Archives

Murali 0.2.0 adds vertical video export, making it easier to create mathematical and AI animations for YouTube Shorts, Instagram Reels, and other mobile-first platforms.

Why unnecessary AI additions to clean work create organizational noise, resurrect dead debates, and waste human bandwidth—and why we need to call it AI Tadka.

A practical review of The Hundred-Page Machine Learning Book from the perspective of a senior engineer rebuilding classical machine learning fundamentals.

A software engineer's view of AI in mid-2026: what is real, what is distorted, where the pain is, and what needs to mature next.

AI systems do not just need data. They create data every time they run, and that changes how we design, debug, evaluate, and improve them.

A practical distinction between open-weight AI models and truly open source AI systems, and why the difference matters when choosing local LLMs.

A step-by-step, reference-backed explanation of what happens during LLM inference: tokenization, embeddings, prefill & decode phases, KV caching, decoding strategies, bottlenecks and optimizations like quantization, FlashAttention and speculative decoding.

A complete guide to tokenizers in modern LLMs, covering BPE, WordPiece, SentencePiece, Unigram, and how ChatGPT, Grok, and Gemini tokenize text. Includes examples, real-world impact, and why tokenization is the foundation of AI.

A deep dive into what embeddings are, why they matter, and how they power modern AI, semantic search, and RAG-based systems.

A Deep Dive into Transformer Optimization

The Architecture That Revolutionized Machine Learning

Decoding the Secrets of AI Text Generation

Decoding the Battle of AI Accelerators in 2025

In the rapidly evolving world of artificial intelligence, large language models (LLMs) like GPT-4 or Grok have transformed how we interact with technology.