He ultimately co-authored a key paper on the bioacoustics of sperm whale vocalizations that was published in Scientific Reports in 2019. Bronstein guided Bermant in choosing the machine learning techniques and approaches that should be applied to the sperm whale bioacoustics data, recalls Gruber (see “Decoding the Deep,” July-August 2024, p. 26). He is first author on the publication “Deep Machine Learning Techniques for the Detection and Classification of Sperm Whale Bioacoustics” which has now been cited 139 times since 2019. Peter's efforts were instrumental in providing proof-of-concept that advanced machine learning could be useful when applied to sperm whale bioacoustics. Project CETI (the Cetacean Translation Initiative) aims to decipher sperm whale vocalizations.