AI for developmentPercona Database Blog
AI for development
We loaded 990,000 OpenAI embeddings of 1,536 dimensions into six databases that index vectors themselves, built an HNSW index in each, and measured five things: time to a queryable index, storage and memory, recall against throughput,…
Generative AI is rapidly evolving from experimenting with models to relying on intelligent, autonomous multi-agent workflows that can reason, act, and adapt in real time. Together, Microsoft and MongoDB are defining the future of AI by…
At MongoDB Research, we’re exploring how to make cutting‑edge AI models smaller, faster, and more flexible. In this blog post, we present LEAF (Lightweight Embedding Alignment Framework), a new knowledge distillation framework for text…
Google has introduced the LiteRT Tensor API, a lightweight C++ API that allows developers to build, customize, and optimize machine learning models directly for on-device execution. According to Google, it combines the flexibility of…