Memory Mosaics are networks of associative memories working in concert to achieve a prediction task of interest. Like transformers, memory mosaics possess compositional capabilities and in-context learning capabilities. Unlike transformers, memory mosaics achieve these capabilities in comparatively transparent way ("predictive disentanglement"). We illustrate these capabilities on a toy example and also show that memory mosaics perform as well or better than transformers on medium-scale language modeling tasks.
Memory Mosaics
Memory Mosaics, which are networks of associative memories, achieve prediction tasks with compositional and in-context learning capabilities more transparently than transformers and perform well in language modeling tasks.
- Year
- 2024
- Venue
- arXiv 2024
- Authors
- 5
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- Abstract onlyARXIV-DEFAULT
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- Abstract & full text
- arxiv.org/abs/2405.06394v3ARXIV-DEFAULT
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