The biggest U.S. tech companies – IBM, Google, Amazon, Microsoft, and others – are in a fierce race to move quantum computers from lab prototypes to fully operational industrial machines. Thanks to advances in chip design and error correction methods, their timelines are now converging toward an ambitious goal: a functional quantum computer before the end of this decade.

IBM and Google Expect a Breakthrough by 2030

In June, IBM unveiled the complete design of its future quantum system. Jay Gambetta, head of IBM’s quantum program, said the company now has a “clear path” to building a machine capable of outperforming classical computers in tasks such as material simulations and AI modeling – potentially before 2030.

Google, for its part, claims to have removed one of the biggest technical obstacles, and according to quantum lead Julian Kelly, the remaining challenges are “surmountable.” The company believes it will achieve the desired results by the end of the decade.

Scaling – the Number One Challenge

The main obstacle remains scaling the number of qubits – the basic building blocks of quantum computers – from today’s hundreds to over one million. This leap is essential for the machines to deliver truly groundbreaking performance.

Currently, qubits can only remain in a stable state for fractions of a second. IBM’s 433-qubit Condor chip, for example, suffered from interference between components. However, the company says it has addressed this by using a different type of coupler.

Google is focusing on cutting manufacturing costs by a factor of ten and on developing an error correction method that improves as the system grows – without it, Kelly warns, the result would be “a very expensive machine that produces noise.”

Different Approaches, Same Goal

IBM is betting on a low-density parity code, which it says requires 90% fewer qubits than the popular Surface code used by Google. The Surface code links each qubit to its neighbors, but for practical use it would require more than a million qubits.

Beyond that, engineers must solve physical challenges such as simplifying wiring, connecting multiple chips into modules, and building larger cryogenic refrigerators to keep systems near absolute zero.

Searching for the Ideal Technology

IBM and Google are working with superconducting qubits, which offer fast progress but are hard to control. Alternative technologies – trapped ions, neutral atoms, and photons – are more stable but slower and harder to integrate into large-scale systems.

According to Sebastian Weidt of the UK’s Universal Quantum, government funding decisions will likely narrow the field to a few contenders. The U.S. Pentagon’s DARPA has already launched a project to identify the fastest route to a practical system.

Amazon and Microsoft are experimenting with new types of qubits, including exotic states of matter, while established players continue refining older technologies. As analyst Mark Horvath sums it up: “Just because it’s hard doesn’t mean it’s impossible.”

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