The rise of AI has created an almost insatiable appetite for computing power. Training and running AI systems requires vast numbers of transistors, and engineers are now racing to pack more of them onto every chip. With their existing designs, however, silicon transistors are rapidly running up against physical limits on how small they can get.

Through new research published in Nature, a team led by Ya-Ping Chiu at National Taiwan University has uncovered new details about next-generation transistors that could help push past these limits.