Robots and self-driving cars could soon benefit from a new kind of brain-inspired hardware that can allegedly detect movement and react faster than a human. A new study published in the journal Nature Communications details how an international team built their neuromorphic temporal-attention hardware system to speed up automated driving decisions.
The problem with current robotic vision and self-driving vehicles is a significant delay in processing what they see. While today’s top AI programs can recognize objects accurately, the calculations are so complex that they can take up to half a second to complete. That may not sound like a lot, but at highway speeds, even a one-second delay means a car travels 27 meters before it even begins to react. That is too long and too slow a reaction time.
To solve this problem, the team worked on a hardware solution rather than tinkering with software, modeling it on how human vision works. When we view a situation, our visual system doesn’t analyze every detail at once. It first detects changes in brightness and movement, then processes the more complex details later.









