Perceiver <2025>

Following the original model, several specialized versions were released:

The Perceiver treats text as a sequence of raw bytes rather than traditional word-level tokens, allowing it to understand the meaning of text directly from its individual characters. perceiver

The is a general-purpose neural network architecture developed by Google DeepMind designed to process a wide variety of data types—including text, images, audio, and video—without needing domain-specific adjustments. : The model uses a small set of

: It makes no prior assumptions about the structure of text, applying the same attention mechanisms it would use for an image or audio file. Following the original model

: The model uses a small set of "latent" variables to attend to the much larger input text. This "cross-attention" step decouples the depth of the network from the size of the input, making it much faster for long documents.