Fission vs Fusion: Nuclear Power Dey Fuel AI Future

AI energy demand dey soar as advanced models dey consume plenty power. To train one big AI model fit use as much electricity as 100 US homes for one year. By 2030, power wey global data centers need fit jump 165%, because AI energy dey grow. Dis big increase show say clean and reliable nuclear power important. Current plants dey use fission to split uranium atoms. Fission don proven, e cost-effective, and e provide stable baseload power. But e get challenges like safety concerns, radioactive waste, and strict rules. Fusion promise even more energy by joining hydrogen atoms. E dey produce small long-lived waste and no get meltdown risk. But fusion reactors need extremely high temperatures over 100 million °C and e still dey experimental. Small Modular Reactors (SMRs) fit fill today’s AI energy gap with faster deployment and flexible output. At the same time, China don expand im cyber capabilities. The “Salt Typhoon” campaign show say China fit pre-position digital weapons inside US infrastructure. Experts dey warn say US need AI-powered “digital twins” for defense and need invest in offensive cyber capabilities. Lastly, China brain-computer interface (BCI) industry fit reach $777 million by 2027. Backed by strong policies and patents, China dey target global BCI leadership by 2030. These technology and security trends show the strategic importance of energy, cyber, and human–machine integration.