Deep learning
Neural networks with many successive layers and training methods tuned to stacked representations (often rebranded circa 2006–2012 revival).
Deep learning usually means networks with multiple hidden layers, or very wide modern Transformers, to learn hierarchical feature representations from raw-ish inputs such as pixels, waveforms, and tokens.
Breakthrough eras include CNNs on perception and attention-based Transformers, including LLMs and other systems built on neural networks, pretrained on enormous corpora.