. In 2024 alone, NVIDIA participated in approximately 45 AI-related financings. By October 2025, that pace had already surpassed the full-year 2024 total, with over 50 AI-related deals completed. Huang personally approves every NVentures investment, which reflects how central this activity is to NVIDIA's overall strategy.

The portfolio includes foundation model companies Mistral AI, OpenAI, and xAI; cloud infrastructure provider CoreWeave, which IPO'd in March 2025 and delivered significant returns; Hugging Face, the open-source AI model platform; Databricks, which raised at a $62 billion valuation in late 2024; and Runway, the AI video generation company. As of April 2025, NVIDIA's publicly disclosed equity portfolio across six holdings totaled roughly $1.14 billion, led by CoreWeave.

Every investment connects back to the NVIDIA ecosystem: strengthening demand for NVIDIA hardware, building the software stack that runs on NVIDIA chips, or extending AI capabilities into physical domains like robotics where NVIDIA compute will be required. In 2025, NVIDIA made notable robotics investments including Dyna Robotics, a company that saw its valuation jump from $100 million to $600 million within six months of its seed round.

Eric Bahn, Hustle Fund GP, has talked about how the most durable investment theses are the ones that leverage the investor's genuine operating advantage. Huang's operating advantage is unprecedented in technology right now: every AI company in the world needs his hardware, which gives him access and information flow that no traditional venture fund can match.

The Ecosystem Logic

The investment portfolio is a map of where NVIDIA's technology is going. CoreWeave provides GPU cloud infrastructure to companies that can't build their own data centers. Hugging Face is the distribution layer for AI models that run on NVIDIA hardware. Databricks connects data infrastructure to AI applications. Runway pushes the boundary of what AI models can do with video, which requires enormous compute. The companies are different but the thesis is unified: invest in businesses that will drive sustained demand for NVIDIA chips.

The NVIDIA Inception program extends this logic to the pre-institutional stage, and it's a model Angel Squad recognizes well: create value for early-stage companies before asking for anything back, and build loyalty that compounds into deal flow. Over 20,000 startups were enrolled in Inception as of 2024, receiving GPU credits and ecosystem visibility in exchange for building on NVIDIA's platform. This isn't equity investing, but it's ecosystem cultivation that gives NVIDIA early visibility into where AI applications are developing, which directly informs where NVentures deploys capital next.

Shiyan Koh, Hustle Fund managing partner, has pointed to ecosystem-driven investment strategies as increasingly important in sectors where platform dynamics determine winner-take-most outcomes. NVIDIA is executing that strategy more aggressively than any other company in technology today.

What This Means for Early-Stage Investors

Huang's approach contains a direct lesson for investors working at much smaller scales. His edge isn't capital. It's the proprietary signal he gets from running the most critical hardware company in the AI supply chain. Every founder he talks to, every investment he evaluates generates real-time information about where the technology is actually heading rather than where hype says it's going.

For angel investors, the analogy is domain expertise. The investors who consistently find great deals in a sector are the ones who understand it from the inside. At Davos in January 2026, Huang stated that 2025 was the largest year for global venture capital on record, with over $100 billion deployed worldwide, most of it into AI-native startups. He framed these as companies building the application layer above NVIDIA's infrastructure. The investors who understood that infrastructure layer first got into those deals at the right prices.

Angel Squad and the Infrastructure Mindset

Jensen Huang investments teach a specific lesson: back the infrastructure layer, not just the application layer on top of it. Angel Squad helps investors develop that kind of structural thinking about the sectors they know best. With 2,500 members across 50 countries, the community brings together operators-turned-angels who understand their industries at a similarly granular level. Members invest alongside Hustle Fund in early-stage companies and build portfolios informed by real operational insight rather than trend-chasing. If you've been inspired by how Huang thinks about ecosystem leverage and platform risk, hustlefund.vc/squad is where you apply that framework.

The Takeaway

Jensen Huang didn't become one of the most important investors in technology by picking trends. He built the most critical infrastructure in the AI supply chain and then deployed capital to strengthen the ecosystem around it. The lesson for early-stage investors: your best investments will almost always come from areas where you have genuine informational advantages over the market. Build that edge first. Then invest consistently around it.