There’s a lot of momentum building up around quantum computing. Big, established companies like IBM, Microsoft, Google and Honeywell are putting their vast resources behind the drive to reach true quantum computing and an array of smaller pure-play startups are rapidly cropping up around them, armed with expertise and a growing amount of funding.
The qubits are beginning to pile up in relatively early systems and the push for creating highly stable qubits is expanding the range of methodologies that are being used to create them. Seeing the economic and political advantages of being among the first to have functional, working quantum systems is fueling growing investments in the space from governments around the world.
However, the acceleration in the quantum computing space and the growing number of companies, universities and government agencies that are pushing this wheel are driving the industry into the same problems that other market segments — think cybersecurity and data science — have hit: a skills shortage.
Yehuda Naveh has a front-row seat to the situation. The co-founder and chief technology officer for quantum startup Classiq — which helps automate processes for quantum algorithm developers — Naveh said the skills shortage is beginning to show itself on both the supply and demand sides in the industry.
The number of companies and universities developing in-house quantum computing hardware and software — from algorithms to applications for a broad range of industries, like banking, oil and gas, aerospace and automotive — is growing and requires a lot of talent, Naveh told The New Stack.
That is from the demand side, from the players who need the talent.
“From the supply side [those providing the talent], “the supply is lagging behind because if we think of this revolution as starting in, say, 2017, there was a really low demand,” he said. The rising demand “caught the universities by surprise. No one expected this and this means a boom in quantum information science is required to fill all this demand.”
Quantum on the Maps Since the 1980s
Quantum computing has been talked about since the early 1980s, but for much of that time since it’s been a theoretical and academic study. It was being worked on by relatively small groups of people and any real growth in the demand for skilled people was essentially linear, Naveh said. What happened four or five years ago were major advancements in physical engineering abilities in the industry and a significant jump in the development of quantum hardware, turning the theoretical onto the path of engineering.
Those developments around 2017 included jumps in the ability to keep the qubits (quantum bits) very cold — a key requirement in quantum computing — and advancements in the ability to building very solid and almost noiseless qubits, he said. Companies like IBM and Google began to drive the development of quantum algorithms and the demand for skilled quantum hardware and software makers began to rise more sharply.
That’s not to say that quantum computing is ready to break out of its niche tomorrow to become a booming segment like cybersecurity. But the future looks busy. Market research firm Statista expects global quantum computing revenues to jump from $471 million this year to $1.76 billion in 2026. Networking site LinkedIn recently noted that there were more than 5,000 job listings for quantum computing in the United States from such known companies as Nvidia and Cisco Systems as well as smaller startups like ColdQuanta and Atom Computing.
Growing Demand for Skill
The demand will only grow. Companies in the space are reaching the point of having working quantum computing systems holding 100 qubits. While that may not be enough to run much in the way of commercial workloads, more companies expect systems housing thousands and eventually millions of increasingly stable qubits to emerge in the coming years with such crucial capabilities as error correction code (ECC) to make them more reliable.
Classiq’s Naveh said that roadmaps he has seen show quantum systems with a few thousand qubits coming out in the next two or so years. The elastic quality of the qubits will be better, which means that by the third quarter of 2023, there could be systems running algorithms on 1,000-qubit systems.
“It is not to say that the devices will work perfectly,” he said. “It is not to say that we have solved some significant industrial problems, but it is going to change the way of computing for the prototype and the initial experiments that we’ve got today into really industrial experiments that will be going on.”
A Bigger Stack and Smaller Needle
The challenge is that finding skilled people for the quantum computing space is not the same as finding data scientists or cybersecurity experts. It’s not simply a numbers game. Most of those entering the industry are generalists coming with backgrounds in theoretical physics, computer science, mathematics or electrical engineering, Naveh said. Companies in the quantum space have to take those people and train them to be quantum scientists who can build quantum processors or create algorithms, all of which take time and effort.
“As we can all recognize, it takes at least five — and I would say even 10 — years to train a fresh student into being a quantum information scientist,” he said. “It’s shortages of the people who develop the algorithms. For the people who build both the hardware and for designing algorithms, you need to have expertise in quantum information science. This is not something that is very simple to get into.”
Naveh describes quantum computing as being a revolution in computer technology. Where traditional computing uses “bits” that can have values of 0 or 1, with quantum computing — which rely on the laws of quantum physics — the qubits can be either or both at the same time, opening up the possibility of running calculations and workloads that are out of reach now at speeds significantly faster. It opens up tremendous opportunities for companies in industries that run highly complex computations, from pharmaceuticals and bioinformatics to artificial intelligence, financial services and energy.
At the Start of a Revolution
Even at a small startup — the company was founded last year in part by Naveh after almost 20 years at IBM, including part of that time working on the vendor’s quantum computing efforts – he is talking with software developers interested in learning about the field.
“I see people coming and having a passion for the field,” the CTO said. “I see a lot of people who want to be part of a revolution, of people who understand what it means to have a new computing paradigm. They have enough imagination and vision. They can see how it would feel if they could have been part of a computing revolution and now they see an opportunity to do just that.”
Vendors in the quantum space will need the resources to bring these people aboard and teach them about quantum computing science, he said. At the same time, universities need to increase the number of courses and programs so that more students are graduating with degrees in quantum computing. Schools like MIT and Stanford are expanding what they do, but more is needed if the quantum computing space is going to close the skills gap, Naveh said.
Self-Education Is Key
Students also must educate themselves on what the market demands of them. It goes beyond simply physics, computer science or electrical engineering. Students need to investigate the world of quantum computing — go beyond classes and do their own reading to get a better understanding of the industry. After that, if they are still interested, then they can take the next steps, such as choosing the right majors and ensuring to attend universities that offer quantum computing courses.
“This is the basics,” he said. “You need to study. You need to learn. It’s not something you can just do in books. Studying is not just going to universities. Studying is also looking around and being curious, asking questions and reading books. The most important thing for a student, especially in the first years, is to learn the meaning and not just sit in the class and listen and pass the exams. Many people can pass the exams, but this is not sufficient. You really need to understand what you are learning, to apply your motivation, to reach an actual understanding. For that, keep reading, keep opening the textbooks. There is an abundance of information on the Web, on the internet. Listen to books, listen to videos and read technical textbooks.”
Students can also apply the skills they are learning. Open source software — such as Qiskit and Q Sharp — is foundational to quantum computing, which means students and those already in the IT field who are interested in the space can download open source libraries, run algorithms and add their own code. It also will connect them to the community around these technologies.
Despite the challenges, Naveh said he is optimistic about the future of quantum computing.
“I’ve followed the field closely for more than 20 years, but specifically I followed it very closely in the last five or six years, since the engineering revolution happened and all I see is growth in the quality of the hardware, growth in the complexity, growth in the number of companies” preparing to leverage quantum computing once it gets robust enough, he said. “That’s why I am optimistic. On the supply side, I see countries investing a lot, investments by universities, investments by the governments to create very good programs in quantum computing. I’m optimistic both from the demand side and the supply side.”
The New Stack is a wholly owned subsidiary of Insight Partners. TNS owner Insight Partners is an investor in the following companies: Real.
IBM is a sponsor of The New Stack.