Goodfire releases research series on neural geometry
GoodfireAI launched a research series positing that neural networks process information through complex geometric shapes rather than language. The company argues linking representation geometry to model behavior improves AI understanding, debugging, and control. The series begins with posts and animated visualizations treating internal geometries as primary research objects. Researchers including pseudonymous OpenAI technical staff member Roon amplified the announcement.
Seeing my recently graduated PhD student @MatthewKowal9, now at @GoodfireAI, attached to this exciting line of research brings a tear to my eye.
Keep pushing Matt 💪
Goodfire@GoodfireAINeural networks might speak English, but they think in shapes. Understanding their rich *neural geometry* is key to understanding how they work – and to debugging and controlling them with precision. Starting today, we’re releasing a series of posts on this research agenda. 🧵
#1789Ekdeep Singh Lubana@EKDEEPLOne of the core fundamental research threads we've been pursuing over the last few months at @GoodfireAI is finally out: tightly linking representation geometry and behavior! Hit us up if this spikes your interest!
Goodfire@GoodfireAINeural networks might speak English, but they think in shapes. Understanding their rich *neural geometry* is key to understanding how they work – and to debugging and controlling them with precision. Starting today, we’re releasing a series of posts on this research agenda. 🧵