Machine learning methodologies encompass algorithmic frameworks and architectures for training, optimizing, and deploying models such as neural networks, transformers, diffusion models, and reinforcement learning agents. Work in this area develops new training objectives, curriculum schemes, speculative and efficient decoding, pruning and communication-reduction strategies, and biologically inspired or physics-informed architectures. The domain also includes safety preservation, unlearning, scaling laws, and specialized methods for vision, language, control, and scientific computing, aiming to improve performance, efficiency, robustness, and controllability of complex AI systems.
Computer Sciences
Most contemporary artificial intelligence (AI) systems learn to complete tasks via machine learning and deep learning. Machine learning is a computational approach that allows models to uncover patterns in data that are useful ...
Energy & Green Tech
Due to the explosive growth of artificial intelligence, it is estimated that data centers will consume up to 12% of total U.S. electricity by 2028, according to the Lawrence Berkeley National Laboratory. Improving data center ...
Apr 27, 2026
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Business
Generative AI is best known for creating images and text. Now, it is helping industries make better planning decisions. Georgia Tech researchers have created a new AI model for decision-focused learning (DFL), called Diffusion-DFL. ...
Apr 22, 2026
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Machine learning & AI
Researchers used the world's fastest supercomputer for open science to train an artificial intelligence model that captures magnetic turbulence within a plasma in unprecedented detail. Results from the model, trained on the ...
Apr 20, 2026
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Machine learning & AI
Artificial intelligence is becoming increasingly important in nearly every aspect of society, but is completely dominated by the United States and China. Leaving the field to foreign powers and large companies may entail ...
Apr 15, 2026
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Security
With the rapid spread of digital content, doctored videos pose growing risks across media, security, and legal domains. A new study published in The Journal of Engineering Research introduces an automated approach to detect ...
Apr 14, 2026
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Computer Sciences
Researchers have demonstrated a new training technique that significantly improves the accuracy of graph neural networks (GNNs)—AI systems used in applications from drug discovery to weather forecasting. GNNs are AI systems ...
Apr 13, 2026
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Computer Sciences
There is an exciting future on the horizon—one in which your thoughts could directly control electronic devices you use every day. In many ways, that future is already here, enabled by neural interfaces—engineered devices ...
Apr 12, 2026
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Computer Sciences
In a recent paper, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and co-author William Gilpin show that a deceptively simple forecasting strategy can outperform several leading machine learning forecasting models.
Apr 10, 2026
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Computer Sciences
Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational resources. Traditionally, obtaining a smaller, faster model either requires training a massive one first ...
Apr 9, 2026
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