Can We Teach AI to Learn from Mistakes Without Forgetting

Can AI learn without forgetting? Explore five levels of continual learning and the stability-plasticity tradeoff to plan better AI roadmaps.
Nature

Continual Learning and Catastrophic Forgetting in Neural Networks

Continual learning in neural networks addresses the challenge of adapting to new information accumulated over time while retaining previously acquired knowledge. A central obstacle to this process is ...
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Google unveils new AI model HOPE that moves closer to continual learning

Google has announced HOPE, a new AI model that's developed in an effort to help machines learn and adapt over time. The firm describes HOPE as a "self-modifying" system that contains an innovative ...
NextBigFuture

AI Legend Sutton Wrote the Bitter Lesson- Gives His Suggestions for True Continual Learning

Sutton believes Reinforcement Learning is the Path to to Intelligence via Experience. Sutton defines intelligence as the computational part of the ability to achieve goals. It is rooted in a stream of ...
NextBigFuture

Progress to Continual Learning AI

2025 saw a tripling of continual learning LLM papers according to arXiv trends. This is driven by foundation model scale and multimodal extensions. However, no flagship AI released models (GPT-5, Grok ...

The AI challenge in BFSI: Preparing humans to lead alongside machines

Explore how the BFSI sector can prepare its workforce to thrive alongside AI, emphasizing leadership, adaptability, and ...