Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as weather patterns, recorded speech or stock market trends. Classical ...

Researchers at the University of Tokyo have identified a precise sweet spot where quantum reservoir computing, a machine learning approach that treats quantum systems as computational engines, reaches ...

Reservoir computing is suited for edge-AI use cases, such as signal processing, time-series forecasting, and pattern recognition, where rapid response and compact systems are essential. In this ...

Can a handful of atoms outperform a much larger digital neural network on a real-world task? The answer may be yes. In a study published in Physical Review Letters, a team led by Prof. Peng Xinhua and ...

HOBOKEN, N.J. , Nov. 17, 2025 /PRNewswire/ -- Quantum Computing Inc. ("QCi" or the "Company") (Nasdaq: QUBT), an innovative, integrated photonics and quantum optics technology company, today announced ...

Quantum reservoir computing has emerged as a promising machine learning paradigm for processing temporal data on near-term quantum devices, as it exploits the large computational capacity of qubits ...

Building on a long-standing MIT–IBM collaboration, the new lab will chart the convergence of AI, algorithms, and quantum computing The MIT-IBM Computing Research Lab builds on a distinguished history ...

Quantum machine learning algorithms have very recently attracted significant attention in photonic platforms. In particular, reconfigurable integrated photonic circuits offer a promising route, thanks ...