Quantum computing is billed as a transformative computer architecture that’s capable of tackling difficult optimization problems and making AI faster and more efficient. But quantum computers can’t be scaled yet to the point where they can outperform even classical computers, and a full ecosystem of platforms, programming languages and applications is even farther away.
Meanwhile, another new technology is poised to make a much more immediate difference: neuromorphic computing.
Neuromorphic computing looks to redesign how computer chips are built by looking at human brains for inspiration. For example, our neurons handle both processing and memory storage, whereas in traditional computers the two are kept separate. Sending data back and forth takes time and energy.
In addition, neurons only fire when needed, reducing energy consumption even further. As a result, neuromorphic computing offers massive parallel computing capabilities far beyond traditional GPU architecture, says Omdia analyst Lian Jye Su. “In addition, it is better at energy consumption and efficiency.”
