Researchers have found a better way to reduce gender bias in natural language processing models while preserving vital information about the meanings of words, according to a recent study that could be a key step toward addressing the issue of human biases creeping into artificial intelligence.
Large language models (LLMs) that drive generative artificial intelligence apps, such as ChatGPT, have been proliferating at lightning speed and have improved to the point that it is often impossible to distinguish between something written through generative AI and human-composed text. However, these models can also sometimes generate false statements…
Natural language processing models including the wide variety of contemporary large language models (LLMs) have become popular and useful in recent years as their application to a wide variety of problem domains have become increasingly capable, especially those related to text generation.