This tutorial demonstrates how to quickly develop an automated system to detect the sounds of a species of interest using only a handful of short clips exemplifying the species. For this tutorial we will build a detector for an endangered bird called the Araripe Manakin.
Elephants are being killed at such an alarming rate in some countries, they could go extinct in fewer than 10 years… One team of scientists is trying something different. If they can’t see them, why not listen for them?
Acoustic monitoring combined with powerful machine learning is giving researchers new insights into the elusive Ashy Storm-Petrel. It’s just one way that artificial intelligence can tackle pressing conservation challenges.
Artificial intelligence is helping Cornell’s Elephant Listening Project learn critical information about forest elephants faster, to better protect the endangered animals from poachers and other threats.
We speak with Matthew McKown, CEO of Conservation Metrics, about how deep learning techniques helped rediscover a bird that was once thought extinct, and how GPU-powered AI now helps biologists crunch vast quantities of data to spot trends that would have been impossible to detect before.
Traveling to remote islands. Scrambling across cliffs to track their quarry. Installing acoustic sensors to detect its every move. Ornithologists — scientists who study birds — often have a little James Bond in them.
“Ethical Machines is a series of conversations about humans, machines, and ethics. It aims at sparking a deeper, better‐informed debate about the implications of intelligent systems for society and individuals.”
We present a strategic vision for how data-driven approaches to conservation can drive iterative improvements through better information and outcomes-based funding mechanisms, ultimately enabling increasing returns on biodiversity investments.