The use of the Fermilab main injector proton beam with an energy of 120 GeV and a 4.4-second spill every minute in combination with a polarized target provides a unique opportunity for future spin physics experiments. New technology in RF manipulated dynamically polarized (DNP) target systems rely on artificial intelligence to optimally configuration the target polarization state using the signal from continuous wave nuclear magnetic renounce (NMR). The target spins can be autonomously oriented in the time between spills allowing for the access of novel observables. Machine learning tools are advancing instrumentation potential as well as information extraction in Spin Physics. Some examples are provided, with a focus on possible future experiments at Fermilab.