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Today, CUDA is one of the most important elements of NVIDIA's success in the world of AI, but few remember how risky that decision was at the beginning. The company bet everything on the development of technology that yielded no profits for years. Costs rose, margins fell, and the future was uncertain. Nonetheless, NVIDIA did not back down from the project and consistently developed its approach to GPU as a computing platform. It is now clear that this was one of the most significant moves in the industry's history.
CUDA could have sunk the company
NVIDIA introduced CUDA in 2006 as a way to extend the capabilities of graphics cards beyond gaming. The problem was that it was a decision that significantly increased costs, with no guarantee of return. As Jensen Huang admitted, the company increased expenses by as much as 50%, and its market value dropped to around $1.5 billion. At that moment, it was a move balancing on the edge of survival.
The goal was to transform graphics cards into tools for general-purpose computing. With technologies like programmable shaders and support for FP32 computations, GPUs began to be used in entirely new areas. This opened the door for scientists and engineers who started using GPUs for tasks that required enormous computing power. GeForce cards played a key role, reaching millions of users. It was these cards that made CUDA start to spread and build an ecosystem. As Jensen Huang emphasizes, it was GeForce that “built the house” on which all of NVIDIA stands today.
The Effects Came Only After Years
What’s interesting is that CUDA only started to bring real benefits after about 10 years since its introduction. This shows the long-term strategy the company adopted. Today, CUDA is one of the main reasons NVIDIA dominates the AI and high-performance computing market. The story of CUDA is an example of a decision that could have ended in disaster, but ultimately changed the entire industry. NVIDIA transformed from a company mainly associated with gaming to a leader in the world of artificial intelligence.
source: wccftech.com
