TinyGPT Visualizer: Tools for Exploring the Souls of Large Language Models

A new open-source tool called TinyGPT Visualizer has been released to make mechanistic interpretability—the study of what happens inside large language models—accessible to a broader audience. The project, created by developer oshea00 and hosted on GitHub, provides a visual "X-ray" of a small but real GPT model, letting users inspect the numeric matrices and internal computations that produce its outputs. Anthropic has even convened religious scholars and philosophers to debate whether its Claude models have souls, underscoring the open questions the field is probing. The tool matters because it lowers the barrier to entry for studying how models form outputs, potentially widening the pool of contributors to safety-adjacent research. What to watch next is whether such accessible visualization tools draw more researchers and funding into interpretability at a time when the field remains small relative to the scale of model development.