👉 Flip engineering is a design strategy in neuromorphic computing that involves reversing the conventional architecture of artificial neural networks to enhance their efficiency and performance, particularly in mimicking biological neural systems. Instead of the typical feedforward or recurrent structures, flip engineering reorders layers so that the input data flows from the output layer to the input layer, or vice versa, depending on the specific application needs. This reversal can lead to more energy-efficient and faster processing, as it aligns better with the way biological neurons operate, where information typically propagates from one neuron to another in a unidirectional manner. By optimizing this data flow, flip engineering can improve the system's ability to handle complex tasks like pattern recognition and sensory processing while reducing computational overhead.
