Onderzoek: hoe AI-agenten context sneller kunnen overdragen

Researchers propose Inductive Latent Context Persistence to reduce computational costs in multi-agent AI systems by transferring compressed hidden states between agents instead of requiring each one to reprocess the same information. This approach, inspired by 6G handover techniques, eliminates redundant tokenization cycles and addresses the cold-start problem when agents transition between tasks.