Towards the end of 2019, I was finishing a book, AI Concepts for Business Applications. The last chapter was titled, “The Future.” I wrote about quantum computing and a version of deep learning that was related: a “quantum walk neural network.”In 1980, the idea of a quantum processing unit was proposed. Such a processing unit doesn’t use the 1s and 0s with which we’re familiar. That “classical” way of thinking is the way we think, with a 1 for true and a for false, and combinations—for example, a “false positive.” Quantum computing is based on a “superposition” of states called “quantum bits” or “qubits” for short. But there’s a big difference between the way we think and the way nature behaves. In 1981, the late Caltech professor, Richard Feynman (a Nobel Prize co-winner for his work with “quantum electrodynamics”) summed it up: “Nature isn’t classical, dammit, and if you want to make a simulation of nature, you’d better make it quantum mechanical, and by golly it’s a wonderful problem, because it doesn’t look so easy.” Now, quantum computing is beginning to emerge.

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