Cognitum One Launches Commercial RuVector, the Self-Learning Database Giving AI Agents Memory That Persists, Connects and Improves

The open-source Rust engine combines vector search, graph relationships and self-learning memory, now backed by commercial licensing, enterprise support and deployment services.SAN FRANCISCO, CA / ...
BIOENGINEER

Small AI on the Edge, Big AI in the Cloud: New Framework Sharpens Wind Speed Forecasts

A new cloud-edge AI framework called SMWPF combines a lightweight edge predictor with a Qwen-based cloud model to cut wind ...
BIOENGINEER

Enhancing BNN storage and performance requirements via efficient quantization and variable encoding

Binary neural networks have long promised to bring deep learning to the smallest and most power-hungry devices on the planet.
MarkTechPost

Google DeepMind Releases EmbeddingGemma 2, a 740M Open Multimodal Embedding Model Built on Gemma 4

Google DeepMind's EmbeddingGemma 2 embeds text, code, images, video and audio in one 740M model for on-device RAG.
Unite.AI

What Is a Vector Database? How AI Stores and Searches Embeddings

Vector databases store, index, filter, and search embeddings so applications can retrieve items by similarity at operational scale. This guide explains the mechanism, trade-offs, evaluation, and ...
unite

Pinecone Open-Sources VQ-Bench Vector Quantization Framework

Pinecone has released VQ-bench, an open-source framework for building and benchmarking vector quantization methods, in a September 17, 2026 announcement by Ashwin Padaki, Amir Ingber, and Edo Liberty.
Morningstar%2c Inc.

Coursera Makes $100 Million Strategic Investment in LearnVector, a New AI-Native Learning Company Founded by Andrew Ng

The investment is intended to advance Coursera’s AI strategy and reflects its conviction that AI expands the market for learning rather than replacing it LearnVector plans to put AI agents to work for ...
GitHub

RDVQ: Differentiable Vector Quantization for Rate-Distortion Optimization of Generative Image Compression

RDVQ is a VQ-based generative image compression framework for efficient and controllable ultra-low-bitrate image compression. Conventional VQ-VAE learns powerful discrete representations, but its ...
InfoQ

Google’s TurboQuant Compression May Support Faster Inference, Same Accuracy on Less Capable Hardware

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. The article examines the transition from ...
Hackaday

vector quantization

Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the probabilities of tokens occurring in a specific order is encoded. Billions of ...
almcorp

Google TurboQuant and Vector Search: What It Is, How It Works, and What It Could Mean for Search

Google keeps looking for ways to make search systems faster, cheaper, and more precise at scale. TurboQuant matters because it sits at the intersection of those three goals. At a high level, ...
quantumzeitgeist

Google: Quantization Boosts Vector Search Efficiency

Google Research has unveiled a suite of new quantization algorithms designed to improve the efficiency of artificial intelligence systems, particularly in vector search and large language models. The ...