Local Maze Solving with Gradient Descent Using Candle and WASM
By
yberreby
Hand-rolled, kettle-boiled, baked to perfection. Worth every minute at the bakery.
Summary
The article demonstrates a demo that uses gradient descent to solve a discrete maze without involving a neural network. The optimization process runs locally on a device using candle and Rust's WebAssembly support, allowing offline use. Users can experiment with hyperparameters to observe their impact on the maze-solving process.
Key quotes
· 4 pulledThis demo uses gradient descent to solve a discrete maze.
No neural network involved: logits are directly optimized, from a random initialization, for each maze.
This runs entirely on your local device, thanks to candle and Rust's support for WebAssembly.
Appearances can be deceiving: On harder and larger grids, you might find that much time is spent being 'stuck'.
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