Unite.AI

Thinking Machines Lab Unveils Inkling, Its First Open-Weights Multimodal AI Model

Thinking Machines Lab has released Inkling, its first general-purpose artificial intelligence model, giving developers access ...

Thinking Machines open sources first multimodal language model, Inkling, focused on low cost and 'resistance to censorship'

An Apache 2.0 designation makes Inkling a true open-source foundation. This gives developers the legal freedom to download, ...
marktechpost

RAG-Anything Tutorial: Build a Multimodal Retrieval Pipeline for Text, Tables, Equations, and Images in Colab

In this tutorial, we build a RAG-Anything workflow and use it to explore how multimodal retrieval works across text, tables, equations, and images. We start by preparing the Colab environment, ...
IEEE

Social-Aware Multimodal Graph Learning for Micro-Video Popularity Prediction

Abstract: Micro-videos, characterized by their brief duration and rich multi-modal content, have become increasingly popular on digital platforms. Micro-Video Popularity Prediction (MVPP) is crucial ...
GitHub

ImmunoStruct enables multimodal deep learning for immunogenicity prediction

ImmunoStruct is a multimodal deep learning framework that integrates sequence, structural, and biochemical information to predict multi-allele class-I peptide-MHC immunogenicity. By leveraging ...
Journal of Medical Internet Research

Multimodal Integration in Health Care: Development With Applications in Disease Management

Multimodal fusion demonstrates accurate prediction of anti-HER2 therapy response (AUC 0.914). In ophthalmology, multimodal integration through the combination of genetic and imaging data facilitates ...
IEEE

Multi-Modal Self-Supervised Learning Algorithm-Based Product Recommendation

Abstract: With the rise of e-commerce, personalized recommendation algorithms have received much attention in recent years. Meanwhile, multimodal recommendation algorithms have become the next ...