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 ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

The computational demands of today’s AI systems are starting to outpace what classical hardware can deliver. How can we fix this? One possible solution is quantum machine learning (QML). QML ...

The quantum tangent kernel method is a mathematical approach used to understand how fast and how well quantum neural networks can learn. A quantum neural network is a machine learning model that runs ...

QTUM ETF tracks the BlueStar Quantum Computing and Machine Learning Index, holding 73 stocks in the quantum computing sector with a 0.40% expense ratio and 0.60% yield. The benchmark follows a passive ...

Overview Indian quantum computing companies are moving from academic research to enterprise adoption.IT leaders such as Tata Consultancy Services and startups l ...

QTUM ETF offers exposure to quantum computing and machine learning, but isn't a pure quantum play; it's a mix of tech, semiconductors, and some defense stocks. Despite dilution from non-core holdings, ...

Explore the future of the Quantum 2.0 market, set to expand from $3 billion in 2026 to over $50 billion by 2036, driven by quantum computing, sensing, and communications. This seismic technological ...