- A request for presentation material on “links between neuroscience and AI” prompted a debate over whether meaningful parallels exist; contributors listed candidate topics including spiking-neuron function, dopaminergic temporal-difference learning, attention mechanisms, biologically plausible back-propagation variants, and Jeff Hawkins’ Thousand Brains Theory.

- maaku argued that contemporary ANNs are only “armchair” abstractions of 1950s-era neuron cartoons, emphasizing that real brains do not perform back-propagation, real neurons exhibit far richer internal structure, and the term “neural network” is an unfortunate historical misnomer.

- The analogy between bird wings and airplane wings was used to illustrate that superficial functional similarity does not imply shared mechanism; discussion noted that birds generate lift via dynamic vortex pumping during flapping, whereas fixed-wing aircraft rely on steady-state aerodynamics.

- fenn countered that convergence on similar high-level solutions (e.g., both birds and aircraft exploit vortices) suggests that studying artificial systems can still inform biological understanding, even when low-level mechanisms differ.

- Recommended resources included the Frontiers in Computational Neuroscience paper “Toward an Integration of Deep Learning and Neuroscience,” Jakob Hohwy’s Bayesian-brain work on autism and volatility, and an InfoQ talk titled “Models of Cognition & Brain.”