Extropic AI Research Publications

At Extropic AI, we're committed to advancing the field of artificial intelligence and scientific computing through rigorous research and open collaboration. Our team of world-class researchers regularly publishes groundbreaking work in top-tier journals and conferences. Explore our latest publications below.

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Stochastic Energy-Based Models on Superconducting Hardware: A New Frontier in AI Acceleration
Zhang, L., Patel, A., Goldstein, M., & Johnson, K.
Nature Machine Intelligence, 2023
Abstract: This paper introduces a novel approach to implementing energy-based models using stochastic superconducting circuits. We demonstrate unprecedented performance in terms of sampling efficiency and energy consumption, opening new possibilities for large-scale AI applications.
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Quantum-Inspired Optimization Algorithms for Financial Portfolio Management
Nakamoto, S., Lee, J., & Goldstein, M.
Quantum Finance, 2022
Abstract: We present a new class of quantum-inspired algorithms for portfolio optimization, leveraging Extropic AI's superconducting hardware. Our approach shows significant improvements in both computational speed and solution quality compared to classical methods.
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Accelerating Molecular Dynamics Simulations with Energy-Based Models on Superconducting Chips
Rodriguez, E., Chang, W., & Patel, A.
Journal of Computational Chemistry, 2023
Abstract: This study demonstrates the application of Extropic AI's superconducting technology to molecular dynamics simulations. We achieve a 100-fold speedup in protein folding simulations while maintaining high accuracy, potentially revolutionizing drug discovery processes.
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Enhancing Climate Models with Stochastic Energy-Based Computing: A Case Study
Johnson, K., Zhang, L., & Lee, J.
Geophysical Research Letters, 2022
Abstract: We apply Extropic AI's stochastic energy-based computing approach to improve the resolution and accuracy of global climate models. Our results show significant enhancements in both short-term weather prediction and long-term climate projections.
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Towards Quantum Supremacy in AI: A Comparative Study of Superconducting and Quantum Computing Approaches
Goldstein, M., Nakamoto, S., & Chang, W.
Quantum Information Processing, 2023
Abstract: This comprehensive study compares the performance of Extropic AI's superconducting technology with state-of-the-art quantum computers across various AI tasks. We demonstrate that our approach achieves quantum-like advantages in certain domains while offering greater scalability and practicality.
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Collaborations and Open Research

Extropic AI is committed to advancing the field of AI and scientific computing through open collaboration. We actively seek partnerships with academic institutions, research labs, and industry leaders. If you're interested in collaborating with us, please visit our research collaboration page.

Join Our Team

We're always looking for brilliant minds to join our research team. If you're passionate about pushing the boundaries of AI and scientific computing, check out our research positions.

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