EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hacker News·Jul 26·5 min read
Show HN: Distill and serve small models with frontier quality for half the cost
TL;DR
A new approach enables the distillation and deployment of small AI models that maintain frontier quality at over 40% lower costs. Continuous improvement is achieved through simulations based on existing agent traces.
✦ Why It Matters
Start optimizing your AI models today by implementing trace-based evaluations to reduce costs and improve performance.
Key Takeaways
- Install WMO and register your providers to get started.
- Tune your routing system using OTel traces for better model performance.
- Evaluate your models against benchmarks to measure improvements.
- Utilize world models for simulating environments during testing.
How It Works
WMO operates by first collecting agent traces, which are data logs of agent interactions. It then uses these traces to optimize routing policies and improve model performance through simulations.
The tool allows for continuous evaluation and refinement of models, ensuring that only the most effective versions are deployed.