machine learning - What's the low dimensional? -

My question is less dimensional?

I read many papers related to AI, machine learning.

Some of them mentioned some dimensions, fewer dimensional factors, and so on.

I already knew PCA, SVD, which reduces the high data dimension for low data dimensions.

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In other words, PCA and SVD can choose the most powerful factor.

So, is this the same concept? (The concepts of PCA and SVD are equivalent to a less dimensional factor) Is this correct?)

If you know this, please help me.

There was a question about the difference between PCA and SVD on the math section. You can check it out: