NVIDIA started its journey in 1993 intending to produce graphics processing units (GPUs) for gaming and professional applications. Over the years, the company began to establish itself as a chip maker, making them the most prominent in chip designing.
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These days the demand for high-performance computing has skyrocketed to an unexpected level. NVIDIA uses its expertise in GPU technology to expand into parallel processing tasks like AI and data analysis.
The company is also continuously collaborating with tech giants and research organizations to push the boundaries of what the latest chip platforms can do.
From its humble beginnings to being the biggest player in the chip industry, here are some factors in how NVIDIA maintains its prominence:
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Innovative GPUs
NVIDIA's early days earned them a reputation for providing impressive GPUs. These units were primarily designed to render images and graphics efficiently which set them apart in the market.
Decades later, the company is now using advanced architecture and manufacturing processes to deliver higher frame rates, greater visual fidelity, and smoother gaming experience.
The company is also a pioneer in real-time ray tracing technology for its RTX GPUs. NVIDIA's NVLink interconnect technology is also useful for high-speed communication between multiple GPUs in a system.
Direct Focus on Performance, Efficiency
NVIDIA's GPUs are known for offering superior graphics rendering capabilities compared to other chipmakers. These earned them dominance in the market, making them the top choice for gamers, content creators, and professionals who use scientific computing.
The Compute Unified Device Architecture (CUDA) platform was also introduced by the company to allow developers to explore the parallel processing power of GPUs for general-purpose computing tasks. This pushes the boundaries for scientific simulations, data analysis, video processing, and more.
Investment in Research, Development, AI
The chip-making company is consistently investing in research and development which helped the company discover new things about the chip technology. For instance, the company develops tensor cores for GPUs which help accelerate deep learning and AI workloads.
NVIDIA also introduced Deep Learning Super Sampling (DLSS) as a proprietary technology used by AI to upscale lower-resolution images to higher resolutions in real-time. DLSS is utilized to train AI models to deliver sharper visuals. It can also improve performance in games without compromising the graphics quality.
Strategic Partnerships
The company continues its powerhouse status by forging strategic partnerships with other industry players in various fields. NVIDIA is known for its close ties with big tech companies like Meta, Microsoft, Google, and more. AI companies such as OpenAI also rely on NVIDIA's chips.
Diversification
NVIDIA does not close its doors on partnering with tech companies only. Although GPUs are mainly useful to certain industries, NVIDIA manages to diversify its offerings by producing products that could be used in the automotive industry, data centers, edge computing, and AI.
In addition, the company is also banking collaborations with the healthcare system by bringing AI to surgeries. Johnson & Johnson has recently started its partnership with NVIDIA to help them develop AI models that could be of help in the operating rooms.
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