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The AI Journey

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Never Ending Journey of Learning

  • Building an Intelligent RAG System for Enterprise-Scale Multi-modal document processing

    Building an Intelligent RAG System for Enterprise-Scale Multi-modal document processing

    Executive Summary Traditional RAG systems struggle because they rely on rigid chunking rules designed for specific document types. When a document is composed of paragraphs, tables, charts, and diagrams, these systems often break the context, leading to incomplete or inaccurate answers. Our approach solves this with a three-tier adaptive RAG architecture that works on mixed-format Read more

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    Sharad Nangia

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  • It’s all about GPUs — Accelerating ML executions

    It’s all about GPUs — Accelerating ML executions

    The evolution from CPU to GPU computing for machine learning represents one of the significant paradigm shifts in computing history, transforming how we approach complex computational problems. This transition from sequential to parallel processing has enabled breakthroughs in artificial intelligence that were previously considered impractical or cumbersome. Today’s state-of-the-art AI systems combine multiple acceleration approaches: Read more

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    by

    Sharad Nangia

    in

  • Machine Learning on Windows 11 with WSL2

    Machine Learning on Windows 11 with WSL2

    WSL (Windows Subsystem for Linux) provides a Linux-native environment on Windows, enabling seamless use of modern machine learning frameworks with full GPU acceleration via NVIDIA CUDA, cuDNN, ROCm (for AMD GPUs), and OpenCL (where supported). This is critical because many ML libraries have limited or deprecated support on native Windows, especially for training with GPUs. Using WSL over native Windows for machine… Read more

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    Sharad Nangia

    in

  • Being Hands-on – Performance Stats

    Being Hands-on – Performance Stats

    Every business has a unique potential waiting to be tapped. Recognizing the keys to unlock this growth can set an enterprise on the path to unprecedented success. Read more

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    by

    Sharad Nangia

    in