<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet href="/rss-styles.xsl" type="text/xsl"?><rss version="2.0"><channel><title>Aditya&apos;s Blogs</title><description>Passionate about AI and software development. This site is my way of giving back — sharing the learnings from my journey, while I keep building and experimenting.</description><link>https://adityaxblogs.com/</link><language>en-us</language><item><title>Self Attention</title><link>https://adityaxblogs.com/blogs/self-attention/</link><guid isPermaLink="true">https://adityaxblogs.com/blogs/self-attention/</guid><description>An intuition-first walk through self attention — queries, keys and values by analogy, then the implementation, multi-head attention, and transformers.</description><pubDate>Tue, 14 Apr 2026 00:00:00 GMT</pubDate><category>AI</category><category>LLM</category><category>Transformers</category><category>Attention</category></item><item><title>Positional Embeddings</title><link>https://adityaxblogs.com/blogs/positional-embeddings/</link><guid isPermaLink="true">https://adityaxblogs.com/blogs/positional-embeddings/</guid><description>Token embeddings alone throw away word order. How position gets encoded into a sentence, and why the sinusoidal scheme is built the way it is.</description><pubDate>Sat, 11 Apr 2026 00:00:00 GMT</pubDate><category>AI</category><category>LLM</category><category>Embeddings</category><category>Transformers</category></item><item><title>Token Embeddings</title><link>https://adityaxblogs.com/blogs/token-embeddings/</link><guid isPermaLink="true">https://adityaxblogs.com/blogs/token-embeddings/</guid><description>How tokens turn into meaningful vectors: the core idea behind embeddings, how the training data is prepared, and a working implementation.</description><pubDate>Fri, 03 Apr 2026 00:00:00 GMT</pubDate><category>AI</category><category>LLM</category><category>Embeddings</category></item><item><title>Neural Networks</title><link>https://adityaxblogs.com/blogs/neural-networks/</link><guid isPermaLink="true">https://adityaxblogs.com/blogs/neural-networks/</guid><description>Building a neural network from the ground up — what the layers actually do, how training adjusts them, and a worked example end to end.</description><pubDate>Sat, 28 Mar 2026 00:00:00 GMT</pubDate><category>AI</category><category>LLM</category><category>Neural Networks</category></item><item><title>Tokenization</title><link>https://adityaxblogs.com/blogs/tokenization/</link><guid isPermaLink="true">https://adityaxblogs.com/blogs/tokenization/</guid><description>Why models break text into subwords, how Byte Pair Encoding builds a vocabulary from scratch, and what naive word splitting gets wrong.</description><pubDate>Thu, 19 Mar 2026 00:00:00 GMT</pubDate><category>AI</category><category>LLM</category><category>Tokenization</category></item><item><title>LLM in a nutshell</title><link>https://adityaxblogs.com/blogs/llm-in-a-nutshell/</link><guid isPermaLink="true">https://adityaxblogs.com/blogs/llm-in-a-nutshell/</guid><description>A plain-language overview of how large language models actually work — the mental model worth having before going anywhere near the internals.</description><pubDate>Fri, 30 Jan 2026 00:00:00 GMT</pubDate><category>AI</category><category>LLM</category></item></channel></rss>