- A SIGGRAPH 2017 video on “Computational Design of Telescoping Structures” was shared, showcasing algorithmic methods for compact, deployable mechanical forms.  
- Discussion centered on the “random-weights” phenomenon: networks whose convolutional layers are left at their (fixed) random initialization still perform surprisingly well on vision tasks; links to the mileyan/neural-style GitHub branch and the arXiv paper 1606.04801 were provided.  
- Participants debated the trade-off between model accuracy and interpretability, with one member stating they would accept 10× longer training times in exchange for transparent, rule-like models instead of “5 MB blobs of black magic.”  
- A Stanford class report on generating adversarial audio examples for speech-recognition systems was circulated, alongside the open-source “speechless” project from Mozilla’s DeepSpeech community.  
- The newly released STARDATA dataset—millions of StarCraft replays for AI research—was announced, together with its TorchCraft/StarData repository.  
- Links to the classic “Optimal Brain Damage” paper (LeCun et al., 1990) on network pruning and a 500 kB pruned ImageNet model were highlighted as relevant to creating smaller, more analyzable networks.  
- A Lancet article on global disease burden was requested; lacking a local paper-bot, members suggested the Twitter hashtag #icanhazpdf for pay-walled access.  
- Kernel-development workflow insights were excerpted from a blog post: the Linux MAINTAINERS file and get_maintainer.pl script automatically identify reviewers, mailing lists, and code ownership to coordinate large-scale, cross-subsystem patches.