The age of generative AI is here: only six months after OpenAI‘s ChatGPT burst onto the scene, as many as half the employees of some leading global companies are already using this type of technology in their workflows, and many other companies are rushing to offer new products with generative AI built in. But, as those following the burgeoning industry and its underlying research know, the data used to train the large language models (LLMs) and other transformer models underpinning products such as ChatGPT, Stable Diffusion and Midjourney comes initially from human sources — books, articles, photographs and so on — that were created without the help of artificial intelligence. Now, as more people use AI to produce and publish content, an obvious question arises: What happens as AI-generated content proliferates around the internet, and AI models begin to train on it, instead of on primarily human-generated content? A group of researchers from the UK and Canada have looked into this very problem and recently published a paper on their work in the open access journal arXiv. What they found is worrisome for current generative AI technology and its future: “We find that use of model-generated content in training causes irreversible defects in the resulting models.”
Full story : Researchers warn of ‘model collapse’ as AI trains on AI-generated content.
