How can we prevent AI models from cannibalizing themselves when human-generated data runs out? Scientists say they've found the answer.

A digital brain dissolving into different kinds of pixels with flowers in them.

While the evolution of artificial intelligence (AI) systems has shown no sign of slowing, there's a growing concern that large language models (LLMs) will soon run out of human-made data to ingest and learn from.

Once this happens, scientists say, AI models will increasingly rely on synthetic AI-made information, which will lead to an effect called "model collapse." This is where LLMs spout gibberish and the AI systems they underpin deliver inaccurate answers and hallucinate information to queries far more commonly than they do today.