In cutting-edge AI developments, UCLA engineers introduced a wearable noninvasive brain-computer interface co-pilot system that deciphers user intent, advancing neurotechnology applications. Additionally, Mount Sinai researchers unveiled a graph neural network AI to personalize anticoagulation therapy in atrial fibrillation, while new deep learning frameworks enhanced pulmonary nodule classification and mammography imaging with CNNs and Vision Transformers. AI tools also emerged for prediction of compound bioactivity and antimicrobial peptide design from venom proteins, marking a significant integration of AI in diagnostics, treatment, and drug discovery.