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SEOUL · DAILY · ISSUE No.340 WE TRIED IT · THE PICK · BEHIND IT 2026.10.13 · TUE
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GADGET BEHIND IT · 5 MIN READ

구글 머신러닝, 뉴질랜드 조류 보전에 활용

JD 젤리비 편집국 · 2026.01.07 SHARE · COPY LINK

무슨 발표인가

  • 3년 수집한 수만 건 조류음향 데이터 자동 분류
  • 뉴질랜드 질랜디아 조류 보호구역 내 위협종 추적
  • TensorFlow로 종·개체수·이동 패턴 파악

뉴질랜드

원문 (영어)

Editor’s note: TensorFlow , our open source machine learning library, is just that—open to anyone. Companies, nonprofits, researchers and developers have used TensorFlow in some pretty cool ways, and we’re sharing those stories here on Keyword. Here’s one of them.

Victor Anton captured tens of thousands of birdsong recordings, collected over a three-year period. But he had no way to figure out which birdsong belonged to what bird. The recordings, taken at 50 locations around a bird sanctuary in New Zealand known as “ Zealandia, ” were part of an effort to better understand the movement and numbers of threatened species including the Hihi, Tīeke and Kākāriki.

Because researchers didn’t have reliable information about where the birds were and how they moved about, it was difficult to make good decisions about where to target conservation efforts on the ground. { "play_video": "Play video", "pause_video": "Pause video" } { "play_video": "Play video", "pause_video": "Pause video", "mute": "Click to mute audio", "unmute": "Click to unmute audio", "enable_cc": "Enable Closed captions", "disable_cc": "Disable Closed captions", "disable_ad": "Disable audio description", "enable_ad": "Enable audio description", "video_progress": "Video progress", "aria_value_text": "elapsed time: [[elapsedTime]], total time: [[totalTime]]" } Endangered species include the Kākāriki, Hihi, and Tīekei.

That’s where the recordings come in. Yet the amount of audio data was overwhelming. So Victor—a Ph.D. student at Victoria University of Wellington, New Zealand—and his team turned to technology. “We knew we had lots of incredibly valuable data tied up in the recordings, but we simply didn’t have the manpower or a viable solution that would help us unlock this,” Victor tells us.

원문: Google Blog (Technology/AI) — "Machine learning gives environmentalists something to tweet about" (2026-01-07) 공식 원문: https://blog.google/innovation-and-ai/technology/ai/machine-learning-gives-environmentalists-something-tweet-about/

#Google Blog (Technology/AI)
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구글 머신러닝, 뉴질랜드 조류 보전에 활용

젤리비 편집국·2026.01.07·5 MIN
IN THIS PIECE
무슨 발표인가 원문 (영어)

무슨 발표인가

  • 3년 수집한 수만 건 조류음향 데이터 자동 분류
  • 뉴질랜드 질랜디아 조류 보호구역 내 위협종 추적
  • TensorFlow로 종·개체수·이동 패턴 파악

뉴질랜드

원문 (영어)

Editor’s note: TensorFlow , our open source machine learning library, is just that—open to anyone. Companies, nonprofits, researchers and developers have used TensorFlow in some pretty cool ways, and we’re sharing those stories here on Keyword. Here’s one of them.

Victor Anton captured tens of thousands of birdsong recordings, collected over a three-year period. But he had no way to figure out which birdsong belonged to what bird. The recordings, taken at 50 locations around a bird sanctuary in New Zealand known as “ Zealandia, ” were part of an effort to better understand the movement and numbers of threatened species including the Hihi, Tīeke and Kākāriki.

Because researchers didn’t have reliable information about where the birds were and how they moved about, it was difficult to make good decisions about where to target conservation efforts on the ground. { "play_video": "Play video", "pause_video": "Pause video" } { "play_video": "Play video", "pause_video": "Pause video", "mute": "Click to mute audio", "unmute": "Click to unmute audio", "enable_cc": "Enable Closed captions", "disable_cc": "Disable Closed captions", "disable_ad": "Disable audio description", "enable_ad": "Enable audio description", "video_progress": "Video progress", "aria_value_text": "elapsed time: [[elapsedTime]], total time: [[totalTime]]" } Endangered species include the Kākāriki, Hihi, and Tīekei.

That’s where the recordings come in. Yet the amount of audio data was overwhelming. So Victor—a Ph.D. student at Victoria University of Wellington, New Zealand—and his team turned to technology. “We knew we had lots of incredibly valuable data tied up in the recordings, but we simply didn’t have the manpower or a viable solution that would help us unlock this,” Victor tells us.

원문: Google Blog (Technology/AI) — "Machine learning gives environmentalists something to tweet about" (2026-01-07) 공식 원문: https://blog.google/innovation-and-ai/technology/ai/machine-learning-gives-environmentalists-something-tweet-about/

#Google Blog (Technology/AI)
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