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.

Cracking the code: How a 'prediction machine' is resurrecting the Singapore Stone

Several years ago, my linguistic research team and I began developing a computational tool we call "Read-y Grammarian." Our ...
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, ...

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 ...
GitHub

Motus: A Unified Latent Action World Model

Inference (without pre-encoded T5) ~ 41 GB A100 (40GB) / A100 (80GB) / H100 / B200 Motus_Wan2_2_5B_pretrain Pretrain / VGM Backbone Stage 1 VGM pretrained checkpoint ...
IEEE

Large Speech Model Enabled Semantic Communication

Abstract: Existing speech semantic communication systems mainly based on Joint Source-Channel Coding (JSCC) architectures have demonstrated impressive performance, but their effectiveness remains ...
IEEE

BEGA: A Binary Code Embedding Method Based on Gravity-Model Augmentation Graph Contrastive Learning

Abstract: Binary code similarity detection primarily aims to compare two or more binary code files or code snippets to identify their differences. Currently, binary code similarity detection is ...
GitHub

3DSPA: 3D Semantic Point Autoencoder

This repository contains the implementation of 3DSPA (3D Semantic Point Autoencoder), a framework for evaluating video realism using semantic-aware 3D point trajectories. 3DSPA extends TRAJAN to 3D by ...
TMCnet

Elastic Introduces Best-in-Class Embedding Models for High Performance Semantic Search

Elastic (NYSE: ESTC), the Search AI Company, today announced the availability of jina-embeddings-v5-text, a family of two small, Elasticsearch-native multilingual embedding models at 0.2B and 0.6B ...
Morningstar

Elastic Introduces Best-in-Class Embedding Models for High Performance Semantic Search

New Jina AI small language models deliver unmatched quality and efficiency on search and semantic tasks Elastic (NYSE: ESTC), the Search AI Company, today announced the availability of jina-embeddings ...