Newsroom

Stay updated with the latest news, press releases, and announcements from QuadaptAI as we revolutionize semiconductor failure analysis.

Latest News

Recent developments, achievements, and milestones in our journey to transform semiconductor failure analysis with autonomous AI.

December 15, 2024

QuadaptAI Achieves 91.7% Accuracy in Failure Analysis

Our autonomous AI system has achieved breakthrough performance, surpassing human expert accuracy by 9.6% while reducing analysis time from hours to minutes.

Breakthrough Performance AI
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November 28, 2024

Partnership with STMicroelectronics Announced

QuadaptAI has entered into a strategic partnership with STMicroelectronics to deploy our autonomous failure analysis technology across their manufacturing facilities.

Partnership STMicroelectronics Deployment
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August 20, 2024

Research Paper Published in Nature Electronics

Our groundbreaking research on adaptive transformer architectures for failure analysis has been published in the prestigious Nature Electronics journal.

Research Publication Nature
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Press Releases

Official announcements and media communications

QuadaptAI Announces Breakthrough in Autonomous Failure Analysis

Paris, France - QuadaptAI today announced a major breakthrough in autonomous semiconductor failure analysis, achieving unprecedented accuracy and speed improvements.

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Strategic Partnership with Leading Semiconductor Manufacturer

QuadaptAI has entered into a strategic partnership with a major semiconductor manufacturer to deploy autonomous failure analysis technology across their global operations.

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Recent Publications

Latest research papers and technical publications

Big GCVAE: Decision-making with Adaptive Transformer

Ezukwoke, K., et al.
Journal of Intelligent Manufacturing (2024)

Advanced decision-making framework using adaptive transformers for semiconductor failure analysis with improved accuracy and efficiency.

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Leveraging Pre-trained Models for Failure Analysis

Ezukwoke, K., et al.
arXiv preprint (2022)

Novel approach using pre-trained models for efficient failure analysis triplet generation and pattern recognition.

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Root Cause Prediction with Genetic Algorithm-ML

Rammal, A., et al.
Scientific Reports (2023)

Hybrid approach combining genetic algorithms with machine learning for accurate root cause analysis in semiconductor manufacturing.

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NLP and Association Rules for Intelligent Fault Analysis

Wang, Z., et al.
Journal of Intelligent Manufacturing (2023)

Advanced natural language processing techniques combined with association rules for intelligent fault analysis and pattern recognition.

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