Introduction
Quantum computing is a type of computing that uses quantum bits (qubits) instead of classical bits to process information. This allows quantum computers to perform certain tasks, such as factorization and simulation, much faster than classical computers. However, despite the potential benefits, quantum computing is still in its infancy and there are still many challenges that need to be overcome before it can be widely adopted.
Challenges of investing in Quantum
One of the main challenges is the cost. Quantum computers are extremely expensive to build and maintain, requiring specialised hardware and software. According to a report by the consulting firm McKinsey, the cost of building a quantum computer capable of performing certain tasks can range from $10 million to $1 billion. Additionally, they are not yet able to perform calculations as quickly as classical computers when it comes to certain tasks. For example, a recent study by Google found that a classical computer was able to simulate a financial market more than 10 times faster than a state-of-the-art quantum computer.
Applications of Quantum
Despite the challenges, many experts believe that quantum computing has the potential to revolutionise various industries, including healthcare, energy, and logistics.
In healthcare, quantum computing could be used for a wide range of applications such as drug discovery, medical imaging, and personalised medicine. For example, quantum computing can be used to simulate the interactions between drugs and proteins, which could accelerate the drug discovery process. In medical imaging, it can be used to process large amounts of data from medical images, such as magnetic resonance imaging (MRI) and computed tomography (CT) scans. This could improve the accuracy of diagnoses. In personalised medicine, it can be used to analyse large amounts of genomic data, which could lead to more personalised treatment plans for patients.
In energy, quantum computing could be used for simulating complex chemical processes and optimising the performance of renewable energy systems. For example, quantum computing can be used to simulate the behaviour of complex molecules and chemical reactions, which could lead to new materials and catalysts with improved properties. In addition, quantum computing can be used to optimise the performance of renewable energy systems such as solar and wind power, which could lead to more efficient and cost-effective energy production.
In logistics, quantum computing could be used for optimization of supply chain and logistics systems. For example, quantum computing can be used to optimise routing and scheduling for transportation and delivery networks, which could improve the efficiency and cost-effectiveness of logistics operations. In addition, it can be used to optimise inventory management and warehouse operations, which could lead to more efficient use of resources and lower costs.
In finance and capital markets, quantum computing could have a number of applications such as risk management, fraud detection, and portfolio optimization. Quantum computing can be used to perform complex simulations of financial markets, allowing investors to better understand and manage risk. This could be particularly useful for portfolio optimization, which involves balancing the risk and return of different investments.
Quantum computing can also be used to detect fraudulent activity by analyzing large amounts of data, such as transaction records. This could be particularly useful for detecting money laundering and other financial crimes. Additionally, it can be used for optimization of financial models, such as those used in derivatives pricing and risk management, which could lead to more accurate predictions and improved decision making.
These ultra fast computers can also be used for optimization of financial algorithms, such as those used in high-frequency trading, which could lead to faster and more efficient trading decisions.
Overall, this emerging technology has a wide range of potential applications in different industries and it has the potential to revolutionise the way we live and work.
Investing in Quantum
Quantum computing is a great example of deep tech investing – see our blog introduction to deep tech. For high net worth investors, investing in private companies at the venture stage that are pioneering in quantum computing can be a risky but potentially lucrative opportunity. However, it is important to keep in mind the current limitations of quantum computing and the fact that it may be several years before commercial products become available.
One example of a company pioneering in quantum computing is Rigetti Computing. Founded in 2013, the company has developed a machine with 19 qubits, which is one of the most powerful quantum computers available. According to the company, their machine can perform certain tasks 100 million times faster than a classical computer.
Another example is IonQ, a company that has developed a trapped ion quantum computer that can perform certain tasks faster than a supercomputer. The company has raised over $100 million in funding from investors including New Enterprise Associates and Two Sigma Ventures.
However, it’s important to note that investing in early-stage companies involved in quantum computing can be a high-risk, high-reward proposition. These companies may have limited applications of quantum and it could be a long time before they see commercial products. It’s important to do thorough research and consult with experts before making any investments.
A number of VC firms have made investments into quantum computing, especially those specialising in deep tech. We have only found one VC firm specialising in quatum computiing and that is Quantonation which closed a fund last year.
Conclusion
In conclusion, quantum computing has the potential to revolutionise various industries, but it’s still in its infancy. High net worth investors should keep an eye on the technology and consider investing in private companies at the venture stage that are pioneering in the area. However, it is important to be aware of the challenges and limitations of the technology and to consider you risk tolerance and time scales.
