Today, the rewards of AI are mostly enjoyed by a few countries in what the Oxford Internet Institute dubs the "Compute North." These countries, such as the US, the U.K., France, Canada, and China, have dominated research and development, and built state of the art AI infrastructure capable of training foundational models. This should come as no surprise, as these countries are home to many of the world's top universities and large tech corporations. But this concentration of innovation comes at a cost for the billions of people who live outside these dominant countries and have different cultural backgrounds. Large language models (LLMs) are illustrative of this disparity.

Using AI and ML to Diagnose and Treat Rare Diseases There are two major initiatives which currently play a significant role in addressing rare disease challenges, and each relies heavily on AI technologies. Research-Focused Initiative The first is a research-centered initiative started by the NIH, called Rare Diseases Clinical Research Network (RDCRN). With the aim to advance medical research on rare diseases, it provides support for clinical studies and facilitates collaboration, study enrollment, and data sharing. It is designed to promote highly collaborative, multisite, patient-centric, translational and clinical research. Through this network, scientists from various disciplines at multiple clinical sites from all over the world can work with patients and advocacy groups to study over 280 rare diseases.

Additionally, like in so many industries, investments in artificial intelligence, blockchain, machine learning and the Internet of Things are also driving …