Quantum computing has reached a pivotal moment where it's delivering practical advantages for artificial intelligence applications, according to recent breakthroughs from multiple research teams.
A team from the University of Vienna and collaborators has demonstrated that small-scale quantum computers can already outperform classical systems in specific machine learning tasks. Using a photonic quantum processor, researchers showed that quantum-enhanced algorithms can classify data more accurately than conventional methods. The experiment, published in Nature Photonics, employed a quantum circuit built at Politecnico di Milano to run a machine learning algorithm first proposed by Quantinuum researchers.
"This could prove crucial in the future, given that machine learning algorithms are becoming infeasible due to too high energy demands," noted co-author Iris Agresti. The photonic quantum platform showed advantages in speed, accuracy, and energy efficiency compared to classical computing techniques, particularly for kernel-based machine learning applications.
In a parallel breakthrough, a multinational team from Chalmers University of Technology, the University of Milan, the University of Granada, and the University of Tokyo developed an algorithm that allows ordinary computers to faithfully simulate a fault-tolerant quantum circuit. This innovation tackles the Gottesman-Kitaev-Preskill (GKP) bosonic code, which has been notoriously difficult to simulate but is crucial for building stable, scalable quantum computers.
Meanwhile, researchers from USC and Johns Hopkins University achieved what many consider the "holy grail" of quantum computing: an unconditional exponential speedup using IBM's 127-qubit Eagle processors. The team demonstrated this advantage on a classic "guess-the-pattern" puzzle, proving without assumptions that quantum machines can outpace the best classical computers. They employed techniques including error correction and IBM's powerful quantum hardware to achieve this milestone.
These developments signal that quantum computing is transitioning from theoretical promise to practical application. As IBM continues its ambitious roadmap toward a 4,000+ qubit system by 2025, and with researchers demonstrating quantum advantages in fields ranging from machine learning to semiconductor manufacturing, the technology appears poised to deliver transformative capabilities across multiple industries.