Quantum Computing is Schr?dinger’s Opportunity

It’s Here, and Not Here at the Same Time

In the past few weeks, I’ve ended up learning a little about quantum computing. I’ve enjoyed discussions with leaders from Microsoft’s quantum team, IBM Q, Ctrl-Q, IonQ and the Cambridge Quantum Computing centre. I even saw a model of the distillation refrigerator of an IBM quantum processor. The processor needs to be cooled to close to absolute zero to operate. (For more amazing pics of how liquid-helium-punk these rigs are, check this out.) This essay is dedicated to questioning: what’s holding back investors from putting more money into quantum startups and general R&D.

This piece was originally published in the latest issue of my weekly newsletter Exponential View. Subscribe here

The promise of quantum computing

Quantum computing promises to be a totally novel form of computation, bringing a mastery to the physics unveiled by De Broglie, Schr?dinger, Heisenberg, Bohr and their chums less than 100 years ago. I won’t dig too much into what quantum computing is and what opportunities it holds, but if you need a primer watch Julie Love’s accessible 20-minute presentation.

The critical thing to understand about quantum computing is that it could deliver a tremendous amount of affordable computing power, compute that we need to solve key problems in the world. Assuming we can get enough stable “logical” qubits — the fundamental building blocks of quantum calculations — to build a working computer, the technology could turn vital calculations that are currently intractable into soluble ones.

One example of a quantum speedup is in search problems. These grow exponentially complex in classical computers, but sub-exponentially using Grover’s algorithms on a quantum computer. For a 1 million item path, a quantum computer takes 500 times fewer steps than a traditional computer.

To give another practical example, consider trying to understand how FeMoco, the chemical cofactor of bacterial nitrogenase, helps make those helpful prokaryotes so darn energy-shrewd at nitrogen fixation. The Haber-Bosch process consumes about 3% of the world energy; learning from the bacterial approach to nitrogen fixation would have a huge green dividend. There are other wins at the new frontier of novel biochemistries, including carbon capture, identifying new materials and exponential improvements in drug discovery that could be unleashed by quantum computing. Other applications include machine learning and logistics.

The physics has long said we can build these machines. It was in the early 1980s that, most famously, Feynman & Deutsch, initiated the field of quantum computing.

Some experts argue that in the past couple of years we’ve made significant progress in tackling the key issues of building quantum computers, and their components, qubits. Currently, nearly half a dozen different technologies vie for supremacy in building qubits: superconducting qubits (as found in IBM’s computer); topological qubits (which Microsoft is trying to use); trapped ions (IonQ’s approach); quantum dots (which Intel took a hedge on when it backed QuTech, a Dutch University spinout); and, potentially, diamond-defect qubits. Of these approaches, superconducting qubits & trapped ions appear to have the most progress.

When experts argue that we’re past the science stage. In some senses they are right. The biggest technical issues relate to error-correction, coherence and scaling the number of qubits to usable. But I hear time and again from quantum experts that these problems are now increasingly in the realm of engineering, rather than science. (Watch Oxford’s Simon Benjamin discuss this point.)

Today we actually have working quantum computers which are accessible via web services. The best known is IBM’s Quantum Experience, a 20-qubit quantum computer. The more technically au courant might like this brief write-up of using a Rigetti quantum computer to calculate the binding energy of a deuteron.

There is a twist

If quantum computing promises so many multi-trillion dollars opportunities, in machine learning, drug discovery and search, as well as in the not-so-distant-future quantum computing giving humanity its biggest dividend ever — surviving or mitigating the impact of climate change — then shouldn’t we be doubling down on it?

This would lead to expectations of huge levels of investment. A multi-trillion dollar payout in the foreseeable future is worth something today, even discounting for risk.

What we actually see is a very nascent field. While the investment levels are slowly rising, the field remains tiny. We looked at three vectors: what had governments announced, what we found from public announcements of investments in quantum computing companies, the amounts the large companies invested in the quantum computing domain.

What we found was surprising.

Given the large potential of quantum computing, the actual investment levels are low (with one exception, see at the end of this). We reckon, from a rough LinkedIn count, that fewer than 2,000 people are involved in companies working in any part of the quantum stack (and that includes all the marketing and PR types attached to these groups in large companies). IBM Q, which runs a developer ecosystem via the IBM Quantum Experience API, should have the deepest team. My scan on LinkedIn (far from perfect) shows only 300-or-so names attached to quantum computing in all of IBM. The startups are of similar scale, Rigetti, numbering less than 150.

Some estimates go beyond this. There are 7,000 researchers working on quantum computing around the world — a more healthy, but still small number — according to the European Commission.

The amount of venture dollars flowing intro quantum computing is small, with D-Wave ($175m), Rigetti ($70m), Cambridge Quantum Computing ($50m) and IonQ ($20m) leading the pack. The European Commission further estimates that total global annual investment in quantum research is some €1.5bn per annum. (Deloitte has further estimates: suggesting that there is about $2.2bn investments globally by governments in quantum computing.)

So quantum computing is Schr?dinger’s opportunity, simultaneously here and not here at the same time.

On the one hand, quantum computing is getting all the accoutrements of a technology close to maturity (press briefings, Gartner reports, analysis from investment banks and management consultancies) and the large tech firms are trumpeting working systems within 5 years.

On the other, investment levels are tiny by the standards of what large companies can put to work, or what VCs invest (Wag, a dog-walking app, recently raised $300m.) This suggests that these smart investors are discounting the potential upside very heavily, i.e. there are many hurdles, which these investors cannot easily enumerate, to overcome or the time frame to realise is very long.

Which is it? Close to maturity or facing a long journey?

The three things holding us back:

1. The science has been hard. This hasn’t been metaphorically quantum physics, it has really been quantum physics. However, as many of the players in the field argue, lots of the problems are now engineering rather than science problems. And there are lots more engineers than theoretical physicists out there.
2. Venture investors need returns within a time frame and with less uncertainty. The fact that there are only three venture-backed startups building the hardware (D-wave, with their application-specific system, Rigetti & IonQ) suggests that most venture investors are more cagey about whether this really is the realm of engineering vs. research, and just how much capital it will take to make these things work.
3. Governments haven’t stepped up to the plate as the “investor of first resort” in basic technologies, in recent years. (I have a podcast coming up on exactly this topic with venture capitalist & economist, Bill Janeway, in a couple of weeks.)

In fact, it seems that today the second and third reasons are the main attenuators. There is still too much uncertainty about when the technical barriers will be overcome and we can actually have useful quantum computers accessible. And many governments are chary about really backing core research, despite the ample long-term evidence of their positive impact in fundamental domains.

In this excellent BCG report, which I recommend reading, the consultants’ estimates for the size of the quantum computing market by 2035 vary by a factor of 28, from $57bn (in their high case) or $2bn (in their base case)!!

The projections suggest:

A substantial market for quantum computing, but the timing could vary widely depending on when the critical technical milestones are reached that unlock actual computing capacity.

In other words, the mid-term potential for this market is rather binary, dependent on when we actually get it all to work.

Of course, there is an exception to all this. And that exception is China where a National Laboratory for Quantum Information Sciences will attract between $10–16bn of investment when it opens in two years. This is pretty significant, likely enough to put China in the lead in developing this technology. China’s Alibaba also has a public-cloud implementation of quantum computing, an 11-qubit machine, at this point smaller than IBM’s cloud-accessible device.

Only two years ago, I was pretty sceptical about where quantum computing was in its cycle. And as Jerry Neumann points out, quantum computing was only “five years away” back in 2000, so quantum could be one of those technologies, like controllable fusion, that is always just around the corner. But something feels a bit different this time… I’d just love to see higher levels of investments in this exciting field.

This piece was originally published in the latest issue of my weekly newsletter Exponential View. Subscribe here