GPU vs CPU in AI: Which is Better?

What are the main differences between GPUs and CPUs in AI applications?

GPUs are designed for parallel processing, making them ideal for handling multiple tasks simultaneously, while CPUs are optimized for sequential processing and general-purpose tasks.

Why are GPUs preferred for training deep learning models?

GPUs can perform thousands of calculations at once, significantly speeding up the training process for deep learning models compared to CPUs.

Are there any scenarios where a CPU would be better than a GPU?

Yes, for tasks that require complex logic or are not parallelizable, such as certain types of data preprocessing or running simple algorithms, CPUs can be more efficient.

How do I choose between a GPU and a CPU for my AI project?

Consider the nature of your tasks: if they involve heavy parallel computations like training neural networks, go for a GPU; for general tasks, a CPU may suffice.