Modern digital integrated circuits contain very large numbers of logic gates, and the conventional heuristics used in logic synthesis and netlist optimization struggle to explore the resulting design space efficiently. Artificial Intelligence (AI) and Machine Learning (ML) have therefore been investigated as complement...
VALERIO LARRYII PENULIAR· Zenodo (CERN European Organi...· 0 citations
This research explores how Artificial Intelligence can enhance the optimization of Arithmetic Logic Units (ALUs), which are crucial for processor speed, energy efficiency, and silicon area. Traditional ALU design relies on fixed architectures and rule-based heuristics, but the proposed framework integrates Graph Neural...
Jhon Rymr Agustin· Zenodo (CERN European Organi...· 0 citations
This research journal discusses how Artificial Intelligence (AI) and Machine Learning (ML) can enhance computer architecture design by addressing challenges in performance and energy efficiency. Traditional methods rely on expert intuition and exhaustive simulations, which are limited when exploring vast design spaces....
Marlyn Sto Domingo· Zenodo (CERN European Organi...· 0 citations
This research explores how Artificial Intelligence can enhance the optimization of Arithmetic Logic Units (ALUs), which are crucial for processor speed, energy efficiency, and silicon area. Traditional ALU design relies on fixed architectures and rule-based heuristics, but the proposed framework integrates Graph Neural...
Jhon Rymr Agustin· Zenodo (CERN European Organi...· 0 citations
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This research journal discusses how Artificial Intelligence (AI) and Machine Learning (ML) can enhance computer architecture design by addressing challenges in performance and energy efficiency. Traditional methods rely on expert intuition and exhaustive simulations, which are limited when exploring vast design spaces....
Marlyn Sto Domingo· Zenodo (CERN European Organi...· 0 citations
The union of Artificial Intelligence and the Internet of Things (IoT) is transforming the way Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM) systems are used in the Industry 4.0 production process. Based on the PRISMA 2020 reporting framework (Page et al., 2021), this report is a systematic literatu...
Madiba Krista Kundai, Madzimure Tatenda, Mafukidze Liberty et al.· World Journal of Advanced En...· 0 citations
Reproducibility package accompanying the manuscript Quantization fragility under image corruption is recipe-dependent: paired evidence from INT8 and FP8 object detectors, prepared for Neural Networks. The release contains analysis, pipeline, and validation code; frozen configurations and manifests; compact deterministi...
Duy Tan Nguyen, Lam Phuong Nguyen, Vinh Huy Nguyen et al.· Zenodo (CERN European Organi...· 0 citations
Understanding the relationship between phenotype and genotype is a central challenge of 21st century biology. Although rare, strong mutations allow for a direct understanding of this relationship, modern genetics is puzzled by the finding that complex traits are influenced by hundreds or thousands of variants, often wi...
Florin Philipp Ratajczak· Universitätsbibliothek der L...· 0 citations
The highly distributed infrastructure and the hetero geneous services and dynamic workloads of future 6G networks impose severe requirements on resource orchestration. We in troduce KG-Orchestrator, a unified framework which combines a Neo4j knowledge graph and a multi-GNN ensemble (Graph SAGE, HashGNN, GAT, GCN) to pe...
Debashish ROY, Alaa AlZailaa, Kostas Ramantas et al.· Zenodo (CERN European Organi...· 0 citations
The article deals with the development of principles for organizing centralized control for automatically restoring and optimizing the normal operation of power districts with distributed energy resources (DER). The aim of the study is to achieve more reliable operation of distribution power grids through making a shif...
Aleksandr KULIKOV, Lyudmila Gurina, Nikita Tomin· Elektrichestvo· 0 citations
Traditional programming assessments focus on correctness and efficiency and do not consider students' cognitive learning processes or code structure. Teachers then encounter challenges in providing effective feedback to facilitate cognitive learning in programming education. This study proposes a hybrid AI framework, A...
A. Sangeetha, B. Suthan, P. Vishaliney et al.· Journal of Multidisciplinary...· 0 citations
When edges are removed from a graph, do graph neural networks lose performance because they lose information, or because they lose specific structural signals? We study this with a controlled edge-removal probe. We sparsify graphs from 0% to 95% under three strategies: random removal, removal of cross-label (heterophil...
Aayush Pokhrel· Zenodo (CERN European Organi...· 0 citations
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
Microsoft Research Blog· microsoft.comJul 13, 2026
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduJul 6, 2026
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
