One often overlooked chapter in the dramatic rise of Nvidia Corporation (NVDA) is cash flow and what Jensen Huang's company is doing with it. In fiscal 2023 (ending February 2023), Nvidia recorded only $3.8 billion in free cash flow. But as its graphics processing units became must-have chips for companies that were starting to build out artificial intelligence infrastructure, Nvidia's profits and cash flow exploded upward.
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According to Macrotrends, the following chart represents NVDA's FCF movements: Now the largest publicly traded company in the world by market capitalization, Nvidia is looking for smart ways to spend that cash pile. For instance, it has committed at least $6.5 billion in companies developing photonics technology, including $2 billion each for Lumintum (LITE), Coherent Corporation (COHR), and Marvell Technology (MRVL), and $500 million for Corning (GLW). Also, it reportedly plans to invest up to $3 billion in privately held Lancium, which is an energy/data center infrastructure company backed by Blackstone (BX) that is seeking to go public as early as next year.
Nvidia is making an initial $2 billion investment in exchange for a 20% stake, and then could add another $1 billion if the company meets specific targets. Lancium notably owns the 1.2-gigawatt Lancium Clean Campus in Abilene, Texas, which is the site of the $500 billion public-private Stargate project that seeks to build next-generation AI infrastructure and a network of advanced data centers. Considering the massive demand for AI computing capacity and data centers, Nvidia's $3 billion investment could reap huge rewards for investors – both in chip sales and Lancium's overall growth, as Nvidia would have a 20% stake in the energy/data center infrastructure company.
Let's take a closer look at Nvidia, which is reporting its fiscal 2027 second quarter earnings on Aug. 26. Nvidia has arguably been the biggest winner in the race to build out AI infrastructure. The company has amassed a $5.4 trillion valuation, built largely on the GPUs that are bundled by the hundreds to supply the computing power needed to do high-level calculations.
Nvidia's GPUs have made generative AI, machine learning, and agentic AI possible. Its next-generation architecture, Vera Rubin, uses NVLink chip-to-chip interconnects to allow GPUs and central processing units (CPUs) to share memory space and work more efficiently. Shares are up 24.1% in the last year, topping the S&P 500 Index's ($SPX) 20.1% gain.
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