Enabling Generative AI: Innovations and Challenges in Semiconductor Design Technologies
In recent years, Generative AI has transformed a wide range of domains, from everyday applications to cutting-edge scientific research. This rapid advancement has driven a substantial increase in the demand for computing, connectivity, communication, and memory/data storage across data centers, infrastructure, and edge devices. As a result, there has been a notable surge in industrial investment in “hard tech,” encompassing advanced materials, packaging, and semiconductor process technologies. These investments are aimed at developing next-generation hardware accelerators, both wired and wireless connectivity solutions, and heterogeneous integration at the chip and system levels, all underpinned by significant research and development efforts. In this paper, we will explore the latest technologies and address the challenges involved in creating high-performance computing and high-speed connectivity solutions, with a particular focus on energy efficiencies to enable Generative AI. We will also examine issues related to power distribution and other engineering complexities that arise in these advanced systems. Our discussion will highlight the critical role of technological challenges and innovations in ensuring the longterm sustainability and continued progress of these technologies in the decades ahead.
Authors
- K. Lawrence Loh
Institutions
- MediaTek (Taiwan) (TW)
Publication Details
- Published
- 2025-06-08
- DOI
- https://doi.org/10.23919/vlsitechnologyandcir65189.2025.11074926
- Citations
- 1
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.73