In December 2024, Google announced that its Willow quantum chip — a device containing 105 superconducting qubits, operating at temperatures colder than outer space, housed in a dilution refrigerator in a Santa Barbara laboratory — had completed a benchmark computation in five minutes. The same task, run on Frontier, which was until recently the most powerful supercomputer in the world, would take ten septillion years. That is a number with 25 zeroes. It is roughly a trillion times the current age of the universe.
The caveat, which Google's own engineers were careful to state, is that the benchmark task in question has no direct practical application. It was chosen to demonstrate a specific capability of quantum systems, not to solve a real-world problem. "Could I solve a problem today that I couldn't solve yesterday?" asked one industry expert in response to the announcement. "The answer is no."
Both things are true simultaneously — and understanding how is the key to understanding where quantum computing actually stands, what it might eventually do, and why it matters enough that governments and technology companies around the world are investing billions in the race to build it.
What a Quantum Computer Actually Is
Classical computers, from smartphones to the world's most powerful data centres, store and process information as binary bits — each one either a 0 or a 1. Every calculation, every image, every word processed by a conventional computer is ultimately built from combinations of these two states.
Quantum computers operate on fundamentally different principles. They use qubits, which exploit the quantum mechanical property of superposition to exist in combinations of 0 and 1 simultaneously. A system of qubits in superposition can represent an exponentially larger number of states than the same number of classical bits. Combined with quantum entanglement — the phenomenon in which qubits become correlated in ways that have no classical equivalent — and quantum interference, which allows certain computational paths to be amplified while others are suppressed, quantum processors can explore vast numbers of possible solutions in parallel rather than checking them sequentially.
The result is not simply a faster version of what we already have. It is an architecturally different type of machine, suited to a specific class of problems that classical computers find intractable — not because classical computers are slow, but because the number of steps required to solve these problems grows exponentially with their size. For certain problems, the most powerful supercomputer on Earth cannot find the solution in any practical timeframe. A mature quantum computer might.
The critical qualifier is "mature." Today's quantum computers are what researchers call NISQ devices — Noisy Intermediate-Scale Quantum systems. They are powerful enough for significant experimental demonstrations, but noise, instability, and error rates prevent them from running the transformative applications their long-term potential promises. The engineering challenge of the decade is getting from here to there.
The Error Problem: Why Qubits Are So Hard to Control
The central engineering challenge of quantum computing is decoherence — the tendency of qubits to lose their quantum state through any interaction with their environment. A stray photon, a vibration, a tiny fluctuation in temperature, even the act of measuring can collapse a qubit's superposition, introducing errors that corrupt the computation.
This is why quantum processors must operate at temperatures of around 15 millikelvin — colder than the background temperature of outer space — in heavily shielded environments. And even then, qubits decohere. The errors must be detected and corrected, which requires additional qubits dedicated to error correction. In current systems, the overhead is substantial: producing a single reliable "logical qubit" capable of sustained computation may require thousands of physical qubits to monitor and correct.
The significance of Google's Willow chip — beyond the headline benchmark — is that it achieved something researchers had been seeking for years: exponential error reduction as the system scales up. In previous quantum systems, adding more qubits tended to add more errors. Willow demonstrated that errors could be suppressed faster than they were introduced as the chip grew, crossing what engineers call the quantum error correction threshold. That is a genuine milestone on the path toward fault-tolerant quantum computing — the point at which a quantum computer can reliably run long, complex calculations without the errors overwhelming the result.
IBM's quantum programme is pursuing a parallel track. The company unveiled Condor in late 2023 — the world's first processor to exceed 1,000 qubits at 1,121 — and has maintained a public roadmap targeting fault-tolerant computing by the end of the decade. In 2025, Microsoft introduced its Majorana 1 chip, built on a fundamentally different architectural approach using topological qubits, which the company believes could eventually allow a million qubits on a single chip — though the approach remains less proven than Google and IBM's superconducting architectures.
By 2025, Google had demonstrated its Quantum Echoes algorithm achieving 13,000 times the speed of a classical supercomputer on a specific task in a verifiable, repeatable experiment — the first time the company used the phrase "verifiable quantum advantage" with confidence. The real-world applications, most researchers estimate, will begin to arrive in the second half of the 2030s.
What Quantum Computers Will Be Good At
The applications that quantum computing's architecture uniquely suits share a common feature: they involve exploring enormous spaces of possibilities where the interactions between components cannot be simplified without losing essential accuracy.
Drug discovery and molecular simulation
Drug discovery is currently among the most expensive and slow processes in modern science. Bringing a single new drug to market can cost more than $1 billion and take over a decade, largely because predicting how molecular compounds will behave inside the human body requires tracking quantum interactions between thousands of atoms simultaneously — a task that overwhelms classical supercomputers.
Quantum computers, which operate at the quantum mechanical level by nature, could simulate these interactions with near-perfect accuracy. Researchers at pharmaceutical companies and academic institutions are already partnering with quantum computing firms to model proteins linked to Alzheimer's disease, antibiotic-resistant bacteria, and specific cancer mutations. A 2025 experiment by Google using Willow in collaboration with UC Berkeley produced results aligned with classical methods in simulating two molecules — a small but meaningful step toward practical quantum chemistry.
Materials science and climate technology
The climate crisis demands solutions at a pace and scale that classical computing struggles to match. Quantum processors could model the electronic structure of materials with extraordinary fidelity, accelerating the discovery of new battery chemistries, more efficient solar cells, and — most ambitiously — room-temperature superconductors. A superconductor that functions at room temperature would transform power transmission, eliminating the energy losses that currently occur when electricity travels through conventional wires, and make magnetic levitation technologies commercially viable.
These are not speculative distant possibilities. Quantum advantage in materials-related calculations has already been demonstrated in limited contexts. The question is scaling those demonstrations to problems of practical size and complexity.
Optimisation and logistics
Many of the most economically significant problems in business and science are optimisation problems: finding the best route through a network, the optimal allocation of resources, the most efficient configuration of a complex system. Classical computers can find good approximate solutions to many of these problems, but finding the provably optimal solution often requires computational resources that grow exponentially with problem size. Quantum algorithms offer a potential path to better solutions in shorter time for specific classes of these problems — with implications for supply chains, financial modelling, and energy grid management.
The Cryptography Crisis That Is Already Here
While the transformative applications of quantum computing lie in the future, one implication is already urgent: the threat to current encryption.
Most digital security infrastructure — the encryption protecting online banking, government communications, medical records, and internet traffic — relies on mathematical problems that classical computers cannot efficiently solve, such as factoring very large numbers. A sufficiently large, fault-tolerant quantum computer running an algorithm known as Shor's algorithm could solve these problems rapidly, rendering current encryption vulnerable.
Security researchers are already documenting a threat called "harvest now, decrypt later" — in which adversaries collect and store encrypted data today, planning to decrypt it once quantum computers are capable enough. Sensitive communications encrypted today with the assumption that they are secure could be vulnerable in a decade or two.
In recognition of this, the National Institute of Standards and Technology (NIST) published the first official post-quantum cryptography standards in August 2024 — algorithms designed to resist quantum attacks. NIST has recommended that federal agencies transition away from classical encryption by 2035. Security experts describe the migration as one of the largest and most complex infrastructure transitions in the history of computing — comparable to the transition to internet-based communication, but with a harder deadline.
The Google Quantum AI team has been involved in developing and testing post-quantum cryptographic algorithms alongside its hardware work. Whether the broader internet will complete the necessary migration before quantum computers capable of breaking current encryption arrive is one of the defining security questions of the next decade.
The Geopolitical Race
The development of quantum computing has become a matter of national strategic priority in a way that few technologies have in recent decades.
The United States, China, the European Union, the United Kingdom, and several other nations have committed billions to national quantum strategies, recognising that the country or alliance that achieves practical, fault-tolerant quantum computing first will hold a significant advantage across defence, intelligence, scientific research, and economic competitiveness. China has invested heavily in quantum communication networks and satellite-based quantum key distribution. The EU's Quantum Flagship programme has committed €1 billion to quantum research across member states. The US has the CHIPS and Science Act and a range of defence-related quantum programmes.
The competition is fierce, and the most consequential prize is not necessarily the fastest quantum computer — it is the first quantum computer capable of breaking current encryption standards at scale. For intelligence agencies, that capability would represent an unprecedented ability to access adversaries' historical communications. The strategic implications are significant enough that some security experts describe the race to quantum computing as the most consequential technological competition since the development of nuclear weapons.
What Is Actually Known, and What Remains Uncertain
Intellectual honesty about quantum computing requires distinguishing clearly between what the evidence currently supports and what remains projection.
What is established: Quantum computers can perform certain specific tasks dramatically faster than classical systems. The error correction threshold has been crossed. Progress in qubit quality and count is accelerating. Post-quantum cryptography standards exist and the migration is underway.
What remains uncertain: When exactly commercially relevant quantum advantage will arrive for real-world applications. Which architectural approach — superconducting, topological, neutral atom, photonic — will prove most practical at scale. Whether the engineering challenges of error correction can be solved cost-effectively at the scale required for transformative applications. How quickly current encryption infrastructure can be upgraded to quantum-resistant standards before the threat materialises.
The honest estimate from researchers not affiliated with companies with market incentives to oversell progress is that practically useful quantum computing for drug discovery, materials science, and similar applications will arrive in the second half of the 2030s under current roadmaps. That is not far away. It is also not tomorrow.
A Different Kind of Computing Future
The significance of quantum computing is not that it will replace classical computers. It will not. Classical computers will remain the right tool for most of what computers currently do — they are extraordinarily good at deterministic, sequential processing, and quantum systems offer no advantage for those tasks.
The significance is that quantum computing makes soluble a class of problems that classical computing leaves genuinely intractable. The simulation of molecular interactions at quantum mechanical accuracy. The modelling of complex systems where all components interact simultaneously. The search through exponentially large spaces for optimal solutions.
These are precisely the problems that sit at the frontier of drug discovery, materials science, climate modelling, and fundamental physics. The arrival of a machine that can address them at scale would not merely accelerate existing science — it would open categories of investigation that current tools cannot approach.
The quantum revolution is not a distant promise. It is an unfolding development, moving from landmark demonstrations to architectural breakthroughs at a pace that surprises even the researchers building it. The question is not whether it will change science and security. It is whether the world will be ready for the changes when they arrive.
What application of quantum computing do you find most significant or most concerning? Share your perspective in the comments below.