Physna is licensing API access to its Physical AI search and normalization engine for a cohort of AI labs, OEMs, ...
That’s not to say that the technology doesn’t have a function or won’t improve, but it does place a much lower ceiling on ...
Deep neural networks (DNNs) have become a cornerstone of modern AI technology, driving a thriving field of research in ...
Bias in AI isn’t just baked into the training data; it’s shaped by us and embedded in the broader ecosystem of human-AI ...
Quantum systems can simulate molecular interactions at a level of fidelity that classical computers cannot achieve. They can ...
X-ray tomography is a powerful tool that enables scientists and engineers to peer inside of objects in 3D, including computer ...
Abstract: This study presents a comprehensive survey on Quantum Machine Learning (QML) along with its current status, challenges, and perspectives. QML combines quantum computing and machine learning ...
Abstract: One of the prominent challenges encountered in real-world data is an imbalance, characterized by unequal distribution of observations across different target classes, which complicates ...
Today's AI agents don't meet the definition of true agents. Key missing elements are reinforcement learning and complex memory. It will take at least five years to get AI agents where they need to be.
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