A recently released paper by CEO Dr. @bengoertzel introduces the concept of fluid-dynamics-based neural networks and discusses their vital role in the journey toward AGI.
The core philosophy of this research is to manage attention, activation, or any cognitive resource as a conserved density that is carried by an incompressible velocity field. An Incompressible-Fluid Network departs from conventional methods like scattering credit through isotropic diffusion or guiding it with unconstrained attention weights. Instead, this unique network directs a set fixed budget along goal-shaped streamlines.
To build upon these early findings, the study also outlines a strategic roadmap for creating advanced AGI systems. This comprehensive plan involves merging neural and symbolic memory architectures while implementing transweave transfer, cognitive Reynolds-number control, and fluid attention.
The core philosophy of this research is to manage attention, activation, or any cognitive resource as a conserved density that is carried by an incompressible velocity field. An Incompressible-Fluid Network departs from conventional methods like scattering credit through isotropic diffusion or guiding it with unconstrained attention weights. Instead, this unique network directs a set fixed budget along goal-shaped streamlines.
To build upon these early findings, the study also outlines a strategic roadmap for creating advanced AGI systems. This comprehensive plan involves merging neural and symbolic memory architectures while implementing transweave transfer, cognitive Reynolds-number control, and fluid attention.