AI论文研究10/21 17:0054
MIT 科技评论:AI 正在尝试解码动物语言,但双向对话仍停留在理论阶段
原题:Interspecies communication
MIT 科技评论梳理了跨物种交流的现状:过去 50 年,水听器、可穿戴生物记录仪等设备积累了大量动物声音数据;近十年 AI 能识别不同叫声、区分发声个体并发现规律,非营利机构 Earth Species Project 用机器学习识别了渡鸦的叫声归属,并希望用基于人类语音、音乐和动物声音训练的 NatureLM 解读多种物种的发声。但特拉维夫大学神经生态学家 Yossi Yovel 担心模型过度依赖声学相似性而误判,双向对话何时实现尚不明确。
推荐理由想了解 AI 在动物语言解码上真实进展与瓶颈的读者,可快速看清哪些是已验证成果、哪些仍是设想。
Humans are far from the only species with a gift for gab, and our furry, feathered, and finned friends could have a lot to tell us. Decoding how animals communicate with one another could offer a window into the inner lives of other species and help humans realize that “animals are sentient creatures who think, who have hopes and dreams of their own,” says Con Slobodchikoff, the founder of Zoolingua, a company working on dog-to-human speech.
The sticking points
Teasing all this out is complex. To decipher howls, squeaks, and clicks, researchers must match the creatures making sounds with what’s happening around them. Prairie dogs, for example, utter a different series of yips when a coyote approaches than when a hawk is nearby. It’s painstaking work, especially for difficult-to-observe species, like deep-diving whales or subterranean mole rats.
There are other hurdles. Many animals communicate not just through sound but through visual cues, touch, pheromones, or a combination of signals, some of which might be difficult for us to perceive. And without a multispecies Rosetta stone, it’s hard to know if translations are accurate.
The progress
Over the past 50 years, a growing arsenal of devices has made it easier to observe the sophisticated ways animals communicate. Hydrophones at the bottom of the ocean can capture humpback whale song, and tiny wearable “biologgers” can record a bat’s every squeak.
In the last decade, advances in AI have leveled up our ability to make sense of it all. The technology can detect different calls, distinguish which sounds belong to which animal, and spot patterns. Researchers at the Earth Species Project (ESP), a nonprofit founded in 2018 to decode animal communication, recently used machine learning to detect vocalizations of carrion crows and determine which bird made which call.
They suspect that more advanced AI could translate critters’ chatter. Large language models like Claude and ChatGPT excel at finding relationships between words, explains Sara Keen, one of ESP’s behavioral ecologists. ESP hopes its own NatureLM—trained on human speech, music, and animal sounds—will be able to interpret the vocalizations of a variety of species.
That promise, however, is still theoretical. Yossi Yovel, a neuroecologist at Tel Aviv University, worries that these models will put too much emphasis on acoustic similarities and make mistakes—like lumping together similar sounds that have different meanings.
As for a two-way convo? It’s not clear when—or whether—that will happen. Still, “a lot of animals have an evolutionary structure that is similar enough that we should be able to understand what they’re saying,” Slobodchikoff says.
Progress meter ………… 4
Researchers have amassed heaps of data on animal communication, but they’re still trying to figure out how to decipher it all.
本文内容转载自 MIT Technology Review,版权归原作者所有。
阅读原文 ↗ https://www.technologyreview.com/2026/10/21/1146124/interspecies-communication-impossible-issue1 个独立信源
- Interspecies communication
MIT Technology Review · 10/21 17:00 · 已取全文
标题与摘要由 AI(deepseek-chat)改写,可能有误,以原文为准。
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