LLMs will transform medicine, media and more

The AI that is hogging so much of the world’s attention now—and sucking up huge amounts of computing power and electricity—is based on a technique called deep learning. In deep learning linear algebra (specifically, matrix multiplications) and statistics are used to extract, and thus learn, patterns from large datasets during the training process. Large language models (LLMs) like Google’s Gemini or OpenAI’s GPT have been trained on troves of text, images and video and have developed many abilities, including “emergent” ones they were not explicitly trained for (with promising implications, but also worrying ones). More specialised, domain-specific versions of such models now exist for images, music, robotics, genomics, medicine, climate, weather, software-coding and more.