Despite seeing tremendous advances in the recent decade, artificial intelligence is still lacking sorely in basic areas such as generalizability, adaptability, and causality. Today’s AI systems—mostly centered around machine learning and deep learning—are limited to narrow applications, require large amounts of training data or experience, and are very sensitive to changes in their environments.
Thinking fast and slow in AI
Thinking fast and slow in AI
Thinking fast and slow in AI
Despite seeing tremendous advances in the recent decade, artificial intelligence is still lacking sorely in basic areas such as generalizability, adaptability, and causality. Today’s AI systems—mostly centered around machine learning and deep learning—are limited to narrow applications, require large amounts of training data or experience, and are very sensitive to changes in their environments.