AI in Energy

What if the most efficient AI energy systems aren’t built in data centers—but inspired by spiders? A new study in Nature reveals that spiders sleep in two distinct stages: a light, responsive phase and a deeper, restorative one. This biphasic rhythm—where neural activity resets during quiescence—mirrors how AI models can optimize energy use by alternating between high-load processing and low-power recalibration. The implications for grid management, edge AI, and real-time energy modeling are profound. Nature’s findings suggest that biological systems evolved energy efficiency long before silicon. How can we apply this insight to reduce the carbon footprint of AI-driven energy systems? The answer may lie not in more power—but in smarter cycles of rest. This insight comes from: https://www.nature.com/articles/d41586-026-03487-0 Source: https://www.nature.com/articles/d41586-026-03487-0 View and join any or all of our communities — AI, quantum, and real estate: https://alex-companies.com/reports/linkedin-groups If there's an AI, quantum, or real estate community you'd like to see us convene, tell us — this portfolio grows by request.