In a recent research paper, OpenAI suggested that the tendency of LLMs to hallucinate stems from the way standard training and evaluation methods reward guessing over acknowledging uncertainty. According to the study, this insight could pave the way for new techniques to reduce hallucinations and build more trustworthy AI systems, but not all agree on what hallucinations are in the first place.

VaultGemma is a 1B-parameter Gemma 2-based LLM that Google trained from scratch using differential privacy (DP) with the aim of preventing the model from memorizing and later regurgitating training data. While still a research model, VaultGemma could enable applications cases in healthcare, finance, legal, and other regulated sectors.

Recent research by Anthropic engineers explores identifiable patterns of activity that seems to give rise to an emerging personality. These traits, known as persona vectors, help explain how a model's personality shifts over its lifecycle and lay the groundwork for better controlling those changes.