One year after unveiling a first-of-its-kind “microwave brain” microchip capable of computing on ultrafast data and wireless signals, researchers from the Cornell Duffield College of Engineering have shown how the chip can encode information into its own language.

The work builds on the world’s first integrated microwave neural network designed by Bal Govind, Ph.D., and experimentally demonstrated with Maxwell Anderson. Together, they showed that the low-power chip could harness the physics of microwaves to emulate the brain’s pattern-finding abilities and perform computations almost instantaneously.

In a new study published in Nature Communications, the researchers found that the device can now use what they describe as microwave token embeddings—similar to the tokens used in large language models—to encode messages into radio signals and compress data, capabilities that could enable faster, more secure communications for satellites, drones and other technologies.