Is it time to cool our quantum jets?

I've previously described quantum computing as being in its "ENIAC" phase, an analogy that would put effective quantum computing several decades away, at best. After all, it took seven decades for binary computers to get from ENIAC to Android, and there was no reason to suspect that quantum computers would any easier to develop than their binary predecessors.

According to a long article on IEEE.org, penned by Mikhail Dyakonov, who does
research in theoretical physics professionally, that decades-away estimate might actually be too optimistic. Quantum computers, he argues, might be more than merely difficult to develop, but impossible.

While I believe that such experimental research is beneficial and may lead to a better understanding of complicated quantum systems, I’m skeptical that these efforts will ever result in a practical quantum computer. Such a computer would have to be able to manipulate—on a microscopic level and with enormous precision—a physical system characterized by an unimaginably huge set of parameters, each of which can take on a continuous range of values. Could we ever learn to control the more than 10³⁰⁰ continuously variable parameters defining the quantum state of such a system?

My answer is simple. No, never.

I believe that, appearances to the contrary, the quantum computing fervor is nearing its end. That’s because a few decades is the maximum lifetime of any big bubble in technology or science. After a certain period, too many unfulfilled promises have been made, and anyone who has been following the topic starts to get annoyed by further announcements of impending breakthroughs. What’s more, by that time all the tenured faculty positions in the field are already occupied. The proponents have grown older and less zealous, while the younger generation seeks something completely new and more likely to succeed.

All these problems, as well as a few others I’ve not mentioned here, raise serious doubts about the future of quantum computing. There is a tremendous gap between the rudimentary but very hard experiments that have been carried out with a few qubits and the extremely developed quantum-computing theory, which relies on manipulating thousands to millions of qubits to calculate anything useful. That gap is not likely to be closed anytime soon.

His entire article gives a solid accounting of the history of quantum computing, along with a detailed (but still accessible) descriptions of the problems facing QC development, problems which  Dyakonov has come to regard as insurmountable. Not merely difficult, not merely challenging, but impossible to overcome, given the theoretical limitations imposed by the uncertainty principle which appears to govern quantum systems. The whole thing is well worth reading, and I urge you to do so.

The conclusions are difficult to dispute, though, with even optimists concluding that QC is a long, long way off. This Bloomberg article, "Why Quantum Computers Will Be Super Awesome, Someday," is a decent exemplar:

6. When do I get my quantum computer?

Not anytime in the near future, and for two reasons, one of which is computing power. Among the universal quantum computers built so far (universal meaning not limited to solving only certain kinds of mathematical problems), Google has the biggest, with 72 qubits, while Rigetti is promising a 128-qubit one within the next 12 months. That would be close to the point at which these machines will be able to do something that a classical computer cannot, a milestone known as “quantum supremacy.” But even these first applications may be very specialized — that is, useful in chemistry or physics but little else.

7. What’s the other reason?

Errors, lots of them. Scientists have only been able to keep qubits in a quantum state for fractions of a second — in many cases, too short a period of time to run an entire algorithm. And as qubits fall out of a quantum state, errors creep into their calculations. These have to be corrected with the addition of yet more qubits, but this can consume so much computing power that it negates the advantage of using a quantum computer in the first place. In theory, Microsoft’s design should be more accurate — but so far it hasn’t succeeded in producing even a single working qubit.

On the other end of the spectrum, we see stories like SingularityHub's "How Quantum Computing is Enabling Breakthroughs in Chemistry," which seems to suggest that effective QC is already here. Read the actual text of the story, though, and a different picture emerges:

Quantum computing is expected to solve computational questions that cannot be addressed by existing classical computing methods. It is now accepted that the very first discipline that will be greatly advanced by quantum computers is quantum chemistry.

Accepted by whom? And when is this expected to take place? SingularityHub's article is full of speculation and assumption, and the things that researchers hope to achieve, but none of it has happened yet. If skeptics like Dyakonov are right, these breakthroughs may never happen; at best, they're decades away.

This is why takes like TechCrunch's "Quantum computing, not AI, will define our future" are starting to ring hollow for me. Sure, true AI may be a long way off; given that we don't yet really understand what a mind is, or how our own minds work, it could be that our current approaches to AI may never bear fruit. But effective Machine Learning is already a thing, and already set to upend the way our society does almost everything; full-blown artificial general intelligence may never materialize, but it isn't necessary to bring about a Singularity-adjacent transformation of our world. QC, meanwhile, can't even keep itself powered up and running long enough to perform even simple tasks.

If you'd asked me a week ago, I'd have told you that I fully expected effective quantum computers to become a thing in my lifetime, while artificial general intelligence remained just out of reach. Now, though, it's looking like QC isn't any closer to fruition, with both next-level computing technologies now set to fail at becoming a thing before I find a patch of daffodils to fertilize. Which kinda sucks, but that's what always happens when you believe the hype: disappointment.

Long story short: if you were thinking of investing your life savings in D-Wave, now that FAANG stocks (yes, all of them) are plummeting in value, you should probably look elsewhere. Maybe look at renewable energy companies' stock, instead.