Technical SEO for generative search: Optimizing for AI agents

Control how AI bots access your site, structure content for extraction, and improve your chances of being cited in ...
XDA Developers on MSN

TurboQuant tackles the hidden memory problem that's been limiting your local LLMs

A paper from Google could make local LLMs even easier to run.
Morning Overview on MSN

Google’s TurboQuant claims 6x lower memory use for large AI models

Google researchers have proposed TurboQuant, a method for compressing the key-value caches that large language models rely on ...

IndexCache, a new sparse attention optimizer, delivers 1.82x faster inference on long-context AI models

Researchers at Tsinghua University and Z.ai built IndexCache to eliminate redundant computation in sparse attention models ...
IEEE

Model Predictive Control Enabled UAV Trajectory Optimization and Secure Resource Allocation

Abstract: In this paper, we investigate a secure communication architecture based on unmanned aerial vehicle (UAV), which enhances the security performance of the communication system through UAV ...
IEEE

Multi-Sized AI Models Assisted Low-Altitude UAV Delivery With RAN Optimization

Abstract: With the development of Artificial Intelligence (AI) technology and wireless communication technology, Uncrewed Aerial Vehicles (UAVs)-based low-altitude applications have become ...
Microsoft

ARO: A New Lens On Matrix Optimization For Large Models

Matrix-based optimizers have attracted growing interest for improving LLM training efficiency, with significant progress centered on orthogonalization/whitening based methods. While yielding ...