Epic signal! Wall Street whales are fully投入 into this "ultimate computing power" race, and by 2029, it could trigger a wealth tsunami rivaling $BTC!

At a recent closed-door investor meeting, the blue giant IBM clearly outlined the timeline for quantum computing. They believe the superconducting approach will win the race for universal quantum computing, setting two key milestones: achieving quantum advantage by 2026 and fault-tolerant computing by 2029. The latter they call the “ChatGPT moment” in the quantum realm.

A core technical leader from IBM Research pointed out that the industry has already entered the “practical stage.” Currently, systems with about 100 qubits and a two-qubit error rate close to one-thousandth have surpassed the simulation limits of classical computers.

The real breakthrough is expected in 2026. At that time, the next-generation processor codenamed “Nighthawk” will support a “clean, strict, and provable” quantum advantage. Market analysis indicates that recent breakthroughs in error rate control, system scalability, and integration with classical computing provide a realistic foundation for this timeline.

The technical leader emphasized that understanding “universal quantum computing” is essential when discussing quantum computing. It is not just simple binary bits but uses continuous quantum states to represent information, with the capacity growing exponentially with the number of qubits. IBM has chosen the superconducting route based on three key metrics: quality, scalability, and speed.

In terms of quality, the error rate of single qubits has dropped from one-tenth to one ten-thousandth over the past six years. Regarding scalability, superconducting qubits can be manufactured using mature lithography techniques, highly compatible with existing semiconductor production lines. In speed, their gate operation speeds are thousands of times faster than competitors like ion traps and neutral atoms.

He believes that the compatibility with semiconductor manufacturing and decades of microwave engineering experience give superconducting qubits a structural advantage that is hard to shake.

Currently, the core obstacle to scaling quantum processors has shifted from physical principles to engineering implementation. Major challenges include increasing control line density in cryogenic systems near absolute zero, managing thermal loads in extreme environments, maintaining performance uniformity and yield as qubit counts reach hundreds or thousands, and integrating control electronics capable of operating in extreme conditions.

These challenges are precisely where the semiconductor industry excels. IBM’s long-term expertise in lithography, materials engineering, cryogenics, and microwave control has paved the way for the commercialization of large-scale quantum processors.

IBM’s technology roadmap is divided into three phases. We are now in the “practical stage.” 2026 marks the first critical milestone, achieving quantum advantage with the Nighthawk processor. The company has even established a public “Quantum Advantage Tracker” to ensure transparency and verifiability of results.

2029 will be the real inflection point. By then, the system will achieve fault-tolerant quantum computing, with an estimated 200 logical qubits capable of executing around 100 million gate operations—four orders of magnitude higher than the current 5,000.

The technical leader clearly states that classical and quantum computing will coexist and collaborate in the long term, rather than one replacing the other. Classical computing remains irreplaceable for arithmetic operations, while quantum computing excels at problems like integer factorization, which are inefficient on classical computers.

A key insight is that quantum computing itself will generate new demands for classical computing power. Especially in future fault-tolerant systems, the decoding of error correction will consume significant classical resources. The next wave of innovation will come from hybrid quantum-classical algorithms, which impose strict requirements on communication latency between the two.

This also explains why IBM has recently partnered with companies like AMD, aiming to tightly couple classical and quantum computing as a unified computing stack.

At the application level, quantum advantage will first be realized in materials science and chemistry, as quantum mechanics is the fundamental language of these disciplines. Complex optimization problems in finance and logistics also hold great potential, as classical algorithms often face scalability barriers here.

IBM’s strategic focus is shifting from solving isolated problems to covering four core algorithm categories: dynamical systems and partial differential equations, Hamiltonian systems and linear algebra, combinatorial optimization, and stochastic processes. These algorithms form the backbone of enterprise-level critical computing.

The leader predicts that once fault-tolerant systems mature in 2029, they will trigger transformative breakthroughs in multi-objective optimization across finance, logistics, and energy sectors, comparable to the emergence of ChatGPT. Subsequently, fields like engineering materials, chemistry, and drug discovery will experience deeper revolutions.

For the computing power market, this means a wave of new, massive demand is brewing. It’s not just about the quantum processors themselves but also the vast classical infrastructure supporting their operation and the new computing paradigms emerging from the deep integration of both.