Mamba: Linear-Time Sequence Modeling with Selective State Spaces
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Mamba: Linear-Time Sequence Modeling with Selective State Spaces
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About this listen
In this episode of AI Papers Explained, we explore Mamba: Linear-Time Sequence Modeling with Selective State Spaces, a 2023 paper by Albert Gu and Tri Dao that rethinks how AI handles long sequences.Unlike Transformers, which compare every token to every other, Mamba processes information linearly and selectively, remembering only what matters.
This marks a shift toward faster, more efficient architectures, a possible glimpse into the post-Transformer era.
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