AI confounds humans with improved chip designs

Described in Nature Communications, the wireless technology processors feature a combination of standard electronic circuits as well as electromagnetic structures including antennas, resonators, and signal splitters. Deep learning systems were tasked with creating new chips, resulting in strange designs featuring unusual patterns of circuitry, often with improved efficiency over existing chips. According to the researchers, the AI-created chip designs were unintuitive and unlikely to be developed by a human mind.

“We are coming up with structures that are complex and look random shaped and when connected with circuits, they create previously unachievable performance. Humans cannot really understand them, but they can work better,” said lead researcher Kaushik Sengupta, a professor of electrical and computer engineering and co-director of NextG, Princeton’s industry partnership programme for next-generation communications.

These circuits can be engineered towards more energy efficient operation or to make them operable across an enormous frequency range that is not currently possible. Furthermore, the  AI method synthesises inherently complex structures in minutes, while conventional algorithms may take weeks. In some cases, the new methodology can create structures that are impossible to synthesise with current techniques.