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 ...
ascopubs.org

Using a Longformer Large Language Model for Segmenting Unstructured Cancer Pathology Reports

Preoperative Maximum Standardized Uptake Value Emphasized in Explainable Machine Learning Model for Predicting the Risk of Recurrence in Resected Non–Small Cell Lung Cancer Many Natural Language ...
American Enterprise Institute

Using Large Language Models to Understand Ordinary Meanings in Legal Texts: Some Early Judicial and Scholarly Experiments

Courts and scholars are experimenting with artificial intelligence tools to help establish the ordinary meaning of words and phrases in statutes and contracts. A tone of cautious optimism—one ...
TweakTown

The iPhone 17 Pro can run a 400B parameter Large Language Model on-device by streaming weights from the SSD

While the speed remains impractical for daily use, this proof of concept demonstrates how new inference engines are ...
Officer

How Law Enforcement Is Using Large Language Models (LLMs)

Support for AI among public safety professionals rose to 90% in 2024, with agencies rapidly adopting large language models (LLMs) to streamline operations and improve engagement. LLMs are being used ...

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 ...
Defense One

For DOD, the future of large language models is smaller

The U.S. military is working on ways to get the power of cloud-based, big-data AI in tools that can run on local computers, draw upon more focused data sets, and remain safe from spying eyes, ...
IEEE Spectrum on MSN

Why are large language models so terrible at video games?

AI models code simple games, but struggle to play them ...
Semiconductor Engineering

Small Vs. Large Language Models

The proliferation of edge AI will require fundamental changes in language models and chip architectures to make inferencing and learning outside of AI data centers a viable option. The initial goal ...