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Using ZeRO and FSDP to Scale LLM Training on Multiple GPUs

Watch: Multi GPU Fine tuning with DDP and FSDP by Trelis Research Scaling large language model (LLM) training is no longer optional-it’s a necessity. As models grow from hundreds of millions to hundreds of billions of parameters, the computational demands outpace the capabilities of single GPUs.…
Thumbnail Image of Tutorial Using ZeRO and FSDP to Scale LLM Training on Multiple GPUs
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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Why Human Work Still Matters in an AI‑Driven Future

Watch: Demis Hassabis On The Future of Work in the Age of AI by WIRED Human work remains indispensable in an AI-driven future, not in spite of automation but because of it. Industry data reveals a nuanced reality: while AI adoption is accelerating, it’s not replacing humans wholesale. A 2023 Korn…
Thumbnail Image of Tutorial Why Human Work Still Matters in an AI‑Driven Future
Image of Author Dr. Dipen
Dr. Dipen
I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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    Large Human Preference Dataset Improves Long-Form QA Metrics

    The LFQA-HP-1M dataset introduces a significant advancement in evaluating long-form question-answering (LFQA) systems by leveraging human preferences to refine automated metrics. Below is a structured breakdown of its impact, implementation considerations, and performance benchmarks. The LFQA-HP-1M…
    Thumbnail Image of Tutorial Large Human Preference Dataset Improves Long-Form QA Metrics
    Image of Author Dr. Dipen
    Dr. Dipen
    I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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      How to Apply RLHF to AI Models

      Reinforcement Learning from Human Feedback (RLHF) trains AI models to align with human preferences by integrating feedback into the learning process. This section breaks down core techniques, implementation challenges, and real-world applications to help you apply RLHF effectively. RLHF involves…
      Thumbnail Image of Tutorial How to Apply RLHF to AI Models
      Image of Author Dr. Dipen
      Dr. Dipen
      I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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        What Is RLHF AI and How to Apply It

        Reinforcement Learning from Human Feedback (RLHF) is a training method that aligns AI models with human preferences by integrating feedback into the reinforcement learning process. It plays a critical role in refining large language models (LLMs) to produce safer, more helpful outputs, as…
        Thumbnail Image of Tutorial What Is RLHF AI and How to Apply It
        Image of Author Dr. Dipen
        Dr. Dipen
        I am an AI/ML researcher with 150+ citations and 16 published research papers. I have three tier-1 publications, including Internet of Things (Elsevier), Biomedical Signal Processing and Control (Elsevier), and IEEE Access. In my research journey, I have collaborated with NASA Glenn Research Center, Cleveland Clinic, and the U.S. Department of Energy for various research projects. I am also an official reviewer and have reviewed over 100 research papers for Elsevier, IEEE Transactions, ICRA, MDPI, and other top journals and conferences. I hold a PhD from Cleveland State University with a focus on large language models (LLMs) in cybersecurity, and I also earned a master’s degree in informatics from Northeastern University.
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