For fundamental physics to go forward, good use of modern technologies and tools needs to be made. Machine learning and quantum technologies are two examples of tools that can be used to drive physics forward. With ever-expanding datasets coming from space missions, it is becoming increasingly more difficult for scientists to manually analyse data. I am currently working on a project involving the use of machine learning to analyze 16-years’ worth of data taken by the Electron Spectrometer aboard the Mars Express mission to better understand the magnetic field configuration of the Martian environment. Similarly, atom interferometers can be used to answer questions regarding one of the universe’s biggest mysteries, dark matter. As part of the Atom Interferometer Observatory and Network (AION) experiment, I will soon start working on a new Strontium Atom Interferometer, for which I will attempt to give a brief overview.