AI advancements in chip design, led by researchers from Princeton and IIT Madras, employ a deep-learning method that enables "inverse design," focusing on desired properties rather than traditional templates. This approach produces effective yet complex circuits, particularly for wireless applications, but raises concerns about transparency and understanding. While it enhances engineering productivity, the reliance on AI may pose risks, especially in critical systems, and could diminish human expertise in design.
