Semiconductor Engineering

Multi-Core Architecture Optimized For Time-Predictable Neural Network Inference (FZI, KIT)

A new technical paper titled “MultiVic: A Time-Predictable RISC-V Multi-Core Processor Optimized for Neural Network Inference” was published by researchers at FZI Research Center for Information ...
eLife

Animacy semantic network supports causal inferences about illness

Inferring the causes of illness is a culturally universal example of causal thinking. We tested the hypothesis that making causal inferences about biological processes (e.g. illness) depends on the ...
unite

How Causal AI is Finally Building AI Models That Can Reason, Not Just React

For decades, artificial intelligence has excelled at spotting patterns in data. Machine learning models can predict customer behavior, forecast market trends, or identify medical risks with high ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...
Finextra

Graph Neural Networks and GraphRAG: Navigating Open-World Complexity in Finance

Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...
Semiconductor Engineering

How Neural Super Sampling Works: Architecture, Training, And Inference

This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...
IEEE

LineGRN: a line graph neural network for gene regulatory network inference

Abstract: Gene regulatory networks (GRNs) depicts the complex interactions between transcription factors and target genes, offering profound insight into deciphering the dynamics of cellular processes ...