Liver disease modelling: This liver model reconstructs the liver periportal region architecture, is able to model aspects of cholestatic liver injury and biliary fibrosis, and can show how ...

Although some cells are still missing, namely the endothelium and immune cells, the model captures with high precision the cellular and structural architecture of the liver's periportal area at the ...

D (highest level of safety integrity), integration of artificial intelligence (AI), and machine learning (ML) in automotive safety architecture. By addressing the unique challenges presented by ...

a model balancer can intelligently switch between models based on the inputs coming. “As researchers working in the intersection of software architecture and ML, we are constantly trying to ...

How can ARBs continue to rely on presentations, spreadsheets, and manually created architecture diagrams as their primary communication tools when devops is well down the path of improving ...

“On-device training enables the model to adapt to new data collected from the sensors by fine-tuning a pre-trained model. However, the training memory consumption is prohibitive for IoT devices that ...

Transfusion uses a unified architecture and vocabulary to process mixed-modality inputs. The model includes lightweight modality-specific components that convert text tokens and image patches into ...

The technical report provides detailed insights into the architecture, training data, and innovative techniques used, such as knowledge distillation, to enhance model performance and Prompt ...

DRAM performance is critical for today's advanced AI/ML architectures due to requirements on efficiency of data movement, computation, AI model complexity, real-time inference and energy consumption.