From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...
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Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics
MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...
In 1854, London was struck by a devastating cholera outbreak. Public authorities responded using the best tools and scientific understanding available at the time.Disease was widely believed to spread ...
AI factories meet the computational capacity and power requirements of today’s machine-learning and generative AI workloads.
Larian Studios will no longer be using any AI or machine learning tools for concept art of writing in the upcoming 'Divinity' ...
Central Banking’s regtech and suptech interviews are in‑depth exploration of the pioneering work at central banks and ...
Many businesses are grappling with how to use artificial intelligence securely. There are major concerns regarding sensitive ...
One of the world’s top artificial intelligence researchers, who works in New Brunswick, is optimistic about what the future ...
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How do we make sure AI is fair, safe, and secure?
AI is ubiquitous now—from interpreting medical results to driving cars, not to mention answering every question under the sun ...
Knowledge representation is a fundamental aspect of AI, which allows machines to understand, think, and even make choices ...
From data analysis to pattern recognition: Here’s how Penn Medicine is using artificial intelligence
Across the University of Pennsylvania Health System, scientists are now using AI to enhance their understanding of biological systems and modern medicine.
For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...
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