Arthur C. Clarke – the British novelist most famous for his 1968 work ‘2001: A Space Odyssey’ – once wrote that “any sufficiently advanced technology is indistinguishable from magic”. Recent developments in the field of artificial intelligence might fit this description – and go some way to explain the share price performance of large tech companies innovating in this space. In reality, today’s artificial intelligence – alongside other frontier technologies like the Metaverse and Blockchain – is built upon the foundations of classical computing. In ‘classical’ computing, transistors – acting as miniature electrical switches which can be either ‘on’ (1) or ‘off’ (0) – manipulate the flow of electricity to allow computers to represent and process information using binary digits (bits); more transistors equates to faster computing speeds and better connectivity.
Moore’s law - which holds that the number of transistors per silicon chip will double every year1 - has proven to be an accurate predictor of the pace of electronic technology advancement since it was postulated in 1965.2 However, there are increasing question marks over the physical limits of continued electronic miniaturisation; today’s leading edge chips already contain tens of billions of transistors, with many advanced transistors now built atom-by-atom.3
Many experts believe we could be on the verge of entering a new era of computing, one which promises to unlock new frontiers of processing power and re-define the problems we can solve using computers – the quantum era. Quantum computing isn’t a particularly new idea; in 1982, Richard Feynman outlined how quantum mechanics could be used to revolutionise computing. The underlying science behind quantum computers is beyond the scope of this article - and indeed most graduate-level courses in physics (Feynman himself is famous for saying “I think I can safely say that nobody understands quantum mechanics”).
However, there are two key ideas which are worth highlighting: superposition and entanglement.
The basic unit of a quantum computer is known as a ‘qubit’; unlike bits in classical computing, which take a value of 1 or 0, qubits can exist in both states simultaneously. This is often likened to a coin mid-spin, with some probability of the coin landing on heads or tails4; this ‘mid-spin’ state is known as superposition and it allows quantum computers to explore multiple solutions to a problem at once. Achieving superposition for more than a few seconds is not easy: ‘noise’ (in the form of ambient thermal energy or electromagnetic interference) can easily disrupt the system. To counteract this, quantum computers must be supercooled close to absolute zero (−273.15 °C, or 250 times colder than deep space).5
Entanglement is perhaps even more perplexing: when two particles become ‘entangled’, they remain connected even when separated by vast distances6 – a phenomenon Einstein referred to as “spooky action at a distance”. While this observation defies our understanding of time and space, there is a clear implication for quantum computers: if one qubit is added to a system, the number of potential states of the system doubles – approximately doubling the computational capabilities of the machine.
According to experts, we are currently in the ‘Noisy Intermediate Scale Quantum’ [NISQ] era of quantum computers7; the goal is transition into a ‘Fault Tolerant Quantum Computer’ [FTQC] era – where there is a sufficient number of high quality qubits to ensure computation remains uncompromised by errors and noise.8 While a number of major obstacles stand in the way of quantum computers achieving ‘quantum advantage’ – that is, accomplishing a task faster, more cheaply or more efficiently than a classical computer – a series of recent breakthroughs in error correction techniques9 10 suggest this second era of quantum computing might be closer than many expect. In December 2023, IBM unveiled ‘Condor’, a new 1,000 qubit quantum chip which represents a 50% increase in qubit density versus its predecessor (‘Osprey’); the company expects to develop a FTQC machine by the end of this decade.11 Other companies – some familiar (Alphabet, Amazon, Microsoft, Intel), some perhaps not (D-Wave, Quantinuum, Rigetti) - have announced similarly ambitious plans.12
The potential impact of these machines, if developed, is difficult to comprehend.
As Richard Feynman pointed out, “nature isn’t classical … if you want to make a simulation of nature, you’d better make it quantum”.13 Drug molecules, for example, are quantum mechanical systems. In pharmaceutical research and development, extensive lab work is required to understand candidate molecules, with many cycles of synthesis and testing; quantum computers could, in theory, skip this process of identifying what works or doesn’t work by screening billions of candidate molecules – dramatically accelerating drug development timelines, reducing costs and, ultimately, improving patient outcomes.14
With many more potential use cases – from simulating the complicated chemistry of prototype battery designs to improving the performance of options pricing models in finance15 – estimates of the total addressable market for quantum computers vary wildly. However, the literature seems to agree that the industry is poised for exponential growth over the current decade, with estimates ranging from a 15% to 50% compound annual growth rate16. Investors are certainly awake to the potential opportunity: public funding for quantum technologies increased by over 50% year-over-year in 202317, with total announced government spending at c.$42bn. As at 31 December 2023, there are 261 quantum computing start-ups globally18, with c.65% of patent applications submitted by the private sector19.
Alongside the obvious engineering challenges of scaling quantum computing, a number of other important questions remain unanswered: how will Quantum Computing as a Service [QCaaS] business models evolve (there is consensus among experts that the sheer size and delicate nature of these machines means quantum computers will be accessed via the Cloud for the foreseeable future)20; how will quantum computers work alongside classical computers (many of the current algorithms designed to work on quantum computers also require a classical computer by design)21; perhaps most notably, which qubit technology – if any – will become the de facto standard (whereas silicon is the base material for classical chips, there are currently a number of different physical starting points for qubits – each with advantages and disadvantages)?22
However, the direction of travel seems clear; Hartmut Neven, the founder of Google’s Quantum AI Lab, has suggested the rate of progress in quantum computing might look like “nothing is happening, nothing is happening, and then whoops, suddenly you’re in a different world”.23 This different world might be closer than we think.
[1] Britannica. (2024) Moore’s Law. Accessed 20 May 2024.
[2] Powell, J. (2008) The Quantum Limit to Moore’s Law. Proceedings of the IEEE, 96(8), p.1247.
[3] Financial Times. (2024) Inside the miracle of modern chip manufacturing. Accessed 20 May 2024.
[4] Quantum Network Explorer. (2024) Superposition. Accessed 20 May 2024.
[5] Data Centre Dynamics. (2024) Cooling quantum computers. Accessed 20 May 2024.
[6] Caltech Science Exchange. (2024) What Is Entanglement and Why Is It Important?. Accessed 20 May 2024.
[7] Boston Consulting Group. (2021) What Happens When ‘If’ Turns to ‘When’ in Quantum Computing?. Accessed 20 May 2024.
[8] McKinsey. (2023) Quantum technology sees record investments, progress on talent gap. Accessed 20 May 2024.
[9] Financial Times. (2023) Google claims breakthrough in quantum computer error correction. Accessed 20 May 2024.
[10] IBM. (2023) The hardware and software for the era of quantum utility is here. Accessed 20 May 2024.
[11] Ibid.
[12] Forbes. (2023) Top 10 Quantum Computing Companies Making Change. Accessed 21 May 2024.
[13] Nature Physics. (2012) Quantum simulation. Accessed 21 May 2024.
[14] Citi GPS. (2023) Quantum Computing – Moving Quickly from Theory to Reality, p.48.
[15] Ibid. p.9.
[16] Ibid. p.97.
[17] McKinsey. (2024) Steady progress in approaching the quantum advantage. Accessed 21 May 2024.
[18] McKinsey. (2024) The rise of quantum computing. Accessed 21 May 2024.
[19] Citi GPS [14]. p.75.
[20] Ibid. p.107.
[21] Ibid. p.27.
[22] Microsoft Azure Quantum. (2024) Explore quantum – types of qubits. Accessed 21 May 2024.
[23] Quanta Magazine. (2019) A New Law to Describe Quantum Computing’s Rise?. Accessed 21 May 2024.
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