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.

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 ...
Scientific American

This mathematician proved a brilliant theorem to justify his social awkwardness

George Pólya’s random walk theorem absolved him of being a lurker and revealed how the laws of chance interact with physical ...
IEEE

Demonstration of a Clock Distribution Method using Switching Matrices and a Two-Phase Clock Signal on an FPGA

Abstract: Very large-scale Integrations (VLSIs) are vulnerable to radiation, and VLSIs used in high radiation environments such as space environment and nuclear power plants have a short lifetime.
IEEE

Findings of Mega: Math explanation with LLMs using the socratic method for active learning

Abstract: This article presents an intervention study on the effects of the combined methods of 1) the Socratic method, 2) chain-of-thought (CoT) reasoning, 3) simplified gamification, and 4) ...
GitHub

Better Math in Callouts & Blockquotes

This is an Obsidian.md plugin to add better Live Preview support for math rendering inside callouts & blockquotes. Note: The feature of this plugin was originally a part of LaTeX-like Theorem & ...