Here's another way to see the same lesson. Forget about vectors for a minute and focus on the data that defines the matrix, its entries.
An $n\times n$ matrix has $n^2$ entries. Imagine that you read these entries one at a time, in any order you choose. How many entries will you have to read before you can decide whether the matrix is singular?
The answer depends on the matrix, so let's focus on the best case.
If the first row of the matrix is all zeroes, then the matrix is guaranteed to be singular regardless of the remaining rows. So if you choose to read the $n$ entries in the first row, and you get lucky, and they are indeed all zeroes, then you're done. In this best-case scenario, you proved that the matrix was singular by reading only $n$ entries.
On the other hand, if the matrix is nonsingular, you will have to read most of the entries before you can prove it. For example, you might learn that the matrix is nonsingular by reading all entries above (and including) the main diagonal. That's $(n^2+n)/2$ entries, which is more than half of the whole matrix. And off the top of my head, I don't think you can do any better than that.
If $n$ is one billion, then the difference between $n$ and $(n^2+n)/2$ is staggering. So this is a quantitative sense in which proving that a matrix is singular can be much, much easier than proving that a matrix is nonsingular.