A new brain-mimicking computer chip can train on complex data in milliseconds, a task that takes standard GPUs several hours.

The MARS reservoir computing architecture outperforms top-tier models like Mamba while using a fraction of the power. This system uses memristive hardware to mimic the way biological brains process time-series data. It bypasses the gradient descent bottleneck that makes current AI training so slow and expensive. The results show that we can achieve state-of-the-art performance on hardware that is orders of magnitude more efficient. This path toward neuromorphic computing could bring powerful AI to tiny, battery-operated devices.