The text provides a comprehensive and forward-looking exploration of the integration between low-power CMOS VLSI design and cutting-edge technologies such as artificial intelligence and machine learning.

• Explores how artificial intelligence techniques are revolutionizing VLSI design, focusing on optimizing low-power circuits and systems.
• Presents the latest advancements and research in both artificial intelligence and VLSI design, such as FinFET and nanosheet-based logic, analog integrated circuits design, and optimization with artificial intelligence.
• Offers perspectives on future trends and potential developments in the integration of artificial intelligence with VLSI design to reduce the complexity and time-consuming process of semiconductor IC design.
• Addresses techniques for achieving energy efficiency in both digital and analog components and presents future trends in low-power VLSI design.
• Discusses topics such as artificial intelligence-driven adaptive power management in VLSI design and neural networks in low-power VLSI architectures.

The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, microelectronics, VLSI design, artificial intelligence, computer science and engineering.

The text provides a comprehensive and forward-looking exploration of the integration between low-power CMOS VLSI design and cutting-edge technologies such as artificial intelligence and machine learning.

• Explores how artificial intelligence techniques are revolutionizing VLSI design, focusing on optimizing low-power circuits and systems.
• Presents the latest advancements and research in both artificial intelligence and VLSI design, such as FinFET and nanosheet-based logic, analog integrated circuits design, and optimization with artificial intelligence.
• Offers perspectives on future trends and potential developments in the integration of artificial intelligence with VLSI design to reduce the complexity and time-consuming process of semiconductor IC design.
• Addresses techniques for achieving energy efficiency in both digital and analog components and presents future trends in low-power VLSI design.
• Discusses topics such as artificial intelligence-driven adaptive power management in VLSI design and neural networks in low-power VLSI architectures.

The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, microelectronics, VLSI design, artificial intelligence, computer science and engineering.

The text provides a comprehensive and forward-looking exploration of the integration between low-power CMOS VLSI design and cutting-edge technologies such as artificial intelligence and machine learning.

• Explores how artificial intelligence techniques are revolutionizing VLSI design, focusing on optimizing low-power circuits and systems.
• Presents the latest advancements and research in both artificial intelligence and VLSI design, such as FinFET and nanosheet-based logic, analog integrated circuits design, and optimization with artificial intelligence.
• Offers perspectives on future trends and potential developments in the integration of artificial intelligence with VLSI design to reduce the complexity and time-consuming process of semiconductor IC design.
• Addresses techniques for achieving energy efficiency in both digital and analog components and presents future trends in low-power VLSI design.
• Discusses topics such as artificial intelligence-driven adaptive power management in VLSI design and neural networks in low-power VLSI architectures.

The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, microelectronics, VLSI design, artificial intelligence, computer science and engineering.