Investors must educate themselves on Quantum Computing so they are not left behind by disruptive technology

IonQ Q3 results are just in. If you haven’t been following too closely, IonQ is an Ion Trap pure-play quantum company – the first of its kind to be listed on the stock market which it did fairly rapidly via a SPAC. Recently we have seen the tie-up of Cambridge Quantum and Honeywell’s Quantum division into Quantinuum, which may naturally lead onto the public markets. As Quantum gains more traction, investors must look at the nascent sector and understand the impact that Quantum technologies will have on a range of industries as well as the technology itself to separate fact from fiction.

Understanding Quantum

Quantum Computing isn’t just an accelerator of existing technologies. In a way, it is an entirely new paradigm. Of course, users hope that it confers benefits such as faster run-time and smarter algorithms, but what it isn’t is a faster method of doing exactly the same thing. That means those who want to exploit quantum will need to go through a steep learning curve. That isn’t to diminish from the potential of quantum, but just a cautionary note. Perhaps for many, it is easier to explain what quantum is not, rather than what it is! This isn’t just putting Q in front of existing technologies and badging them Quantum. A quantum circuit and quantum hardware work very differently from classical or traditional computing which relies on binary 1’s and 0’s. Quantum requires quantum thinking or certainly quantum training and therefore, education is a smart way to gen-up on how quantum computing works.

Introducing the Qubit

We have written about some of the quantum learning resources and courses out there, from online courses to textbooks to books aimed at general understanding. One of the gentlest ways of getting into the field and understanding some of the fundamental components of the qubit is with online courses. Some of these we have covered here, but there are new courses emerging all the time, like a recently announced black opal course from Q-ctrl. Many will want to explore quantum programming through one of the numerous quantum programming languages out there

For those who would prefer book form, and there is nothing wrong with that, there are excellent books that can introduce users to quantum programs, primarily through Qiskit or Cirq. Two books that have proved popular with readers are Dancing with Qubits by Bob Sutor and Quantum Computing: An applied approach by Jack Hidary. Of course, there are others, but these are a good place to begin the quantum journey.

The commercial benefits, use-cases and more use-cases

Quantum isn’t a panacea for the ills of classical computing bottlenecks. Use cases for Quantum are continuously being developed and we think will provide most with a much better understanding of what quantum computers can and cannot do. In our opinion, there is nothing better than getting to grips with a real live use case. Understanding where the benefits come in really helps elucidate the whole rationale behind QC.

The application of quantum isn’t easy and finding a way through is key. Understanding right now, where the benefits of quantum are and will be is central to understanding the investment proposition. Hype is not your friend here, and investors must separate the signal from the noise.

Understanding what quantum can and cannot do, should therefore be the motive of any investor as well as understand some of the hardware flavours, we may not be able to pick a winner just yet, but understanding the types and tracking their progress will provide a trend that many are following. There are some excellent resources out there that can cater to a range of base levels of understanding. Fundamentally it helps to understand how Quantum is so different and the challenges and pitfalls that come along with it, and that might mean dusting off the Quantum Mechanics 101 folder and getting to grips with the less than intuitive results of Quantum such as superposition and entanglement.

The promise of faster or better results has many sectors excited. Even if we cannot do computations always faster, we may be able to get better results. Take for example the work in quantum-classical or Hybrid Neural Networks, which show that networks can train more effectively.

We are in the early days of those use-cases, but a few are here, and without listing, we point you to the recent announcement of a cyber security product named Quantum Origin from Quantinuum fka as Cambridge Quantum.

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