I tested local AI on my M1 Mac, expecting magic - and got a reality check instead

At random, I chose glm-4.7-flash, from the Chinese AI startup Z.ai. Weighing in at 30 billion "parameters," or neural weights, GLM-4.7-flash would be a "small" large language model by today's ...
Tech Xplore

Geometry behind how AI agents learn revealed

A new study from the University at Albany shows that artificial intelligence systems may organize information in far more ...
The Lancet

CARDBiomedBench: a benchmark for evaluating the performance of large language models in biomedical research

Although large language models (LLMs) have the potential to transform biomedical research, their ability to reason accurately across complex, data-rich domains remains unproven. To address this ...
GitHub

SCFlow: Implicitly Learning Style and Content Disentanglement with Flow Models

This repository contains the official implementation of the paper "SCFlow: Implicitly Learning Style and Content Disentanglement with Flow Models". We proposed a flow-matching framework that learns an ...
Tech Xplore

Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...
GitHub

TesserAct: Learning 4D Embodied World Models

We propose TesserAct, the first open-source and generalized 4D World Model for robotics, which takes input images and text instructions to generate RGB, depth, and normal videos, reconstructing a 4D ...
IEEE

Quantum Machine Learning: Recent Advances, Challenges, and Perspectives

Abstract: This study presents a comprehensive survey on Quantum Machine Learning (QML) along with its current status, challenges, and perspectives. QML combines quantum computing and machine learning ...
IEEE

LYRICEL: Knowledge Graphs Combined With Large Language Models and Machine Learning for Cross-Cultural Analysis of Lyrics—The Case of Greek Songs

Abstract: This paper presents LYRICEL, a framework integrating Knowledge Graph (KG) representation learning, Large Language Models (LLMs), and machine learning for reliable, explainable, and ...