Goodfire releases Silico tool for mechanistic LLM interpretability
goodfire released silico, a tool for mechanistic interpretability that lets developers map and adjust neurons inside large language models. the startup aims to make ai training less like alchemy and more like traditional engineering by exposing internal parameters.
San Francisco startup Goodfire released Silico, a mechanistic interpretability tool that allows researchers to inspect and modify internal model parameters during training. The tool maps neurons and pathways to help developers debug behaviors and steer outputs, moving AI development closer to traditional software engineering.