  The ability to perform nanometer-scale optical imaging and spectroscopy is
key to deciphering the low-energy effects in quantum materials, as well as
vibrational fingerprints in planetary and extraterrestrial particles, catalytic
substances, and aqueous biological samples. The scattering-type scanning
near-field optical microscopy (s-SNOM) technique has recently spread to many
research fields and enabled notable discoveries. In this brief perspective, we
show that the s-SNOM, together with scanning probe research in general, can
benefit in many ways from artificial intelligence (AI) and machine learning
(ML) algorithms. We show that, with the help of AI- and ML-enhanced data
acquisition and analysis, scanning probe optical nanoscopy is poised to become
more efficient, accurate, and intelligent.
