• KIC 8462852 (Tabby’s Star) was revisited as a real-world analogue of the fictional “OnOff” star, with participants noting the latest unexplained dimming events and debating whether megastructures are the most probable first signature of an advanced civilization.  
• The group argued that large-scale stellar engineering (Dyson spheres, swarms, or partial occluders) may be far more detectable at interstellar distances than incidental radio leakage, shifting the prior probability of first contact scenarios.  
• A darker counter-argument emerged: truly advanced civilizations might intentionally cloak their works or even destroy uniquely informative stars to slow the physics progress of emerging species, making the absence of obvious artifacts itself a potential signal.  
• Offense/defense asymmetry for Dyson-scale infrastructure was compared to cybersecurity: a single kinetic-energy projectile can wreck a vast, fragile collector array, suggesting that “defense in depth” is exponentially harder at astronomical scales.  
• Participants suggested searching for low-magnitude brown-dwarf companions around Tabby’s Star as a way to find earlier, smaller-scale examples of astrophysical engineering that might precede full Dyson-level projects.  
• A 50-minute GTC 2015 webinar on GPU-accelerated deep learning with NVIDIA cuDNN was circulated as essential viewing for practitioners scaling neural-network training.  
• A freshly transcribed talk, “Baidu Deep Learning for Speech Recognition,” was added to the diyhpl.us wiki, providing open-source access to production-grade speech-modeling techniques.  
• HDBSCAN (hdbscan.readthedocs.io) was recommended as a high-performance, density-based clustering library for unsupervised learning on large, high-dimensional datasets.  
• Practical tooling trade-offs were discussed: Keras (with Theano or TensorFlow backends) versus compiling Octave with GPU support, with consensus that Theano had matured rapidly since 2015 and now offers competitive performance for rapid prototyping.