Photonic Quantum Chips Could Outpace Transformer AI
Photonic quantum chips may leapfrog today’s AI by doing machine learning with light—ultrafast inference, 92%+ accuracy, far lower energy—while we keep betting on bigger transformers.
Photonic quantum chips may leapfrog today’s AI by doing machine learning with light—ultrafast inference, 92%+ accuracy, far lower energy—while we keep betting on bigger transformers.
Transformers predict tokens brilliantly but hit limits. Emerging architectures like Pathway’s BDH and Google’s MIRAS aim for modular, memory-rich systems that reason like living organisms, not parrots.
When conflict heats up, ask “What need are they trying to meet?” and guess out loud. After 20+ years studying empathy, I’ve seen enemies become allies when you treat anger as data, not attack.
Breaking AI tasks into specialized agent teams—each handling research, drafting, or review—often beats dumping everything into one prompt. Cleaner output, faster results, lower cost.
Cognitive empathy with people who trigger you isn’t about excusing them—it’s resistance training for your nervous system, turning hard conversations into data and building regulation skills.
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