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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In 2019, we explored the foundations of neural networks—how layers of interconnected nodes mimic the human brain to extract patterns from data. Since then, one area where neural networks have truly transformed the landscape is Natural Language Processing (NLP). What was once rule-based and statistical has now evolved into something more fluid, contextual, and surprisingly human-like—thanks to Large Language Models (LLMs) built atop deep neural architectures. We touched upon this topic in early 2020 in our blog 🧠 Understanding the Correlation Between NLP and LLMs lets keep momentum and try understand Neural Networks empowers NLP and LLM. The NLP Challenge:…
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Introduction Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and human language. In recent years, a significant advancement in NLP has been the development of Large Language Models (LLMs), which have dramatically improved the ability of machines to understand and generate human-like text. This blog aims to provide a foundational understanding of NLP and LLMs, their interconnection, and the transformative impact they have on various applications. What Is Natural Language Processing (NLP)? NLP is a subfield of AI that enables machines to read, interpret, and generate human language. It encompasses a…