  Resistive Silicon Detectors (RSD, also known as AC-LGAD) are innovative
silicon sensors, based on the LGAD technology, characterized by a continuous
gain layer that spreads across the whole sensor active area. RSDs are very
promising tracking detectors, thanks to the combination of the built-in signal
sharing with the internal charge multiplication, which allows large signals to
be seen over multiple read-out channels. This work presents the first
experimental results obtained from a 3$\times$4 array with 200~\mum~pitch,
coming from the RSD2 production manufactured by FBK, read out with a 16-ch
digitizer. A machine learning model has been trained, with experimental data
taken with a precise TCT laser setup, and then used to predict the laser shot
positions, finding a spatial resolution of $\sim$~5.5~\mum.
