Direct announcements from model vendors, companies and research institutions on their official sites, blogs and accounts.
Condé Nast and AWS's Generative AI Innovation Center (GenAIIC) built a multimodal video search solution using Amazon Bedrock and Amazon OpenSearch Service. It uses TwelveLabs Marengo embeddings to jointly encode visuals, audio, and transcripts, cutting a single content search from 250 minutes to under two minutes.
Google Research proposes Retrieve-for-Train, a framework that uses offline RL to discover reward-aligned query fan-outs and compile them into supervision, then distills them into a 53.9M-parameter diffusion retriever. At inference, it generates a complete result set in one non-autoregressive pass without chain-of-thought tokens. The method fine-tunes fan-out language models based on Gemma3-4B and Qwen3-4B, using set-level attribute rewards to address paraphrase collapse in zero-shot LLMs and autoregressive latency.
