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Tools for tracking and visualizing the evolution of internal memory states within neural networks during data processing.
Distinct from Prediction Evolution Analysis: Distinct from system memory analysis or prediction evolution; focuses on the internal latent state of neural memory architectures.
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This project is a collection of deep learning research implementations and a reproduction kit designed to translate theoretical AI papers into working code. It provides a library of neural network architectures and reference implementations for reproducing seminal research concepts through interactive notebooks. The repository distinguishes itself through the implementation of AI theory and scaling laws, covering complexity dynamics, information theory, and the simulation of universal AI agents. It also includes a benchmarking suite for synthetic reasoning, allowing for the evaluation of mode
The project tracks and visualize how internal memory states change as a model processes data.