  The use of large arrays might be the solution to the capacity problems in
wireless communications. The signal-to-noise ratio (SNR) grows linearly with
the number of array elements $N$ when using Massive MIMO receivers and
half-duplex relays. Moreover, intelligent reflecting surfaces (IRSs) have
recently attracted attention since these can relay signals to achieve an SNR
that grows as $N^2$, which seems like a major benefit. In this paper, we use a
deterministic propagation model for a planar array of arbitrary size, to
demonstrate that the mentioned SNR behaviors, and associated power scaling
laws, only apply in the far-field. They cannot be used to study the regime
where $N\to\infty$. We derive an exact channel gain expression that captures
three essential near-field behaviors and use it to revisit the power scaling
laws. We derive new finite asymptotic SNR limits but also conclude that these
are unlikely to be approached in practice. We further prove that an IRS-aided
setup cannot achieve a higher SNR than an equal-sized Massive MIMO setup,
despite its faster SNR growth. We quantify analytically how much larger the IRS
must be to achieve the same SNR. Finally, we show that an optimized IRS does
not behave as an "anomalous" mirror but can vastly outperform that benchmark.
