<?xml version="1.0" encoding="UTF-8"?><urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:video="http://www.google.com/schemas/sitemap-video/1.1"><url><loc>https://aiunderstanding.org/news/google-launches-gemini-3-5-transcribe-for-real-time-cleaned-up-speech-to-text</loc><video:video><video:thumbnail_loc>https://aiunderstanding.org/api/news/image/google-launches-gemini-3-5-transcribe-for-real-time-cleaned-up-speech-to-text</video:thumbnail_loc><video:title>Google’s Gemini 3.5 Transcribe expands cleaned-up voice input beyond Gboard</video:title><video:description>Ars Technica reports that Google is extending Gemini 3.5 Transcribe, a speech-to-text model that removes verbal filler and handles corrections, from Pixel 11’s Gboard feature to selected Google products and developer tools. Google claims faster transcription and a lower live-speech error rate, but those figures…</video:description><video:content_loc>https://aiunderstanding.org/api/news/video/google-launches-gemini-3-5-transcribe-for-real-time-cleaned-up-speech-to-text</video:content_loc><video:publication_date>2026-08-26T17:02:11.345Z</video:publication_date><video:family_friendly>yes</video:family_friendly></video:video></url>
<url><loc>https://aiunderstanding.org/news/goodfire-presents-silico-an-agent-for-interpreting-and-debugging-ai-models</loc><video:video><video:thumbnail_loc>https://aiunderstanding.org/api/news/image/goodfire-presents-silico-an-agent-for-interpreting-and-debugging-ai-models</video:thumbnail_loc><video:title>Goodfire presents Silico, an agent for interpreting and debugging AI models</video:title><video:description>Goodfire’s new Silico platform is designed to inspect hidden model representations, diagnose behavior and guide targeted interventions across life-sciences, robotics, vision and language models.</video:description><video:content_loc>https://aiunderstanding.org/api/news/video/goodfire-presents-silico-an-agent-for-interpreting-and-debugging-ai-models</video:content_loc><video:publication_date>2026-08-26T12:01:51.315Z</video:publication_date><video:family_friendly>yes</video:family_friendly></video:video></url>
<url><loc>https://aiunderstanding.org/news/ollama-adds-claude-desktop-support-as-a-third-party-gateway</loc><video:video><video:thumbnail_loc>https://aiunderstanding.org/api/news/image/ollama-adds-claude-desktop-support-as-a-third-party-gateway</video:thumbnail_loc><video:title>Ollama adds Claude Desktop support as a third-party gateway</video:title><video:description>Ollama says developers can connect Claude Desktop to local Ollama models, Ollama-hosted cloud models, or Anthropic models through a toggle in Ollama.</video:description><video:content_loc>https://aiunderstanding.org/api/news/video/ollama-adds-claude-desktop-support-as-a-third-party-gateway</video:content_loc><video:publication_date>2026-08-26T03:02:51.999Z</video:publication_date><video:family_friendly>yes</video:family_friendly></video:video></url>
<url><loc>https://aiunderstanding.org/news/hugging-face-introduces-gradio-tool-for-building-deployable-ai-workflows</loc><video:video><video:thumbnail_loc>https://aiunderstanding.org/api/news/image/hugging-face-introduces-gradio-tool-for-building-deployable-ai-workflows</video:thumbnail_loc><video:title>Hugging Face introduces Gradio tool for building deployable AI workflows</video:title><video:description>Hugging Face says its new gr.Workflow feature lets developers connect typed Python functions, models, Gradio Spaces and datasets into visual pipelines that can also be exposed as REST APIs and deployed to Spaces.</video:description><video:content_loc>https://aiunderstanding.org/api/news/video/hugging-face-introduces-gradio-tool-for-building-deployable-ai-workflows</video:content_loc><video:publication_date>2026-08-25T03:16:31.227Z</video:publication_date><video:family_friendly>yes</video:family_friendly></video:video></url>
<url><loc>https://aiunderstanding.org/news/aws-describes-an-ai-workflow-for-correcting-and-harmonizing-biomedical-metadata</loc><video:video><video:thumbnail_loc>https://aiunderstanding.org/api/news/image/aws-describes-an-ai-workflow-for-correcting-and-harmonizing-biomedical-metadata</video:thumbnail_loc><video:title>AWS describes an AI workflow for correcting and harmonizing biomedical metadata</video:title><video:description>AWS has published a deployable workflow that uses language models, embeddings and rule-based validation to identify inconsistent biomedical metadata and recommend corrections, with either human approval or agent-driven automation.</video:description><video:content_loc>https://aiunderstanding.org/api/news/video/aws-describes-an-ai-workflow-for-correcting-and-harmonizing-biomedical-metadata</video:content_loc><video:publication_date>2026-08-24T16:56:32.834Z</video:publication_date><video:family_friendly>yes</video:family_friendly></video:video></url></urlset>