Jensen Huang's 33-year leadership transformed Nvidia from a graphics-chip startup into a global AI powerhouse.
GeForce, CUDA and AI-focused GPUs helped Nvidia expand beyond gaming into data centres and accelerated computing.
Huang's resignation comes amid allegations and an independent investigation, with CFO Colette Kress appointed interim CEO.
Jensen Huang resigned as Nvidia's chief executive on Thursday, drawing fresh attention to the 63-year-old co-founder who led the company from a graphics-chip startup in 1993 to one of the world's most valuable technology firms.
The move came amid reports of alleged extramarital relationships and questions surrounding his links to a businesswoman suspected by US intelligence of having connections to Chinese intelligence.
Nvidia's rise over three decades has been closely tied to Huang's strategy and leadership. The company now supplies processors used in artificial intelligence (AI) models, data centres and high-performance computing systems. Its leadership change therefore comes at a significant moment for the company as demand for AI infrastructure continues to grow, reported Hindustan Times.
Nvidia was founded in 1993 when Huang and two other engineers set out to improve computer graphics for video games and multimedia applications. Over the next 33 years, the company expanded from PC graphics into parallel computing, AI and the infrastructure powering the generative AI boom.
Its evolution involved more than developing faster graphics cards. Nvidia also invested in technologies that enabled its processors to be used for a wider range of computing applications.
Founding And Early Struggles
Nvidia was founded on April 5, 1993, by Jensen Huang, Chris Malachowsky and Curtis Priem.
The three engineers wanted to bring advanced 3D graphics to the gaming and multimedia markets. According to Nvidia's corporate history, they believed specialised graphics processors could make computers more capable of handling complex visual tasks. Huang had previously worked at Advanced Micro Devices and LSI Logic, where he gained experience in the semiconductor industry and chip design.
The company's early years were challenging. Nvidia's first major product, the NV1, failed to establish it as a leading player in the graphics market. Its subsequent NV2 project was cancelled, adding to the company's financial difficulties.
Following the setback, Nvidia secured an investment from Sega and shifted towards graphics technology based on Microsoft's DirectX standards. The move helped the company remain competitive in the PC graphics market.
GeForce And CUDA
A major breakthrough came in 1999, when Nvidia introduced the GeForce 256, which the company described as the world's first GPU.
The graphics processing unit (GPU) was designed to handle complex graphics calculations, allowing the central processing unit (CPU) to focus on other tasks. GeForce subsequently became one of the best-known graphics card brands among gamers and computer enthusiasts.
The introduction of the GPU also laid the foundation for Nvidia's expansion beyond gaming. The company began targeting professional graphics, visual effects, scientific computing and other applications requiring substantial processing power.
Another significant shift came in 2006, when Nvidia introduced CUDA, a parallel computing platform that allowed developers to use its GPUs for general-purpose computing.
GPUs can perform thousands of calculations simultaneously, making them useful for scientific research, simulations and complex mathematical workloads. CUDA helped Nvidia build a software ecosystem around its processors, creating demand beyond the gaming market.
AI Era And Scale
Artificial intelligence transformed Nvidia's business. In 2012, researchers used Nvidia GPUs to train AlexNet, a neural network that delivered a landmark result in image recognition at the ImageNet competition.
Nvidia identifies the AlexNet breakthrough as a catalyst for the modern AI era. Huang subsequently made AI central to the company's strategy, investing in chips, software and computing infrastructure designed for machine learning.
The strategy gained further momentum after ChatGPT was launched in November 2022, bringing generative AI into mainstream focus and driving demand for Nvidia's processors.
The company also expanded the range of products it offered. Instead of supplying individual graphics processors, Nvidia increasingly began offering complete computing platforms comprising AI chips, networking equipment, software and integrated data centre systems.
Its strategy has centred on providing an integrated computing platform rather than competing solely on the performance of individual chips. This has helped Nvidia become a major supplier to technology companies, cloud service providers and AI developers.
Its data centre GPU portfolio includes the Hopper and Blackwell architectures. According to Nvidia's fiscal year 2026 annual report, the company recorded revenue of $215.9 billion, a 65% increase from the previous year. Its Data Center business generated $193.7 billion, while gaming contributed $16 billion.
Data Center accounted for nearly 90% of the company's total revenue. Nvidia's market capitalisation also reached around $4 trillion as it expanded into areas such as healthcare, robotics, autonomous vehicles, scientific research and professional visualisation.
Exit And Succession
Huang's resignation brings his 33-year tenure at the helm of Nvidia to an end. His departure came amid reports of two alleged extramarital relationships and scrutiny over his reported links to a businesswoman suspected by US intelligence of having connections to Chinese intelligence.
Nvidia's board announced an independent investigation into the matter, with a committee of independent directors overseeing the review with assistance from external counsel. The allegations remain subject to investigation, and the company has not announced any findings.
Huang stepped down as chief executive and also resigned from the company's board. Colette Kress, Nvidia's chief financial officer, has been appointed interim CEO while the board considers candidates for a permanent successor.
The leadership transition comes at a time when Nvidia remains a major supplier of the processors and computing infrastructure underpinning the expansion of AI. The company now faces the task of maintaining its technological and business momentum under a new leadership structure.
