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  • Building Blocks of LLM
    AI, ML & Data Science - Artificial Intelligence (AI) - Academic Use - Acharjo - Generative AI Fundamentals

    A Deep Dive Into the Inner Workings of Large Language Models: đź§  Transformer Architecture Explained: The Brain Behind LLMs

    December 6, 2022 - By Kinshuk Dutta

    🔍 Introduction: Beyond Thought Simulation In our previous blog on Thought Generation in AI and NLP, we explored how modern AI systems can simulate reasoning, explanation, and creativity. At the heart of this capability lies a game-changing innovation in deep learning: the Transformer architecture. Originally introduced in the groundbreaking paper Attention is All You Need by Vaswani et al. in 2017, transformers have become the standard building block for nearly every large language model (LLM)—including GPT, BERT, PaLM, and Claude. This blog takes a hardcore technical deep dive into the full transformer architecture diagram you see above. Whether you’re a…

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  • AI, ML & Data Science - Generative AI Fundamentals - Acharjo - Academic Use - Artificial Intelligence (AI)

    How ChatGPT and Large Language Models Simulate Thinking: đź§  Thought Generation in AI and NLP

    November 30, 2022 - By Kinshuk Dutta

    The Moment the World Realized AI Could “Think” It’s just before midnight on November 30, 2022, and something extraordinary is unfolding. ChatGPT was released to the public earlier today, and like many across the world, I’ve spent hours interacting with it—testing its reasoning, pushing its boundaries, and watching it respond with an uncanny sense of logic, memory, and conversational flow. This very day made something abundantly clear: Machines can now simulate thought—with startling fluency. If you’ve followed my earlier explorations on AI vs ML vs DL or Tokenization in NLP, you’ve seen how machines learn and process language. But today’s…

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Editor-in-Chief

Kinshuk Dutta Editor-in-Chief, Data-Nizant Forum Enterprise AI, agentic systems, governance, MLOps, and operating models, focused on what works in production.

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