- 3D Systems has acquired Volumetric Biotechnologies; the company’s bioprinting platform couples a galvo-driven DLP projector to raster light across non-planar build surfaces, enabling complex, curved tissue scaffolds.  
- Participants debated whether a stack of ~10 wafer-scale chips purpose-built for ultra-sparse spiking neural networks (SNNs)—each paired with hundreds of terabytes of NAND flash—could deliver human-brain-scale emulation while dissipating only a few watts per wafer thanks to <1 % firing sparsity.  
- Storage, not raw compute, was identified as the primary bottleneck for whole-brain SNN simulations; the group speculated that we may already be in a “compute-overhead” regime.  
- Training strategies for large-scale SNNs were contrasted: unsupervised, local-learning rules such as STDP and reward-modulated Hebbian plasticity (mirroring biology) versus supervised conversion of conventional ANNs into SNNs, the latter being less energy-efficient.  
- Avalanche transistors were floated as candidate ultra-fast, low-power devices for hardware SNNs, though most discussion assumed digital simulation rather than custom analog circuits.  
- A detailed side-thread explored clay mineralogy: phyllosilicate sheets arise from hydrated aluminum-silicate lattices (kaolinite 1:1 Al:Si, montmorillonite 1:2 with Mg substitution) produced by low-temperature chemical weathering of feldspars, yielding high-aspect-ratio platelets that sinter into strong ceramics once hydroxyls are driven off.