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GPU (Graphics Processing Unit)

What is a GPU (Graphics Processing Unit) in AI?

A GPU, or Graphics Processing Unit, is a type of hardware that is designed to handle graphics processing tasks. In the context of AI, GPUs are widely used for training deep learning models, as they can perform many computations simultaneously, making them well-suited for the large-scale computations required in deep learning.

Why are GPUs used in AI?

GPUs are used in AI due to their ability to perform parallel processing. Unlike CPUs, which are designed to perform a few computations at a time, GPUs are designed to perform many computations simultaneously. This makes them ideal for tasks like matrix multiplication and convolution, which are common in deep learning.

Using GPUs can significantly speed up the training of deep learning models, reducing the time and computational resources required.

What are the limitations of GPUs in AI?

While GPUs offer significant advantages for AI, they also have limitations. They can be expensive and consume a lot of power, which can be a barrier for smaller organizations or individuals. They also require specialized programming to use effectively, which can add complexity to the development process.

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