Moore’s Law, which predicted that the number of transistors on a chip would double approximately every two years, driving exponential growth in computing power, has been the foundation of technological advancement for decades. However, as transistor miniaturization approaches its physical limits, we are now facing the era of “post-Moore's Law” computing. This shift presents both challenges and opportunities. The most immediate consequence of Moore's Law slowing down is the end of rapid performance improvements in traditional silicon-based chips. With transistor sizes approaching the atomic scale, further shrinking becomes impractical due to quantum effects, heat dissipation, and manufacturing complexity. This leads to diminishing returns on cost and performance improvements, forcing the industry to explore alternatives. One promising avenue is the development of new materials and architectures. Quantum computing, with its ability to perform parallel computations using quantum bits, offers the potential to solve certain classes of problems far faster than classical computers. Another approach involves neuromorphic computing, which mimics the human brain’s neural networks to perform tasks like pattern recognition with greater efficiency. Furthermore, advances in 3D chip stacking, where multiple layers of transistors are placed on top of each other, could prolong the gains in computational power. In addition to these hardware innovations, the post-Moore’s Law era will likely see greater emphasis on software optimization and algorithmic efficiency. As raw hardware performance growth slows, maximizing the efficiency of software will become crucial to maintaining innovation. While the end of Moore’s Law marks a significant turning point in computing history, it also opens the door to new possibilities. The future of computing will likely be shaped by a combination of quantum technologies, alternative computing paradigms, and breakthroughs in materials science, ushering in a new era of innovation beyond the silicon age.