Since its founding in 1993, NVIDIA Corporation has evolved from developing graphics processing units (GPUs) for gaming into a broad technology company with a diverse product portfolio in parallel computing, AI, and data center technology. NVIDIA has pivoted strongly towards AI, leveraging its GPU technology for deep learning and AI workloads. The company's CUDA programming model and GPUs are widely used in data centers for AI research and cloud computing and by enterprises for AI inference and training tasks.

NVIDIA has expanded its offerings beyond hardware and its proprietary CUDA development environment to include AI with deep learning libraries (like cuDNN), AI software platforms (like NVIDIA AI Enterprise), and 3D collaboration and simulation platforms (like Omniverse). These software offerings enhance the value of NVIDIA hardware by enabling developers to build and deploy applications on the NVIDIA computing platform efficiently.

NVIDIA's go-to-market model reflects its transition from originally focusing on graphics technology to becoming a central player in the broader field of parallel computing and AI. NVIDIA is positioned as a critical enabler of the growing AI market by leveraging its GPU technology across various industry sectors, including edge computing. This broad market approach and an emphasis on software and ecosystem development help explain NVIDIA's growth and influence in the AI technology sector.