Welcome to my blog, where I share my journey through the fascinating world of Artificial Intelligence and Machine Learning. I critically analyze research papers to break down complex ideas and uncover insights. Alongside, I document my hands-on experiences in creating neural networks from scratch, explaining every small detail and tackling coding challenges step by step. Whether you're here to explore theory or dive into practical implementation, this blog is for you!
Collaboration and research.
Jan 8 · 9 min read · I recently came across a paper called "Recursive Language Models" that made a claim I couldn't ignore we can make LLM handle inputs longer than its context window and not just handle them, but actually perform better on complex tasks. We don't need t...
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Aug 19, 2025 · 12 min read · OpenAI stated in the GPT-OSS documentation that these models should only be used with the Harmony response format; otherwise, they won’t work correctly. They’re trained on this specific format, only understand this, and only respond properly when use...
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Apr 23, 2025 · 6 min read · Sometimes, when working with RAG systems, we need to know exactly what context is being passed to the LLM. You run a query, the model gives an answer, sometimes strange or irrelevant, and you are left wondering , “Did it actually get the right inform...
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Mar 30, 2025 · 5 min read · We are surrounded by very messy data. Text is often unsupervised, unlabeled, with images scattered throughout documents, along with complex figures and tables that hold most of the actual information. The insight is stored less in words and more in v...
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Jan 21, 2025 · 21 min read · In my last three blog posts, we explained about how to reduce the wrong but high confidence of neural network, how to identify dead neurons, and The Kaiming initialization and batch normalization. The core of these three blog post is, the correct ini...
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