A research team led by Professor Choi Moon-jung at KAIST's Graduate School of Science and Technology Policy quantitatively analyzed that the responses of the generative artificial intelligence model “ChatGPT-4o” embed subtle age stereotypes toward older adults, with findings published in the February 2026 special issue of *The Gerontologist*. The team collected 900 texts using neutral prompts asking the model to describe characteristics of age groups in 10-year intervals from 10 to 90 years old, applying the Stereotype Content Model to analyze “warmth” and “competence.” For groups aged 60 and older, warmth scores were high while competence tended to be lower than for younger groups, and expressions related to assertiveness decreased with age. Separately, a UNIST research team led by Professor Yoon Seonghwan identified why multimodal AI learns more accurately and stably than single-modal AI, with results to be presented at the International Conference on Machine Learning (ICML 2026). The team introduced a “convolutional smoothing effect” and proposed distribution-based multimodal learning (DML), which outperformed conventional fixed-pair learning in image–text retrieval and classification experiments. Additionally, GIST announced on the 28th that it held the “GIST Integration and Innovation Forum” at the GIST Oryong.