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Small-scale quantum computers can enhance machine learning performance, as shown in an experimental study using a photonic ...
MIT and NVIDIA researchers created a GPU-accelerated algorithm that lets robots plan complex tasks in seconds, boosting industrial efficiency.
MLCommons' AI training tests show that the more chips you have, the more critical the network that's between them.
If data used to train artificial intelligence models for medical applications, such as hospitals across the Greater Toronto ...
Quantum computing has the potential to transform the aerospace sector by tackling complex challenges that classical systems cannot address. This white paper exp ...
Computer Interfaces (BCIs), Deep Brain Stimulation (DBS), Neuroadaptive Algorithms de Lima Dias, R. (2025) The Hybrid Mind in ...
This paper introduces a data-oriented, machine learning-enhanced approach to achieve massively parallel EMT simulation on CPU-GPU ... via artificial neural networks and integrates these models using a ...
We use CMake because the autohecbench.py was giving us trouble ... We encourage writing the results of the execution to a log file for later error/execution analysis. Once all the roofline ...
Speed and agility are key when building a competitive advantage, and many organizations are using AI to get there ... back-end APIs, machine learning algorithms or data pipelines.
With biomedical data collected by Sleuth Insights, researchers helped sculpt a version of OpenAI’s o3-mini model using scientific ... he’s worked in the machine learning field for years ...
More information: Ji Huang et al, NUE regulons conserved model-to-crop enhance machine learning predictions of nitrogen use efficiency, The Plant Cell (2025). DOI: 10.1093/plcell/koaf093 ...