quantisation
Beyond Market Intelligence keeps quantisation in one place: 2 stories so far. The section currently leads with “Explore vector embeddings through an interactive Wordle-style guide” and “A free guide to making ML models faster, from silicon to agents”. Vector embeddings don't have to be abstract. Performance engineering isn't just about reducing FLOPs. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every quantisation story on Beyond Market Intelligence, newest first.
Explore vector embeddings through an interactive Wordle-style guide
Vector embeddings don't have to be abstract. Machine learning engineer Abdur-Rahman Butler built an interactive guide that lets you play with them directly. The centerpiece is SemanticGuessr, a Wordle-meets-GeoGuessr game where you triangulate a hidden word on a 2D semantic map of 43,339 terms. It's challenging at first, semantic space rarely matches intuition, but addictive once you start throwing vector equations at it. For deeper context on how words map into learned vector space, check out our related guide on word embeddings.
A free guide to making ML models faster, from silicon to agents
Performance engineering isn't just about reducing FLOPs. Usamah Zakir spent months writing the guide he wished he'd had when starting out: *How to Make Your Model Fast*. It moves from silicon to agents, using roofline analysis to help you diagnose whether you're compute, bandwidth, or memory bound before optimizing. That systems-first thinking is rare and valuable. The whole thing is free and open source. If you're working on inference or edge AI, it's worth exploring.