Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding

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 ...
InfoWorld

Multi-token prediction technique triples LLM inference speed without auxiliary draft models

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.
Hackaday

Calculus By Oscilloscope

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 ...