Modern computing’s electricity consumption is rising rapidly, with projections suggesting that by 2026, data centers, artificial intelligence (AI), and cryptocurrency operations could double their 2022 energy usage levels, potentially matching Japan’s annual energy needs. To address this, companies like Nvidia are focusing on developing more energy-efficient hardware, while others are exploring fundamentally different architectures, such as neuromorphic computing. This approach mimics the brain’s structure, integrating memory and processing into single units on a chip, which reduces energy consumption and enhances processing speed. Commercial initiatives like SpiNNcloud Systems are advancing this technology, offering neuromorphic supercomputers for AI applications and edge computing. Despite technical challenges and high costs, innovations from Intel and IBM, such as Intel’s Hala Point and IBM’s NorthPole chip, highlight significant progress in this field, poised to revolutionize computing alongside traditional and quantum computing platforms.