AI and machine learning algorithms are quite skilled at generating works of art -- and highly realistic images of apartments, people, and pets to boot. But relatively few have been tuned to singing synthesis, or the task of cloning the voices of musicians. Researchers from Amazon and Cambridge put their collective minds to the challenge in a recent paper, in which they propose an AI system that requires "considerably" less modeling than previous work of features like vibratos and note durations. It taps a Google-designed algorithm -- WaveNet -- to synthesize the mel-spectrograms, or the representations of the power spectrum of sounds, which another model produces using a combination of speech and signing data. The system comprises three parts, the first of which is a frontend that takes a musical score as input and produces note embeddings (i.e., numerical representations of notes) to be send to an encoder.