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AI · September 25, 2025

LA

Lingo – A linguistic database in Rust with nanosecond-level performance

Hi HN, I made Lingo - the SQLite of semantic search. I'm a self-taught developer and researcher who left school at 16, and I've spent some time exploring a first-principles approach to system design for various frontier problems. In this case it's AI that challenges the 'bigger is better' transformer paradigm. Lingo is the first piece of that research, a high-performance linguistic database designed to run on-device. The full technical overview and manifesto is here: https://medium.com/@robm.antunes/bcd1e9752af6 The paper has been archived on Zenodo with a DOI:…

Alternativestop 21% of September 2025

In plain words

Lingo is a linguistic database written in Rust that performs semantic search with nanosecond-level speed and runs on-device. Designed as an alternative to large transformer models, it targets developers and researchers seeking efficient, on-device AI solutions without requiring massive computational resources. The open-source project prioritizes system design efficiency and challenges conventional approaches to language processing.

written from the facts on this page · September 2026

From the sources

In the maker’s words, at launch

Hi HN, I made Lingo - the SQLite of semantic search. I'm a self-taught developer and researcher who left school at 16, and I've spent some time exploring a first-principles approach to system design for various frontier problems. In this case it's AI that challenges the 'bigger is better' transformer paradigm. Lingo is the first piece of that research, a high-performance linguistic database designed to run on-device. The full technical overview and manifesto is here: https://medium.com/@robm.antunes/bcd1e9752af6 The paper has been archived on Zenodo with a DOI: https://doi.org/10.5281/zenodo.17196613 The code is open-source and can be found at https://github.com/RobAntunes/lingodb, it's currently broken and feature incomplete but I'm working on it - just wanted to start getting some feedback. All benchmarks are reproducible from the repo and can also be found in the various texts. As an independent without academic affiliation, I'd be incredibly grateful for your feedback! I'm here to answer any questions. Cheers!

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