Rebbelith explores the viability of quantum machine learning as a tool for coping with Radical Uncertainty by focussing on two key points:
1. Why finance and investing will not benefit from quantum machine learning as expected and how, because of non-stationarity, its application may embed and magnify risks.
2. Why some uncertainties, like those faced in pharmaceuticals development, make a viable application for quantum machine learning.
We then discuss why systems that help us cope with uncertainty must accommodate the way the world actually is, and the way humans actually think, so that we can make better decisions.
Rebbelith used our systems to identify exactly which media and journalists are valued by some of the busiest venture capital firms in the UK at the moment.
We believe growing companies should have the opportunity to communicate their value directly to target investors through the most effective media.
1. Why finance and investing will not benefit from quantum machine learning as expected and how, because of non-stationarity, its application may embed and magnify risks.
2. Why some uncertainties, like those faced in pharmaceuticals development, make a viable application for quantum machine learning.
We then discuss why systems that help us cope with uncertainty must accommodate the way the world actually is, and the way humans actually think, so that we can make better decisions.