It was 1970 when marine biologist Roger Payne first brought the mesmerizing sound of humpback whales to a wide audience via the celebratedalbum. Back then, the possibility of deciphering those eerie vocalizations seemed a far-out idea plucked straight from science fiction.
Intrigued, Goldwasser asked Gruber to share some recordings with her group and suggested that they could set up a project to understand what those haunting, otherworldly noises actually meant. Although she meant that more as a joke, Gruber thought it was an idea worth exploring. He approached machine learning expert Michael Bronstein, also a Radcliffe fellow, to learn whether artificial intelligence could be used for that purpose.
That was enough for a proof of concept. Using Gero’s dataset, Bronstein tasked an NLP algorithm with detecting whales by their clicks and running it to a sample of recordings. The algorithm correctly identified the specific whales Identifying patterns in whale talk, estimated Andreas, will take “roughly one billion clicks, or 100 to 200 million codas.” Gero’s Dominica Sperm Whale Project database currently contains around 100,000 entries.
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