Black Forest Labs' new Self-Flow technique makes training multimodal AI models 2.8x more efficient

This efficiency makes it viable for enterprises to move beyond generic off-the-shelf solutions and develop specialized models ...
IEEE

Future of Breast Cancer Diagnosis: A Review of DL and ML Applications and Emerging Trends for Multimodal Data

Abstract: Breast cancer diagnosis has greatly benefited from the use of deep learning (DL) and machine learning (ML) methods on multimodal data, including mammography, magnetic resonance imaging (MRI) ...

Visual imitation learning: Guidde trains AI agents on human 'expert video' instead of documentation

Guidde already claims 4,500 enterprise customers and seeks to expand this number with its new round of funding.
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 ...
IEEE

Self-Supervised Learning for Multimodal Fault Diagnosis With Shapley-Value Weighted Transformers

Abstract: In recent years, there has been extensive exploration of intelligent fault diagnosis (IFD) methodologies. Nevertheless, there has been a paucity of prior research addressing the integration ...