"Why GPUs Are the Real Driving Force Behind Artificial Intelligence"

Why Does Artificial Intelligence Rely on Graphics Cards More Than Processors?

In the world of artificial intelligence, models perform massive computational tasks with huge amounts of data, especially during training. This is where graphics cards (GPU) come in, as they can perform thousands of operations at the same time, unlike the central processing unit (CPU), which handles a limited number of tasks.

Key Reasons:

???? Parallel Processing Power: A GPU has thousands of cores, which means it can work on a huge amount of data quickly.

???? Time Efficiency: Training an AI model on a CPU can take days, but with a GPU, it can be done in hours or less.

???? Compatibility with AI Tools: Tools like TensorFlow and PyTorch are optimized for GPUs and support them extensively.

???? Higher Performance for Energy Consumption: A GPU delivers powerful results while consuming less energy.

Conclusion: Without powerful graphics cards, artificial intelligence wouldn’t have reached the level we see today. They provide the power and speed AI needs.