A realistic outlook for quantum computing in the enterprise
By Neil Raden February 1, 2022
SUMMARY: Quantum computing is one of the hot topics on any 2022 tech predictions list. But what is realistically achievable today? How should enterprises consider the use cases — and computing requirements? And could QaaS (Quantum as a Service) play an enabling role?
In the summer 2021 a keynote on the state of play in quantum computing at Data Center World in Orlando, Celia Merzbacher, executive director of the Quantum Economic Development Consortium, described a technology still in its infancy:
Progress in the field is closely tied to the amount of qubits (the basic units of quantum information) engineers manage to get to work in concert. A thousand logical qubits is thought to be the minimum for doing any meaningful, but you need a million physical qubits to have 1,000 logical ones. That’s because physical qubits are sensitive to vibration, and you need so many of them “in order to correct for the noise and the errors in qubits today,” she explained. “I think when we make certain milestones, things may go pretty quickly through the scaling and getting to that million qubit system where we can do something useful.
At least, in theory, a quantum computer can run a billion times, or faster, than the fastest supercomputers. That will change in orders magnitude in the next five years. But there is a catch: there are more things a quantum computer can’t do than it can. The only company I’ve come across that realistically discusses the quantum “stack” and what it looks like is Quantum Machines. This interesting Israeli company developed (and sells) a universal orchestration package that manages quantum operations. They’ve developed quantum algorithms and even quantum programming languages. As Dr. Itamar Sivan, Co-Founder and CEO, Quantum Machines, explained to me:
Although reports in the popular press tend to focus on the development of qubits and the number of qubits in the current prototypical quantum computing chip, any quantum computer requires an integrated hardware approach using significant conventional hardware to enable qubits to be controlled, programmed, and read out.
According to Sivan, a quantum computer needs three elements to perform: a quantum computer and an orchestration platform of (conventional) hardware and software. There is no software in a quantum computer. The logic needed to operate the quantum computer resides with, and is controlled by, the orchestration platform. The platform manages the progress of their algorithm, through mostly laser beam pulses:
Contrary to popular perception, achieving quantum advantage isn’t as simple as replacing an enterprise’s classical compute infrastructure with shiny new quantum computers. Quantum computers will always make up just one component — albeit a unique, powerful one — of a more significant technology stack consisting mainly of classical computers. There are a few reasons for this. For any quantum application with business value, data will always need to be processed by classical computers before and after it is fed through quantum algorithms — whether to clean it, structure it or present it in a useful way for business decision-making.
Data — the stumbling block as usual
At the moment, quantum computing requires bringing all their decentralized data and computing power around the world together in one place. Not many sizable enterprises have their data centralized in one place. Logically, if you’re running a billion or a trillion times faster, any latency in orchestrating data will dilute the advantage.
What are the problems quantum computing can solve?
One promising area is modeling biological processes. Studying things like corrosion to help industries design materials with desired qualities — and systems optimization, will be useful for everything from helping the likes of Amazon and FedEx optimize routes for their massive fleets, to helping financial institutions optimize investment portfolios.
Cryptography — a problematic example, as Merzbacher pointed out:
Shor’s algorithm is an algorithm for factoring prime numbers, and eventually it’s believed that quantum computers are going to be able to run that algorithm and will break the prime number-based encryption standards that are widely used today.
An application with massive potential is supply chain management: supply chains provide the integration of inbound, outbound and reverse flows of products, services, and related information. Managing supply chains today requires understanding the diverse roles of the supply chain’s members, their interactions, and the transaction models they use to interact with one another.
Trying to optimize these flows for timeliness, yield, cost, and a host of other objectives is complex. Multi-point multi-role, multi-location supply chain systems are nonlinear (In mathematics, a nonlinear system’s output is not directly proportional to its input), dynamic and chaotic. Current deterministic supply chain models today are locked into rigid roles. Dynamic models gradually develop their capacity for differentiation and relationships, growing progressively towards their maximum potential contribution to the organization’s efficiency.
The problem is it takes a supercomputer, calculating and recalculating endlessly, to provide this capacity.
A classical supply chain is often complicated and includes the following elements:
- Mass amounts of information, goods, and capital flowing among suppliers, manufacturers, and distributors.
- Supply chain members may also be members of other supply chain networks.
- Constantly changing network structure.
- Supply chain members have their own goals.
In any of the current forms, a quantum computer, and there are at least five, no tenderization and likely more versions hiding in secret laboratories. Will you build a quantum infrastructure, and staff a team to write and maintain quantum algorithms? For most companies, the answer is no. Algorithms will need to be developed from scratch, by computer scientists who understand the idiosyncrasies of the particular machine they are working with.
My take — Quantum as a Service (QaaS)
So all of these factors add up to a future (and very near future) of cloud-based QaaS. For most enterprises, building out a quantum computing infrastructure (quantum computer, orchestration platform, and some way to gather the needed data for the quantum computer to operate) may be too expensive and challenging for now. MIT, AWS, Azure, and D-Wave’s Leap offer shared quantum services, including pre-written multi-purpose algorithms. For your specific application — biological engineering, for example — the QaaS offering may not provide the capacity you need, or it may turn out to be too expensive. But for the time being, QaaS offers an excellent on-ramp to Quantum.