Empowering DTCO Innovation with AI and Machine Learning - Popular Science

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As Moore's Law faces the daunting challenge of slowing down, the semiconductor industry is in urgent need of a new breakthrough. This book was written specifically to address the "efficiency black hole" that costs the industry tens of billions of dollars annually.

《AI and Machine Learning-Powered DTCO: Synergizing Chip Design and Manufacturing》 provides readers with a practical DTCO.ML framework. It demonstrates how to leverage Machine Learning (ML) and Generative AI (GenAI) to inject new momentum into the fabrication process. By mastering process variability and optimizing chip power efficiency, companies can finally break free from the time-consuming and expensive cycle of physical tape-out trial and error.

What You Will Achieve:

• Predictive Yield: Shift from trial-and-error to data-driven, Accelerated ROI.
• Energy Efficiency: Realize significant power breakthroughs in every iteration.
• Market Leadership: Gain a critical Time-to-Market (TTM) advantage of several months.

Whether you are a chip design engineer looking to boost productivity, a process R&D expert, or a manager seeking a "re-acceleration" strategy for the industry, this book provides a proven, AI-powered blueprint for execution.

The future of DTCO starts here!

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About the Author

Dr. Hock Chen (陳世豪) CEO, DigWise Technology

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Dr. Hock Chen is a pioneer in applying Machine Learning and Generative AI (GenAI) to semiconductor process optimization. Previously the CEO of DipSci Technology, he focused on leveraging ML to enhance chip manufacturing monitoring and production efficiency.

His core research centers on the application of GenAI in chip design, low-power optimization, and Design-Technology Co-Optimization (DTCO). Dr. Chen earned his Ph.D. in Computer Science from National Tsing Hua University in 2012.

You are currently reading a free trial of this book. To fully explore the content, examples, and techniques, please purchase the full version.