The Mamba Selective State Space Model — A Story

Title: Traveling Through the Maze

Imagine you are traveling through a vast maze — each spot in this maze is a mamba, a state in the model.

Each step you take is guided by a special logic — a system that decides where to go next, how to remember the past, and what to output from your journey.

Let’s meet the key parts of this system:

B: The Input Gatekeeper The input affects the current state and helps decide the next step. It interprets new information to guide where the journey in the maze should go next.

A: The Memory Tuner This is how the model remembers or forgets — it tunes the internal memory. It helps update your position in the maze based on what you've seen so far.

h: The Hidden State The hidden state carries the essence of the journey so far, a compressed summary of your entire path through the maze.

c: The Transformer This part transforms the hidden state into an output — a signal, a word, a prediction — depending on the purpose of your journey.

D: The Decoder Finally, D helps convert the internal representation into a meaningful final output, the result of your passage through the maze.

Summary

Each step in the Mamba maze isn't just about where you are — it's about how you use the past, how you process the present, and how you generate the future.

The Mamba architecture is like a well-planned expedition:

• Input (B) decides where to go
• Memory update (A) decides what to keep or forget
• Hidden state (h) tracks where you've been
• Output transform (c) explains what you're seeing
• Decoder (D) delivers the final message.