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An Open Source Machine Learning Framework for Everyone
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Over the past few months I have been using pretty much every major AI tool available right now. Not for research and not for a project, but just as part of my daily student life. Assignments, coding, building apps, and asking questions. Normal usage. Across all of them, I noticed patterns. Things each one does well, and things each one consistently gets wrong. This is just what I found. Gemini — S
Most AI news tools try to solve information overload by summarizing more content, faster. That was not the product I wanted to build. I wanted something closer to a personal news radar: a system that could watch Hacker News, Reddit, RSS, GitHub, Telegram, and other sources for me, reduce the noise, connect the context, and still leave room for human judgment. So I built Horizon. Horizon is an ope
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
A practical look at using tower as the middleware layer for Rust AWS Lambda functions, with examples that build up to a DynamoDB-backed per-IP rate limiter. It covers Service, Layer, stack ordering, short-circuiting, boxed async futures, and testing middleware without deploying a Lambda. Comments