October 24, 2025, 12:10 AM EDT. MIT materials science grad student Miranda Schwacke explores how materials design can reduce AI's energy footprint. Through neuromorphic computing-hardware that processes and stores information in the same place-her work uses electrochemical ionic synapses that can be tuned like neural connections. Her advisor Bilge Yildiz notes that the brain's efficiency comes from minimizing data movement, a major energy sink in training large AI models. The goal is brain-inspired, energy-efficient AI hardware that preserves performance while cutting power. The Kitchen Matters experiments-showing how changing a structure alters properties-underscore a core principle: architecture drives energy use and speed. Schwacke's research spans materials science, engineering, and sustainability as she eyes new devices for AI that learns more like the brain.
October 24, 2025, 12:08 AM EDT. Nokia's chief executive argues that AI funding will accelerate rather than stall, describing AI as a super cycle with massive prospects. He frames ongoing AI investments as core to Nokia's strategy, spanning network infrastructure, edge computing, and next-gen services. The comments position AI as a long-term growth engine amid competitive telecom markets, with management emphasizing the need to scale capabilities, attract talent, and partner with software ecosystems. The article highlights how AI-driven optimization could improve network performance, reduce costs, and unlock new revenue streams for operators and Nokia alike. Investors are watching for sustained commitment to AI initiatives, with implications for the broader tech and telecom landscape.