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    HYPERQ

    Sustainable Machine Learning

    Faster Training. Lower Costs. Better Planet.

    POWERING SUSTAINABLE
    AI TRAINING

    HyperQ is leading the way in sustainable AI training through our state of the art quantum-inspired optimization techniques that increase efficiency without compromising model performance. Our mission is to make AI training more environmentally friendly, cost-effective, and accessible for the next generation of machine learning innovators.

    1B

    Handles 1B+ Parameters

    5

    Real Time and Adaptive Monitoring Systems

    3

    Layers of Gradient Protection

    The HyperQ Optimizer

    We provide HyperQ as a seamless upgrade to the baseline optimizers currently used in your training pipelines. By tailoring our algorithm to your specific tech stack—from the models you build to the hardware you run on—we unlock significant efficiency gains that reduce development cycles and infrastructure spend. This allows your teams to train larger, more complex models faster, all while ensuring state-of-the-art performance. It is Distributed Data Parallel (DDP) and DeepSpeed compatible, ensuring seamless integration on any tech stack.  

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    SERVICES

    We have received requests to pilot from one of the largest computer vision model companies. 

    OUR BENCHMARKS

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    OUR TEAM

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    Matthew Birov
    Solo Founder & CEO
    CS + Business at Northeastern University
    GET IN TOUCH

    © 2025 By HyperQ.

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