FT.com – The Transformer – This Is How It Works [free link] – By Visual Storytelling Team and Madhumita Murgia in London. “The technology has resulted in a host of cutting-edge AI applications — but its real power lies beyond text generation. Generative AI exists because of the transformer. One of our big goals for AI coverage at the FT has been to do more explanatory journalism, diving deep into the technology that has suddenly exploded into the mainstream. This visual explainer, built together with our brilliant Visual Storytelling team, tries to get to the heart of a large language model – how it works, where it goes wrong and why it’s so powerful. We hope it helps to demystify generative AI for you….Over the past few years, we have taken a gigantic leap forward in our decades-long quest to build intelligent machines: the advent of the large language model, or LLM. This technology, based on research that tries to model the human brain, has led to a new field known as generative AI — software that can create plausible and sophisticated text, images and computer code at a level that mimics human ability. Businesses around the world have begun to experiment with the new technology in the belief it could transform media, finance, law and professional services, as well as public services such as education. The LLM is underpinned by a scientific development known as the transformer model, made by Google researchers in 2017. “While we’ve always understood the breakthrough nature of our transformer work, several years later, we’re energised by its enduring potential across new fields, from healthcare to robotics and security, enhancing human creativity, and more,” says Slav Petrov, a senior researcher at Google, who works on building AI models, including LLMs. LLMs’ touted benefits — the ability to increase productivity by writing and analysing text — are also why it poses a threat to humans. According to Goldman Sachs, it could expose the equivalent of 300mn full-time workers across big economies to automation, leading to widespread unemployment. As the technology is rapidly woven into our lives, understanding how LLMs generate text means understanding why these models are such versatile cognitive engines — and what else they can help create.”