# Why Full-Fledged Quantum Computers Might Always Be Five Years Away
The timeline for practical quantum computing remains perpetually distant because researchers and industry leaders lack consensus on what constitutes a "useful" quantum computer, writes Karmela Padavic-Callaghan in New Scientist.
The problem sits at the intersection of engineering ambition and moving goalposts. Companies like IBM, Google, and IonQ have built machines with dozens to hundreds of qubits, yet none solves real-world problems faster than classical computers. Each vendor defines success differently. Some measure progress by qubit count alone. Others focus on "quantum volume," a metric combining qubit quality and connectivity. Still others emphasize error correction, the ability to fix quantum errors that currently plague all devices.
This definitional vagueness allows companies to claim progress while sidestepping harder questions. Quantum computers excel at specific tasks—simulating molecular behavior, optimizing routes, breaking encryption—but predicting when they'll outperform conventional machines depends entirely on how you frame the benchmark.
The five-year prediction recurs in quantum computing like clockwork. In 2018, researchers said five years. In 2023, they said five years. This pattern suggests the goalpost shifts as capabilities improve but unexpected obstacles emerge. Quantum decoherence, where qubits lose information, remains a stubborn engineering challenge. Scaling from dozens of qubits to millions while maintaining error rates below critical thresholds demands breakthroughs nobody has delivered.
Padavic-Callaghan argues the field needs clearer definitions. Without them, investors, policymakers, and researchers cannot honestly assess progress. The distinction between "quantum advantage" (solving something faster than classical methods, however niche) and "practical quantum computing" (solving problems that matter to industry or science) gets blurred