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🧠 LSTM Memory Cell Gate Lab

Interactive 3D LSTM cell where a stream of tokens flows down a glowing conveyor belt through forget, input, and output gates that open and close shows how the network learns what to remember, discard, and reveal across long sequences.

Machine Learning & Neural Networks3DModerate60 FPS

The simulation shows a sequence of tokens moving along a glowing cell-state conveyor belt through forget, input, and output gates whose opening and closing is driven by a simple reactive function, visually mirroring how an LSTM decides what to discard, write, and expose at each timestep.

🔬 What It Demonstrates

🎮 How to Use

Pick a sequence type from the dropdown, use the speed slider to control how fast timesteps advance, and watch the stats panel report each gate's open/closed state; press Rebuild for a fresh random run or Pause to freeze the animation at any step.

💡 Did You Know?

The 'Long Dependency' sequence mode reproduces the classic LSTM party trick: a strong signal injected near the start of the sequence stays visibly bright on the belt and is successfully carried all the way to a distant recall step, something a plain RNN's decaying gradients would make almost impossible to learn.

⚙ Under the hood

Interactive 3D LSTM cell visualization showing forget, input and output gates and a memory belt evolving through time steps of a sequence.

lstmrecurrent-neural-networkmemory-cellgatesmachine-learningdeep-learning

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install