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.
Engineering
To manage increasingly complex manufacturing systems, involving material flows across numerous transporters, machines, and storage locations, the semiconductors and display fabrication industries have implemented automated ...
Jul 22, 2025
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Computer Sciences
AI image generation—which relies on neural networks to create new images from a variety of inputs, including text prompts—is projected to become a billion-dollar industry by the end of this decade. Even with today's technology, ...
Jul 22, 2025
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Computer Sciences
What began as a Ph.D. project has grown into a website with 120,000 unique visitors each year. With the platform OpenML, researcher Jan van Rijn is contributing to open science, aiming to make machine learning more transparent, ...
Jul 21, 2025
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Machine learning & AI
In the race to develop AI that understands complex images like financial forecasts, medical diagrams and nutrition labels—essential for AI to operate independently in everyday settings—closed-source systems like ChatGPT ...
Jul 21, 2025
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Hardware
Large language models (LLMs) like BERT and GPT are driving major advances in artificial intelligence, but their size and complexity typically require powerful servers and cloud infrastructure. Running these models directly ...
Jul 21, 2025
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Computer Sciences
Diffusion models are widely used in many AI applications, but research on efficient inference-time scalability, particularly for reasoning and planning (known as System 2 abilities) has been lacking. In response, a research ...
Jul 21, 2025
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Machine learning & AI
Artificial intelligence is accelerating at breakneck speed, with larger models dominating the scene—more parameters, more data, more power. But here is the real question: Do we really need bigger to be better? We challenged ...
Consumer & Gadgets
Machine learning is an integral part of high-stakes decision-making in a broad swath of human-computer interactions. You apply for a job. You submit a loan application. Algorithms determine who advances and who is declined.
Jul 17, 2025
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Machine learning & AI
Just as people from different countries speak different languages, AI models also create various internal "languages"—a unique set of tokens understood only by each model. Until recently, there was no way for models developed ...
Jul 16, 2025
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Computer Sciences
Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and reasoning models like ChatGPT. The principle: during a training phase, the parameters of the network's ...
Jul 14, 2025
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