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.
IEEE

Continual Self-Supervised Learning With Masked Autoencoders in Remote Sensing

Abstract: The development of continual learning (CL) methods, which aim to learn new tasks in a sequential manner from the training data acquired continuously, has gained great attention in remote ...

Learning with two teachers

2 In pairs, imagine you are teachers in a co-taught classroom. Create a “dream lesson plan” on a topic of your choice, ...
IEEE

Continual Learning With Neuromorphic Computing: Foundations, Methods, and Emerging Applications

Abstract: The challenging deployment of compute- and memory-intensive methods from Deep Neural Network (DNN)-based Continual Learning (CL), underscores the critical need for a paradigm shift towards ...

5 Types of Learning Content Every Company Should Add to Their Learning Library

According to the McKinsey 2024 report, companies that prioritise learning outperform peers by 2.5x in innovation. By 2023 and beyond, continuous learning has become a strategic advantage, making it ...