Lifelong and Meta Learning

Lifelong Learning and Meta-Learning

Lifelong learning allows an AGI system to continually build and update its knowledge base throughout its existence, similar to how humans learn over time. Meta-learning—often described as “learning to learn”—gives the system the ability to refine its own methods of learning by reflecting on past performance. Together, these abilities enable AGI to adjust to changing conditions, preserve valuable information, and improve its capabilities without needing to be retrained from scratch.

These learning mechanisms also support long-term self-improvement. An AGI can recognise areas where its understanding is weak and actively seek new data or strategies to strengthen those gaps. For instance, when encountering an unfamiliar language or cultural setting, it could modify its communication techniques and learning processes to better fit the situation. This not only boosts its overall intelligence but also enhances its situational awareness and social adaptability.