ARTIFICIAL INTELLIGENCE
value of Humanoid robotics. Autonomous systems become more efficient and instead of sending data to a central brain, intelligence moves into the system itself. Whether it’s a hand, or a drone, this change reduces latency and power and increases robustness.
“Sensing itself is becoming AI.” What does this mean?
This is the most important shift. Today, sensing and computing are separate. In biology, they are one and the same. Sensing is the “exposed nervous system.” The line between sensing and computing is blurring, as the two systems speak the same language: a sparse, event-driven neural representation.
This leads to a new model, where sensing is no longer passive, but becomes active, extracting meaning at the source. Basically, it’s “exposed, active AI”, with computation moving into the signal, and processing happening where the data is generated, vs. after it moves.
The brain does not have a sensor pipeline and then a compute pipeline. It is one system. Signals are processed as they are sensed. This is what we mean by: sensing is AI.
What role does neuromorphic computing play?
Neuromorphic computing rings three essential properties.
First, sparsity: only meaningful events are processed, reducing wasted computation. Second, event-driven operation, where AI reacts to changes, vs continuous streams. This is how our visual system works. We do not respond well to ‘uniformity’, for a very good
reason: we need to preserve precious power. Which brings to the next item. Third, ultra-low power: Neuromorphic systems can operate continuously at very low energy, enabling always-on intelligence. Neuromorphic is one of the Emergent Compute technologies (not the only one!) that allows AI to operate within the constraints of the physical world.
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JULY/AUGUST 2026 | ELECTRONICS FOR ENGINEERS 21
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