When a neural network trained on new data suddenly loses its ability to perform well on previously learned tasks.
When a neural network trained on new data suddenly loses its ability to perform well on previously learned tasks. It's a major challenge for continual learning — the model overwrites old knowledge with new patterns. Various techniques like elastic weight consolidation try to mitigate this.
The process of taking a pre-trained model and continuing to train it on a smaller, specific dataset to adapt it for a particular task or domain.
Using knowledge learned from one task to improve performance on a different but related task.
A mathematical function applied to a neuron's output that introduces non-linearity into the network.
An optimization algorithm that combines the best parts of two other methods — AdaGrad and RMSProp.
Artificial General Intelligence.
The research field focused on making sure AI systems do what humans actually want them to do.
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