Topic: catastrophic forgetting
-
Sakana AI's Evolutionary Algorithm: Build Powerful AI Models Without Costly Retraining
Sakana AI's M2N2 method enables cost-effective AI enhancement by merging multiple pre-trained models into a single, more powerful system without traditional retraining. The technique uses evolutionary principles like dynamic merging, diversity preservation, and attraction heuristics to create opt...
Read More » -
AI That Learns Continuously Without Limits
MIT's SEAL framework enables AI to continuously learn by updating its own parameters and generating synthetic training materials, mimicking human-like learning processes. The approach improves AI performance on tasks like textual analysis and abstract reasoning but faces challenges like catastrop...
Read More » -
MIT's Self-Learning AI Framework Breaks Static Limits
MIT researchers developed SEAL, an AI framework enabling language models to self-teach by generating their own training data and updating instructions, creating a continuous learning loop. SEAL uses a dual-loop reinforcement learning system where the model self-edits its parameters and evaluates ...
Read More »
