In a recent installment of the Joe Rogan podcast, Jensen Huang, the CEO of NVIDIA, delved into the pivotal moments that shaped the dawn of deep learning and the trajectory of his company's growth. He highlighted that the watershed moment in deep learning's evolution in 2012 was propelled by an SLI dual-GPU setup, featuring two GTX 580 graphics cards—hardware not originally engineered for AI applications. Back then, the AlexNet model, crafted by a team led by Geoffrey Hinton from the University of Toronto and trained on these two graphics cards, dramatically enhanced image recognition accuracy in the ImageNet competition, sparking the AI revolution. This seminal breakthrough opened NVIDIA's eyes to the immense potential of GPUs in the AI landscape, spurred the widespread adoption of the CUDA platform, and ultimately cemented NVIDIA's position as the frontrunner in the AI chip market.