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Explore how merging Graph Machine Learning with Large Language Models creates Graph Foundation Models, enhancing our ability to analyze interconnected data for advanced applications in various domains.

In 2024 AI researchers have won the Nobel Prize in Physics and half of the Nobel Prize in Chemistry for pure AI research and applications.

New AI method learns from relationships, not data, using knowledge graphs to overcome scarce samples, improving predictions medicine, science, and engineering with human-like contextual understanding.

OpenClaw, an open-source AI agent project, and Moltbook, a bot-only social network, have surged in popularity since late 2025, attracting commentary from AI leaders.

Unmasking AI Text: Ghostbuster Technique Breakthrough! Berkeley scientists develop cutting-edge tool for authenticity verification, outperforming competitors and addressing ethical concerns.

Tired of AGI leaderboard illusions? A data scientist reveals the real test: can it invent Bitcoin in 2007, teach quantum physics in Swahili, and know when to ask for help?

Geometry-Informed Neural Networks (GINNs) transform shape generation by using geometric constraints and neural fields, enabling data-free training and diverse solutions across computer graphics, engineering, and medical imaging.

Internal embodiment, combining physical interaction and self-awareness of internal states, could improve safety and trustworthiness of future AI systems.

MIT has introduced Tyche, a pioneering framework for medical image segmentation that leverages stochastic learning to enhance diagnostic accuracy and reduce the need for retraining, transforming healthcare practices.

The ERA system developed by Google and Harvard researchers dramatically speeds up the creation of custom programs used in scientific research and outperforms human-written code.