Feynman's visionary keynote speech emphasized the need for probabilistic computers to simulate complex, inherently probabilistic problems. This project addresses the challenge of developing hardware capable of accelerating probabilistic algorithms. By designing probabilistic bits (p-bits) based on stochastic low barrier magnets in magnetic tunnel junctions (MTJs), the research aims to realize a breakthrough in probabilistic computing. The proposed materials foundation focuses on identifying novel soft magnetic Heusler alloys with ultra-low energy barriers that can be controlled using energy-efficient spin-orbit torque (SOT) materials. This interdisciplinary endeavor integrates theoretical modeling, high-throughput materials screening, computational simulations, experimental synthesis and characterization, and modular simulations to accelerate materials discovery and device design for p-bit implementation. The transformative potential of this research lies in enabling compact and energy-efficient hardware for probabilistic computing, with implications for the semiconductor industry and expanding the material base for industry-relevant spintronic memory technologies. Research results produced by this work will be available to the wider community through the nanoHUB spintronics portal and gained knowledge will be disseminated through its educational platform that has offered courses to thousands of students and engineers. Moreover, student training and workforce development will be enhanced through a planned summer school.