R started as an open-source alternative to a proprietary statistics language, “S,” and it has grown into one of the most important tools in data science. Long before the current AI boom, R became the environment where statisticians, researchers, economists, and data scientists developed many of the methods, workflows, and validation frameworks that modern AI now builds upon. R may not be a household name, but it sits underneath many of the systems and decisions people rely on every day. Today, it's used by researchers, economists, healthcare organizations, and AI developers around the world to analyze data, build models, and make sense of complex information. In many ways, it's become part of the foundation that modern data-driven decision-making, and increasingly AI as we know it, relies on. Read More

by Richard James Market Leader, Asia Pacific Japan Middle East & Africa – Consulting & Engineering Services, DXC Technology 1. AI is moving fast from experimentation to real business impact, how are enterprises adapting to this shift? Enterprises are moving from isolated AI experiments to embedding AI into core operations where it delivers measurable value.... Read More