12 Most Widely Held Stocks by Individuals in 2025

4. NVIDIA Corporation (NASDAQ:NVDA)

Number of Hedge Fund Holders: 223

NVIDIA Corporation (NASDAQ:NVDA) is a leading semiconductor company specializing in GPUs, AI, and high-performance computing. Its GeForce GPUs dominate the gaming market, while NVIDIA RTX technology powers real-time ray tracing and AI-driven graphics. In data centers, NVDA’s AI and deep learning processors, including the H100 and A100 GPUs, are widely used in cloud computing, AI training, and scientific computing. The company also develops autonomous driving solutions and provides Arm-based processors for edge computing and robotics.

NVIDIA Corporation (NASDAQ:NVDA) announced that its latest generation GPU, Blackwell, is now in full production, driven by soaring demand as AI computing requirements reach a critical inflection point. The company highlighted that AI computation needs have expanded nearly 100-fold beyond previous expectations, fueled by advancements in agentic AI and reasoning capabilities. To address this surge, NVDA introduced the Blackwell NVLink 72 system powered by the Dynamo operating system, which delivers a 40x improvement in AI factory performance over the previous Hopper generation. The company also outlined a strategic focus on three AI infrastructure pillars: cloud infrastructure, enterprise computing, and robotics infrastructure.

In networking, NVIDIA Corporation (NASDAQ:NVDA) unveiled its first co-packaged silicon photonic system, achieving 1.6 terabit-per-second performance, a breakthrough designed to scale AI infrastructure to millions of GPUs. The company also provided a detailed product roadmap, introducing upcoming architectures such as Vera Rubin and Rubin Ultra, with the latter projected to deliver 15 exaflops of performance and 4,600 terabytes per second of scale-up bandwidth. NVDA emphasized its vision of transforming traditional data centers into AI-driven compute factories, forecasting that data center build-out could approach $1 trillion as the industry shifts from general-purpose computing to machine learning software optimized for GPUs and accelerators.