The landscape of artificial intelligence is no longer shaped solely by algorithms, model architecture, or silicon wafer size. Today, power availability has become a decisive axis of AI scalability. The performance of next-generation language models, vision systems, and reinforcement learning frameworks hinges not just on computational elegance but on electrical throughput.
Deep within the cosmic expanse, trillions of particles known as neutrinos traverse the universe every second, weaving through stars, planets, and even our bodies with barely a whisper of their presence. These ghostly particles, born from the nuclear reactions of stars and supernovae, carry with them secrets that humanity has only begun to uncover. Despite their abundance, neutrinos are among the least understood phenomena in physics—a paradoxical enigma that has inspired decades of relentless inquiry.
For ages, the scientific community has been enamored by the potential of harnessing energy from the elusive matter waves of Louis de Broglie, often referred to as radiations of the unseen spectrum. The pioneering stride towards unraveling this mystery was taken by the illustrious Nikola Tesla, who termed these matter waves as "the aether." Alas, his endeavors, while visionary, did not culminate in practical applications.