13-11-2023
How AI could break the Language Barrier between Humans and Cetaceans - Artificial Intelligence, Cetacean Communication and Oceanography
In this episode of Ocean Explained, we delve into the fascinating intersection of artificial intelligence (AI) and cetacean communication. Can AI help translate marine life interactions and even predict the evolution of our oceans? Join us as we explore how AI works with scientific data, the potential for communication with whales, and the quantification of carbon cycles in marine organisms. Discover the impact of deep learning in marine conservation and ecology, and learn about the application of AI techniques in analyzing vast amounts of data from marine ecosystems. We discuss the training, evaluation, and application phases of AI strategies, as well as the use of deep learning algorithms for identifying individual animals and analyzing their behavior. Additionally, we highlight a successful study that applies deep machine learning to analyze a large passive acoustic dataset, focusing on the identification of highly variable humpback whale sounds. We also explore various cases where AI is used to study fish vocal communications, detect ghost fishing gear, and understand carbon cycling in marine environments. Don't miss this episode as we uncover the potential of AI to revolutionize marine biology and conservation efforts. Subscribe to our Instagram page at oceanexplained_ for more episodes, trailers, and additional content about the ocean.
Keywords: artificial intelligence, cetacean communication, marine life interactions, evolution of oceans, deep learning, marine conservation, marine ecology, scientific data analysis, individual animal identification, humpback whale sounds, fish vocal communications, ghost fishing gear, carbon cycling, marine biology, marine conservation efforts, Instagram, Ocean Explained
References :
-NOAA ; https://www.ncei.noaa.gov/news/using-ai-listen-and-learn-about-humpback-whales
-Copernicus European Project ; https://marine.copernicus.eu/news/artificial-intelligence-digital-twin-ocean
-ICES Journal of Marine Science, Volume 79, Issue 2, March 2022, Pages 319–336, Morten Goodwin, Kim Tallaksen Halvorsen, Lei Jiao, Kristian Muri Knausgård, Angela Helen Martin, Marta Moyano, Rebekah A Oomen, Jeppe Have Rasmussen, Tonje Knutsen Sørdalen, Susanna Huneide Thorbjørnsen, Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook,