Nature

Large language models versus classical machine learning performance in COVID-19 mortality prediction using high-dimensional tabular data

This study compared the performance of classical feature-based machine learning models (CMLs) and large language models (LLMs) in predicting COVID-19 mortality using high-dimensional tabular data from ...
Nature

DECIPHER for learning disentangled cellular embeddings in large-scale heterogeneous spatial omics data

The functional role of a cell, shaped by the sophisticated interplay between its molecular identity and spatial context, is often obscured in current spatial modeling. In efforts to model large-scale ...
VentureBeat

Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...