A College Project That Planted a Seed Years ago I was on a university team trying to build a Go AI. We explored monte carlo simulation for lookahead search, basic neural networks for pattern recognition, and expert systems for encoding domain knowledge. None of them worked well enough on their own. Go's branching factor is enormous, so brute-force search fails quickly. Neural networks without th
This section is the map for the rest of the book. The five stages introduced in the 1.1 chapter overview (parse, analyze/rewrite, plan, portal, execute) are traced here through the actual code: which functions implement each stage, and in what order they get called. The mechanics of each of the five stages are unpacked in later chapters. Here, only the skeleton matters: how a backend starts up, ho
If you’ve been building with AI recently, you’ve probably seen these terms everywhere: AI Gateway. And depending on where you read, they either sound like the same thing… or completely different systems. Some vendors use them interchangeably. Others define only one and ignore the rest. And if you try to piece it together yourself, you end up with a vague understanding that doesn’t really help when
PostgreSQL Internals · Chapter 1 Query Processing Suppose a client sends SELECT * FROM users WHERE id = 1. The path that single line travels before coming back as a result row is longer than you might expect. Inside the PostgreSQL backend, that SQL goes through a five-stage pipeline. Backend entry and dispatch. The backend receives the message from the client and decides which processing path it s
In an era where data privacy is often the price we pay for convenience, medical information remains the most sensitive frontier. When you upload a patient's transcript or a personal health log to a centralized API, you're essentially trusting a third party with your most intimate data. But what if the "brain" lived entirely within your browser? Today, we are diving deep into the world of Edge AI a
SQL is widely known for data querying and manipulation but systems do grow; data becomes larger; processes become repetitive and operations become sensitive. SQL has some features which enables it to be considered a fully fledged programming language. Some of the features which I discuss in this article are procedures, functions and transactions. Each of these concepts serve distinct purposes. Sto
Self-attention already helps a transformer understand relationships between words using Query, Key, and Value. But there’s a problem. One attention mechanism usually ends up focusing on a limited kind of relationship at a time. Language doesn’t work like that. A sentence can have structure, meaning, and long-range links all at once. That’s why transformers use multi-head attention. Instead of doin
I keep seeing the same argument about AI making us dumber. It's the same argument people had about search engines, and before that books. The usual response is to point at history and say "every generation panics, every generation was wrong, relax." I think that response is half right, and the wrong half is what bothers me. Tools change what we bother to remember. The people who'd trained their wh