This research uses natural language processing techniques to uncover evolutionary relationships between ancient proteins. By analyzing contextual patterns among amino acids, the new computational tool can identify connections between proteins that diverged billions of years ago, helping scientists reconstruct the history of early microbial life and Earth’s biological evolution.

Generative AI chatbots are predictive systems that generate human-like responses without true understanding. Using large datasets, they model word relationships similarly to weather forecasting. While effective, they can produce convincing inaccuracies, or “hallucinations.” This research emphasizes interpreting AI realistically—as probabilistic tools with limitations—rather than attributing human cognition to them.

This research addresses the exclusion of minority and low-resource languages from modern language technologies. Using linked data principles, it builds interconnected, machine-readable linguistic resources for languages like Cree, Welsh, and Kurdish. The goal is to enable inclusive AI systems and future technologies that support global communication across diverse linguistic communities.