Good question. Read on.
Kea, a species of Parrots are native to New Zealand. It is hailed as one of the Smartest Bird on the planet. Hmm. Now you know why? 🙂
The more we read about the bird, the more we liked this name, as we had envisioned our application to be the smartest in answering questions on data. Here are few of aspects of this bird’s intelligence that caught our attention.
The ability to learn a broad skill and then applying it to different situations. Humans are bestowed with this skill.
Kea, the data analyst has similar vision and intent. It can be trained on a wide variety of datasets for it to respond back with answers and more on diverse situations.
Their ability to predict the future based on probabilities based on statistical inference. Reasoning under uncertainty is a central part of human decision making.
For Kea, the application, the intent is to be good at both descriptive as well as uncovering a wide variety of unknown unknowns, answers that are latent.
The birds apparently learn and understand social cues from fellow humans to make decisions that benefit them. What else could be more appropriate to name a solution that is built to mimic social interactions – conversations?
Abstract: One key aspect of domain-general thought is the ability to integrate information across different cognitive domains. Here, we tested whether kea (Nestor notabilis ) can use relative quantities when predicting sampling outcomes, and then integrate both physical information about the presence of a barrier, and social information about the biased sampling of an experimenter, into their predictions. Our results show that kea exhibit three signatures of statistical inference, and therefore can integrate knowledge across different cognitive domains to flexibly adjust their predictions of sampling events. This result provides evidence that true statistical inference is found outside of the great apes, and that aspects of domain general thinking can convergently evolve in brains with a highly different structure from primates. This has important implications not only for our understanding of how intelligence evolves, but also for research focused on how to create artificial domain-general thought processes.