Agents need vector search more than RAG ever did

Qdrant's $50M Series B and version 1.17 release make the case that agentic AI didn't simplify vector search — it scaled the ...
InfoWorld

Why Postgres® has won as the de facto database: Today and for the agentic future

The 13% succeeding with AI platforms share one move: unifying their data on an extensible Postgres® foundation.

Google Gemini Embedding 2 Supports Text, Images, Audio, PDFs & Short Videos

Google Gemini Embedding 2 unifies text, images, audio, PDFs, and video; it supports 3,072-dimension vectors, simplifying retrieval stacks.

Google's Gemini Embedding 2 arrives with native multimodal support to cut costs and speed up your enterprise data stack

While previous embedding models were largely restricted to text, this new model natively integrates text, images, video, audio, and documents into a single numerical space — reducing latency by as muc ...

Gemini Embedding 2 Supports Search Across 100+ Languages

Gemini Embedding 2 ships cross-modality retrieval with Matryoshka vectors, offering flexible dimensions for cost and accuracy tradeoffs.
MarketWatch

Unstructured and Teradata Partner to Make Enterprise Data AI-Ready at Scale

Unstructured today announced a partnership with Teradata to deliver data ingestion and processing as a native capability inside Teradata Enterprise Vector Store. Expected to be available to eligible ...
Tech Times

The DIY Lakehouse Tax: Why Companies Spend $520K/Year Recreating What Already Exists

Building an open-source data lakehouse costs $520K/year in engineering time, before licenses and infra. The real all-in cost ...
WinBuzzer

Gemini Embedding 2 Unifies Text, Images, Video in One Model

Google has launched Gemini Embedding 2, its first natively multimodal embedding model supporting text, images, video, audio, ...