New AI “copilot” helps engineers design better structures
The system asks humans for feedback to increase trust in machine-generated designs for buildings and bridges.
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Advancing science & engineering with Antigravity’s /teamwork
Education Innovation
XYBench: Helping with the problem behind the question
Helping robots fit into the human workplace
Founded by Anthony Jules ’92, SM ’92 and Professor Emeritus Rodney Brooks, Robust AI’s robots are designed to collaborate with humans in factories and warehouses.
Microsoft Research Focus – Edition #98
What's new in research at Microsoft? Host Anson Ho explores the latest, including AI-powered universal translation, a breakthrough in a 31-year-old mathematics challenge, and advances making AI coding agents faster and more efficient. The post Microsoft Research Focus – Edition #98 appeared first on Microsoft Research.
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Anomaly detection in smart power grids with graph-regularized MS-SVDD: a multimodal subspace learning approach
A generalized Multimodal Subspace Support Vector Data Description model with graph-embedded regularization is proposed, illustrating how relational and structural information can be systematically embedded into one-class models, enabling robust learning under complex, high-dimensional, and multimodal conditions.
The Post-Economic Human: Artificial Intelligence, Ontological Displacement, and the Ideological Foundations of Future Conflict
Artificial intelligence is usually analysed as a productivity technology, a labour-market shock, or a governance problem. This article argues that its deeper political significance may arise from a fourth channel: ontological displacement. Ontological displacement occurs when a technology weakens the socially recognise...
ProphDR: An Interpretable Deep Learning Model for Predicting Cancer Drug Response via Multi-Omics and Cross-Attention Mechanisms
ProphDR is an interpretable deep learning framework that integrates multiomics data and drug structural information using a hierarchical attention mechanism, and generates biologically interpretable attention maps that highlight key pharmacophores and resistance-related genes consistent with established mechanisms in N...
Hermeneutic Sovereignty under Generative AI: A Humanities Framework for Protecting Human Meaning-Making from Interpretive Foreclosure
A person-centred framework of hermeneutic sovereignty for generative AI is developed and concludes that trustworthy AI must preserve not only a human role in decisions, but a meaningful human standing in the production of the interpretations on which decisions depend.