There has been some recent research showing that using human neuron based Brainoware is able to achieve a higher sample efficiency in some tasks compared to conventional ML techniques.

It is very difficult to keep these biological systems alive so it is difficult to directly compare sample efficiency (it is a lot cheaper to train a digital neural network compared to a physical one). However, it is possible that this biological hardware (and underlying algorithms) has such a significant advantage for some tasks that it will outperform digital AI with more research.

This market will resolve YES if research is published at any point within the next 10 years in which a biological neural network is trained to solve a learning problem which is not feasible to solve with the digital algorithms available at the time. To be clear I am referring to an "organoid reservoir" not a human or animal brain trained to complete a task. The organoid should be grown in a lab which ensures that it is not performing well based on previous life experience.