Mamba

Processing sequences poses a unique machine learning challenge. To effectively model behavior over time, systems must selectively propagate relevant information while filtering noise. The dominant Transformer technique has achieved state-of-the-art results using self-attention and feed-forward layers. But real-world sequences strain its computational limits. Mamba – an advanced state-space model (SSM) built for sequence efficiency. Mamba … Read more