Megabyte
lastmod 2023-05-30created 2023-05-262 edits
Meta unveils Megabyte, an innovative AI model architecture
Features
- Goes beyond the transformer architecture used by models like GTP-4, scaling to more efficient/parallel processing
- Transformers suit short sequences, but are hard to scale to long inputs of over 1 million tokens, such as high-resolution images, podcasts, code, and books
- Megabyte is a multi-scale decoder architecture that can model sequences of over 1 million
- Splits input and output sequences into "Patches" rather than individual tokens
- A local AI model generates output for each patch, and a global model manages and coordinates these patches
Meta AI's Megabyte explained
A translation of the Megabyte explainer written by ENCORD, a startup building AI infrastructure / tools
- Introduces the main components of MegaByte
- Patch Embedder: embeds the input and splits it into patches
- Global Module: an autoregressive transformer that performs self-attention
- Local Module: predicts the next patch from the input received from the global model
- Self-attention with computational cost reduced to O(N^(4/3))
- Feedforward layers applied per patch
- Parallel processing during decoding
- SAM: https://news.hada.io/topic?id=8893
- MTIA: https://news.hada.io/topic?id=9246
- DINOv2: https://news.hada.io/topic?id=9269
- ImageBIND: https://news.hada.io/topic?id=9156
- (Not in the article, but) MMS: https://news.hada.io/topic?id=9245
- (Also not in the article, but) LIMA: https://news.hada.io/topic?id=9239