Light can compute functions during its propagation and interaction with structured materials, with high speed and low energy consumption. Achieving universal computing using all-optical neural networks requires optical activation layers with nonlinear dependence on input. However, the existing optical nonlinear materials are either slow or have very weak nonlinearity under the natural light intensity levels captured by a camera. Therefore, the design and development of new optical activation functions is essential for realizing optical neural networks that compute with ambient light.