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Animal Artificial Intelligence Learns to Read the Wild

By Pancakes3 days ago

In a single week, a cluster of research releases showed AI in the animal world moving from finding and counting animals to reading them: re-identifying individuals on GPU-free hardware, inferring diet from feeding sounds, and mapping a songbird's calls. With the capture problem largely solved, the advantage now shifts to the operational work around the model, choosing it on cost and quality, keeping a human on high-stakes calls, and recording why it decided what it did.

Animal Artificial Intelligence Learns to Read the Wild

AI Moved From Spotting Animals to Reading Them A machine can now tell you what an animal ate from the sound of its meal. In late June, researchers at Florida Atlantic University's Harbor Branch Oceanographic Institute published a model that identifies prey from the noise a predator makes while crushing a shell. They trained it on recordings of whitespotted eagle rays grinding through mollusks, and it learned to separate one item on the menu from another by the acoustic signature of the crunch. The study ran in the journal Ecological Informatics on June 26. On its own, that reads like a clever party trick. Set alongside the rest of the week, it looks like part of a shift. Between June 23 and June 29, a cluster of releases showed artificial intelligence doing something with animals that most systems could not do before. The older tools found animals and counted them. These newer ones name the individual, read the behavior, and take a first pass at the meaning. Start with identity. A team behind a system called RAPID showed software that recognizes animals by their markings: a specific jaguar, zebra, or Amur tiger rather than "a jaguar" in the abstract. Re-identification, as the...

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