A new study led by researchers from Tel Aviv University highlights a key challenge in using artificial intelligence (AI) to understand animal communication. Published in the journal Current Biology, the study shows that AI models tend to focus on the physical properties of sounds—like pitch and volume—rather than the meanings that animals assign to those sounds. The research team, which included scientists from several institutions in Israel, the UK, and Germany, found that sounds that are similar in structure do not always have the same meaning, while sounds that seem different might actually convey the same message to the animal hearing them. To explore this issue, the researchers used recordings of vocalizations from human toddlers who had not yet developed full speech. These sounds were recorded in three specific situations: when the child was distressed, calling for a parent, or requesting food. The recordings were analyzed using both traditional acoustic methods and two advanced AI systems: one trained on animal sounds and another trained on adult human speech. The AI models were asked to group the toddler sounds based on their characteristics. The results showed that even the most advanced AI models performed better than traditional methods, but they still struggled to classify the toddler vocalizations by their intended meaning. Sometimes, the models grouped together sounds that meant different things, and other times, they separated sounds that were meant to convey the same message. The AI also failed to recognize when a sequence of sounds showed increasing urgency, something that humans can naturally detect with their ears. The researchers suggest that to accurately decode animal communication, AI must be combined with other methods such as observing animal behavior, conducting playback experiments, and measuring brain activity. Each species has its own unique way of perceiving and responding to sounds, so understanding what animals are "saying" involves more than just analyzing the sound itself—it also requires understanding how the animal hears and reacts to it. Yossi Yovel, one of the researchers, emphasized that identifying patterns in sounds does not automatically mean understanding their meaning. To truly decipher animal communication, a combination of AI, behavioral studies, and neuroscience research will be necessary.