With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

A University of Hawaiʻi at Mānoa student-led team has developed a new algorithm to help scientists determine direction in ...

Neural encoding is the study of how neurons represent information with electrical activity (action potentials) at the level of individual cells or in networks of neurons. Studies of neural encoding ...

Even entry-level oscilloscopes today have simple math functions such as adding or subtracting two channels. But as [Arthur Pini] notes, more advanced scopes can now even do integration and ...

A recent study demonstrates the applicability of quantum computers for multi-objective optimization, bringing quantum computing a step closer towards practical applications. Knowledge gained by ...