AI Self-Evolution: Long-Term Memory Could Unlock Continuous Learning

A new research paper proposes long-term memory (LTM) as a missing layer for AI systems, enabling continuous adaptation during inference without retraining. Unlike static models, LTM organizes past interactions into structured experiences that persist across sessions. Early experiments show memory-enabled frameworks improve performance on complex benchmarks like GAIA.