Especially in proteomics, applications also exist for libraries that contain unidentified MS2 spectra (exclusively or not). Such spectral libraries are sometimes referred to as spectral archives . For spectral archives to be useful, spectra are often grouped by spectral similarity into clusters by some clustering algorithm. It is often, but not always, assumed that spectra in a cluster originate from the same analyte, or from highly related analytes, on account of their spectral similarity. It should also be noted that in recent years, due to the advances in artificial intelligence, it has become possible to predict the characteristic fragmentation patterns of the analytes of interest, for both peptides and small molecules. Such predicted spectra can also be compiled into in silico spectral libraries and utilized in a similar way as traditional spectral libraries built from real data.