The errors that quantum computers make are holding the technology back. But recent progress in quantum error correction has ...
As new large language models, or LLMs, are rapidly developed and deployed, existing methods for evaluating their safety and discovering potential vulnerabilities quickly become outdated. To identify ...
Those that solve artificially simplified problems where quantum advantage is meaningless. Those that provide no genuine quantum advantage when all costs are properly accounted for. This critique is ...
Abstract: Under the nearing error-corrected era of quantum computing, it is necessary to understand the suitability of certain post-NISQ algorithms for practical problems. One of the most promising, ...
Microsoft released new open-source quantum development tools, expanding the Quantum Development Kit. VS Code and GitHub Copilot now play a more central role in ...
A team of researchers from the University of Chicago's Pritzker School of Molecular Engineering (UChicago PME) has used Quantum Machine Learning (QML) to identify cancer early. Their innovative ...
We introduce DeepQuantum, an open-source, PyTorch-based software platform for quantum machine learning and photonic quantum computing. This AI-enhanced framework enables efficient design and execution ...
As AI and quantum collide, we get huge leaps in power — along with a scramble to secure our data, trust the results and brace for a fast-approaching Q-Day. In recent years, artificial intelligence (AI ...
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