The new 3.5 release lets developers run PaddleOCR’s OCR and document‑parsing models (e.g., PP‑OCRv5, PaddleOCR‑VL 1.5) on a Transformers inference backend, simplifying integration with Hugging Face and PyTorch pipelines. Users can configure dtype, device placement, and attention via engine_config, reducing friction for RAG, Document AI, and other downstream workflows.
Google is expanding its content-transparency suite, adding SynthID watermark verification and C2PA Content Credentials to Search, Gemini, Chrome and Pixel devices. The new features let users ask if media was AI-generated and view its creation and edit history, aiming to improve provenance and combat misinformation.
Simon Willison unveiled Datasette Agent, an extensible AI assistant that lets users ask natural‑language questions of Datasette‑hosted SQLite data and generate charts via plugins. The demo shows the tool translating queries into SQL, producing visualizations with Observable Plot, and supporting additional plugins for image generation and code execution.
Hugging Face has published a concise glossary that defines core AI‑agent terminology such as “harness,” “scaffold,” and “agent.” The guide aims to reduce confusion for developers and researchers by offering practical, uniform definitions for concepts that appear across tools like Claude Code, Codex, and Hermes Agent.
Simon Willison released llm-gemini 0.32, extending his Python LLM library to include the new Gemini 3.5 Flash model. The upgrade lets developers tap into Gemini 3.5 Flash’s fast, cost‑effective performance directly from the library.