- A pre-print on biorxiv describes “De novo design of modular peptide binding proteins by superhelical matching,” a computational method for creating custom peptide-binding proteins that could enable new biosensors or targeted therapeutics.  
- Another pre-print introduces iterative ultrastructure expansion microscopy (iU-ExM), a nanoscopy technique that physically enlarges tissue samples to resolve organelle-scale details with conventional light microscopes.  
- Rumors from Silicon Valley, summarized in a Substack post, claim that GPT-4 will arrive within months and represent as large an improvement over GPT-3 as GPT-3 was over GPT-2, prompting discussion about societal readiness for such an inflection point.  
- The Allen Institute announced a global collaboration to produce a whole-brain cell-type atlas of the human brain, aiming to map every neuron and glial cell as a foundation for neuroscience and brain-computer-interface research.  
- A Cerebras white-paper was circulated showing that the CS-2 wafer-scale engine delivers 62.5 PFLOPS of AI performance—orders of magnitude beyond the human brain’s raw throughput—leading participants to argue that algorithmic efficiency, not hardware, is now the main bottleneck.  
- Conversation turned to selective breeding of dogs for enhanced intelligence as an alternative path to aligned, friendly “AI,” with the suggestion that existing smart breeds could be leveraged without many generations of breeding.  
- Links shared for background reading included Matthew Yglesias’s “One Billion Americans,” James C. Scott’s “The Art of Not Being Governed,” and a rationalist review of the Superman deconstruction novella “The Metropolitan Man.”