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As a new UN report declares a global water bankruptcy crisis, the AI industry's massive resource demands collide with Earth's limits, forcing a pivotal turn toward space-based infrastructure.

UC San Diego researchers create a computing device that mimics brain networks to combine memory and processing for faster and more energy-efficient performance.

Engineers at UC San Diego have created a better way to teach AI systems to handle tough problems mixing words and pictures, like math questions with charts.

Researchers introduce recursive language models that help AI handle very long texts without losing accuracy, using self-calls and code environments to break down and analyze information efficiently.

This innovation separates core logic from search methods in AI systems, making it easier to fix mistakes and improve performance without major code changes.

Penn State researchers develop a method called ZENN that helps artificial intelligence adapt to differences in data quality for better scientific discoveries.

Researchers embed AI models in radio waves to make edge computing more efficient and save energy on tiny gadgets.

KAIST develops SpecEdge to make large language models more affordable by using consumer-grade graphics processing units alongside data center ones, cutting expenses and improving access.

Researchers created a device that processes information like a brain by using charged particles, allowing small electronics to run powerful artificial intelligence programs while using much less electricity.

The startup introduces a probabilistic computer designed to run AI tasks with far less power than traditional systems.