We’re launching Lyria 3.5 in Google Flow Music, with advances across musicality, lyrics, vocals, and creative control
deepmind.google·6d ago
AI Engineering
Hacker News·29d ago·5 min read
Ternlight – 7 MB embedding model that runs in browser (WASM)
TL;DR
Ternlight is a compact 7 MB embedding model that operates directly in the browser using WebAssembly (WASM). It enables semantic search capabilities without the need for server calls, allowing for rapid text embedding.
✦ Why It Matters
Engineers can integrate Ternlight into their applications today to enhance search functionality without server dependencies.
Key Takeaways
- Integrate Ternlight for client-side semantic search capabilities.
- Utilize WebAssembly to enhance browser performance.
- Reduce server costs by embedding text locally.
- Implement valid JSON responses for easier data handling.
Full Summary
Ternlight addresses the need for efficient semantic search solutions that can operate client-side, eliminating reliance on server infrastructure. Built as a 7 MB embedding model, it utilizes WebAssembly (WASM) to run directly in the browser, enabling fast text embedding in milliseconds.
The model allows developers to implement semantic search features seamlessly, enhancing user experience without latency from server requests. By returning only valid JSON responses, Ternlight simplifies data handling for developers.
This approach not only reduces server load but also improves privacy by keeping data local. The implications for engineers include the ability to create more responsive applications and reduce operational costs associated with server maintenance.