<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0"
  xmlns:atom="http://www.w3.org/2005/Atom"
  xmlns:dc="http://purl.org/dc/elements/1.1/"
  xmlns:content="http://purl.org/rss/1.0/modules/content/">
  <channel>
    <title><![CDATA[StreamingMeme — Twelve Labs coverage]]></title>
    <link>https://www.streamingmeme.com</link>
    <description><![CDATA[Articles mentioning Twelve Labs.]]></description>
    <language>en-us</language>
    <ttl>60</ttl>
    <lastBuildDate>Fri, 18 Sep 2026 00:00:00 GMT</lastBuildDate>
    <copyright>StreamingMeme</copyright>
    <atom:link href="https://www.streamingmeme.com/client/twelve-labs/feed.xml" rel="self" type="application/rss+xml"/>
    <image>
      <url>https://www.streamingmeme.com/streamingmeme_logo_main.svg</url>
      <title><![CDATA[StreamingMeme — Twelve Labs coverage]]></title>
      <link>https://www.streamingmeme.com</link>
    </image>
    
    <item>
      <title><![CDATA[TwelveLabs launches video intelligence platform for 60x real-time indexing]]></title>
      <link><![CDATA[https://mazikbox.com/p/twelvelabs-video-intelligence-platform-api]]></link>
      <guid isPermaLink="false">15c03f6e-8753-4580-85ac-4fcbe9a7b315</guid>
      <pubDate>Fri, 18 Sep 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[TwelveLabs has announced a video intelligence platform and API that utilizes its Marengo and Pegasus models to enable natural language search and automated content analysis. The platform claims to index video at 60x real-time speeds and is currently used by organizations including NFL Media and MLSE.]]></description>
      <content:encoded><![CDATA[TwelveLabs has announced a video intelligence platform and API that utilizes its Marengo and Pegasus models to enable natural language search and automated content analysis. The platform claims to index video at 60x real-time speeds and is currently used by organizations including NFL Media and MLSE.]]></content:encoded>
      <dc:creator><![CDATA[MazikBox]]></dc:creator>
      <author><![CDATA[MazikBox]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/15c03f6e-8753-4580-85ac-4fcbe9a7b315.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[NASA, Google, and TiVo to headline Streaming Media Connect virtual event]]></title>
      <link><![CDATA[https://www.streamingmedia.com/Articles/News/Online-Video-News/NASA-Google-TiVo-Ballys-Wowza--TwelveLabs-to-Headline-Streaming-Media-Connect-with-Must-See-Series-of-Keynote-Fireside-Chats-176008.aspx]]></link>
      <guid isPermaLink="false">25079004-6a39-43fa-967f-54ffe6364af5</guid>
      <pubDate>Tue, 04 Aug 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[Streaming Media Connect 2026 will host a series of fireside chats featuring executives from NASA, Google, TiVo, Bally's, Wowza, and TwelveLabs. The sessions will cover technical topics including space-based streaming infrastructure, the role of agentic AI in streaming user experiences, and real-time live video processing strategies.]]></description>
      <content:encoded><![CDATA[Streaming Media Connect 2026 will host a series of fireside chats featuring executives from NASA, Google, TiVo, Bally's, Wowza, and TwelveLabs. The sessions will cover technical topics including space-based streaming infrastructure, the role of agentic AI in streaming user experiences, and real-time live video processing strategies.]]></content:encoded>
      <dc:creator><![CDATA[Streaming Media]]></dc:creator>
      <author><![CDATA[Streaming Media]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/25079004-6a39-43fa-967f-54ffe6364af5.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[TwelveLabs introduces Jockey platform to create a video memory layer]]></title>
      <link><![CDATA[https://www.startuphub.ai/ai-news/artificial-intelligence/2026/twelvelabs-builds-video-memory-layer]]></link>
      <guid isPermaLink="false">61ed1fc1-4eb2-46ee-89fa-92bf2a6028b8</guid>
      <pubDate>Thu, 23 Jul 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[TwelveLabs has unveiled 'Jockey,' a platform designed to create a persistent 'memory layer' for video ecosystems by preserving spatiotemporal relationships in video corpora. The system utilizes the company's Morango encoder and Pegasus language model to enable complex reasoning and querying across video collections for media, surveillance, and advertising applications.]]></description>
      <content:encoded><![CDATA[TwelveLabs has unveiled 'Jockey,' a platform designed to create a persistent 'memory layer' for video ecosystems by preserving spatiotemporal relationships in video corpora. The system utilizes the company's Morango encoder and Pegasus language model to enable complex reasoning and querying across video collections for media, surveillance, and advertising applications.]]></content:encoded>
      <dc:creator><![CDATA[StartupHub.ai]]></dc:creator>
      <author><![CDATA[StartupHub.ai]]></author>
      
    </item>

    <item>
      <title><![CDATA[TwelveLabs secures $100M Series B to scale video foundation models on AWS]]></title>
      <link><![CDATA[https://www.sportsvideo.org/2026/07/02/twelvelabs-raises-100-million-in-series-b-funding]]></link>
      <guid isPermaLink="false">80e80e80-53f5-4798-af12-8cbe4a2543c1</guid>
      <pubDate>Thu, 02 Jul 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[BUSINESS_NEWS]]></category>
      <description><![CDATA[TwelveLabs has secured $100 million in Series B funding, co-led by NEA and NAVER Ventures, to scale its video foundation models and expand international operations. The company provides video intelligence through its API and AWS Bedrock, focusing on semantic search and structured metadata generation.]]></description>
      <content:encoded><![CDATA[TwelveLabs has secured $100 million in Series B funding, co-led by NEA and NAVER Ventures, to scale its video foundation models and expand international operations. The company provides video intelligence through its API and AWS Bedrock, focusing on semantic search and structured metadata generation.]]></content:encoded>
      <dc:creator><![CDATA[Sports Video Group]]></dc:creator>
      <author><![CDATA[Sports Video Group]]></author>
      <enclosure url="https://www.sportsvideo.org/wp-content/uploads/2026/04/TwelveLabs.jpg" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[TwelveLabs secures $100M for video models as AWS partnership deepens]]></title>
      <link><![CDATA[https://www.sportsvideo.org/2026/07/02/twelvelabs-raises-100-million-in-series-b-funding/]]></link>
      <guid isPermaLink="false">ed39d043-abd5-42b0-840d-06fdcb8ab349</guid>
      <pubDate>Thu, 02 Jul 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[TwelveLabs has successfully secured $100 million in Series B funding to scale its video intelligence foundation models and expand its international operations. The company has also strengthened its multiyear partnership with AWS to optimize its inference workloads using custom Trainium chips.]]></description>
      <content:encoded><![CDATA[TwelveLabs has successfully secured $100 million in Series B funding to scale its video intelligence foundation models and expand its international operations. The company has also strengthened its multiyear partnership with AWS to optimize its inference workloads using custom Trainium chips.]]></content:encoded>
      <dc:creator><![CDATA[Sports Video Group]]></dc:creator>
      <author><![CDATA[Sports Video Group]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/ed39d043-abd5-42b0-840d-06fdcb8ab349.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[TwelveLabs raises $100M for multimodal video understanding and AWS expansion]]></title>
      <link><![CDATA[https://siliconangle.com/2026/07/01/twelvelabs-raises-100m-bring-superintelligence-ai-video-models/]]></link>
      <guid isPermaLink="false">bd499a74-77e9-49c0-b016-aa3797fdcc81</guid>
      <pubDate>Wed, 01 Jul 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[TwelveLabs has secured $100 million in Series B funding to scale its multimodal foundation models for video understanding and reasoning. The company is concurrently deepening its partnership with AWS to optimize inference workloads on custom Trainium silicon for applications in sports, advertising, and security.]]></description>
      <content:encoded><![CDATA[TwelveLabs has secured $100 million in Series B funding to scale its multimodal foundation models for video understanding and reasoning. The company is concurrently deepening its partnership with AWS to optimize inference workloads on custom Trainium silicon for applications in sports, advertising, and security.]]></content:encoded>
      <dc:creator><![CDATA[SiliconANGLE]]></dc:creator>
      <author><![CDATA[SiliconANGLE]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/bd499a74-77e9-49c0-b016-aa3797fdcc81.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[TwelveLabs brings Marengo video models natively to Snowflake AI Data Cloud]]></title>
      <link><![CDATA[https://www.twelvelabs.io/blog/twelvelabs-video-understanding-comes-to-snowflake-ai-data-cloud]]></link>
      <guid isPermaLink="false">699baccd-f0d1-4ea5-8c4b-5410bf64554f</guid>
      <pubDate>Fri, 19 Jun 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[Video-AI startup TwelveLabs has integrated its Marengo video understanding model natively into the Snowflake AI Data Cloud. This allows media, entertainment, and advertising teams to process video files and generate vector embeddings directly within their secure Snowflake environments, enabling analytics on unstructured video data. The integration aims to support advanced metadata queries, brand suitability scoring, and content curation for platforms like Warner Bros. Discovery, Disney, and Paramount.]]></description>
      <content:encoded><![CDATA[Video-AI startup TwelveLabs has integrated its Marengo video understanding model natively into the Snowflake AI Data Cloud. This allows media, entertainment, and advertising teams to process video files and generate vector embeddings directly within their secure Snowflake environments, enabling analytics on unstructured video data. The integration aims to support advanced metadata queries, brand suitability scoring, and content curation for platforms like Warner Bros. Discovery, Disney, and Paramount.]]></content:encoded>
      <dc:creator><![CDATA[TwelveLabs]]></dc:creator>
      <author><![CDATA[TwelveLabs]]></author>
      <enclosure url="data:image/svg+xml,&lt;svg display=&quot;block&quot; role=&quot;presentation&quot; viewBox=&quot;0 0 159 32&quot; xmlns=&quot;http://www.w3.org/2000/svg&quot;&gt;&lt;path d=&quot;M 1.915 0 L 0.558 0 C 0.25 0 0 0.25 0 0.559 L 0 1.344 C 0 1.653 0.25 1.903 0.558 1.903 L 1.915 1.903 C 2.223 1.903 2.472 1.653 2.472 1.344 L 2.472 0.559 C 2.472 0.25 2.223 0 1.915 0 Z&quot; fill=&quot;rgb(29, 28, 27" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[TwelveLabs bridges video-native AI with ad-tech rails for contextual targeting]]></title>
      <link><![CDATA[https://www.twelvelabs.io/blog/video-adversiting-still-does-not-read-the-room]]></link>
      <guid isPermaLink="false">13e8ef02-7330-4474-b1e2-d834c2f96a95</guid>
      <pubDate>Fri, 19 Jun 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[TwelveLabs outlines an architectural blueprint for streaming publishers to operationalize in-house video intelligence. By integrating multimodal AI models like Pegasus 1.5 and Marengo 3.0 with ad-serving infrastructure such as FreeWheel and AWS Elemental MediaTailor, the workflow targets advanced, brand-safe contextual targeting for VOD, FAST, and live sports.]]></description>
      <content:encoded><![CDATA[TwelveLabs outlines an architectural blueprint for streaming publishers to operationalize in-house video intelligence. By integrating multimodal AI models like Pegasus 1.5 and Marengo 3.0 with ad-serving infrastructure such as FreeWheel and AWS Elemental MediaTailor, the workflow targets advanced, brand-safe contextual targeting for VOD, FAST, and live sports.]]></content:encoded>
      <dc:creator><![CDATA[TwelveLabs]]></dc:creator>
      <author><![CDATA[TwelveLabs]]></author>
      <enclosure url="data:image/svg+xml,&lt;svg display=&quot;block&quot; role=&quot;presentation&quot; viewBox=&quot;0 0 159 32&quot; xmlns=&quot;http://www.w3.org/2000/svg&quot;&gt;&lt;path d=&quot;M 1.915 0 L 0.558 0 C 0.25 0 0 0.25 0 0.559 L 0 1.344 C 0 1.653 0.25 1.903 0.558 1.903 L 1.915 1.903 C 2.223 1.903 2.472 1.653 2.472 1.344 L 2.472 0.559 C 2.472 0.25 2.223 0 1.915 0 Z&quot; fill=&quot;rgb(29, 28, 27" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[TwelveLabs launches Marengo, Pegasus, and Rodeo video AI on AWS Marketplace]]></title>
      <link><![CDATA[https://siliconangle.com/2026/06/16/twelvelabs-video-ai-awsmarketplaceseries/]]></link>
      <guid isPermaLink="false">85d59525-e87d-4293-bf27-5c5c1a510a2f</guid>
      <pubDate>Tue, 16 Jun 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[TwelveLabs has expanded its video AI models, Marengo, Pegasus, and Rodeo, onto AWS Marketplace, enabling enhanced video search and editing capabilities for the telco, media, entertainment, games, and sports (TMEGS) sectors. This move aims to broaden the reach of its multimodal AI technology for analyzing and interacting with video content for streaming industry professionals.

Danny Nicolopoulos, head of strategic partnerships at TwelveLabs, highlighted the demand from companies monetizing video for these AI tools, which facilitate use cases like creating highlight reels and accelerating video editing workflows.]]></description>
      <content:encoded><![CDATA[TwelveLabs has expanded its video AI models, Marengo, Pegasus, and Rodeo, onto AWS Marketplace, enabling enhanced video search and editing capabilities for the telco, media, entertainment, games, and sports (TMEGS) sectors. This move aims to broaden the reach of its multimodal AI technology for analyzing and interacting with video content for streaming industry professionals.

Danny Nicolopoulos, head of strategic partnerships at TwelveLabs, highlighted the demand from companies monetizing video for these AI tools, which facilitate use cases like creating highlight reels and accelerating video editing workflows.]]></content:encoded>
      <dc:creator><![CDATA[SiliconANGLE]]></dc:creator>
      <author><![CDATA[SiliconANGLE]]></author>
      <enclosure url="https://d15shllkswkct0.cloudfront.net/wp-content/blogs.dir/1/files/2026/06/Danny-Nicolopoulos-head-of-strategic-partnerships-at-TwelveLabs-AWS-Marketplace-Series-2026.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Overcast and TwelveLabs Redefine Enterprise Video]]></title>
      <link><![CDATA[https://content-technology.com/media-in-the-cloud/overcast-and-twelvelabs-redefine-enterprise-video/]]></link>
      <guid isPermaLink="false">ca5903df-a7d2-4cc6-b0d6-accf5f70e52f</guid>
      <pubDate>Thu, 21 May 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[Overcast and TwelveLabs have formed a partnership to integrate AI-powered video understanding and workflow automation into enterprise content operations. The collaboration aims to enhance how businesses manage and utilize their video content.]]></description>
      <content:encoded><![CDATA[Overcast and TwelveLabs have formed a partnership to integrate AI-powered video understanding and workflow automation into enterprise content operations. The collaboration aims to enhance how businesses manage and utilize their video content.]]></content:encoded>
      <dc:creator><![CDATA[Content+Technology]]></dc:creator>
      <author><![CDATA[Content+Technology]]></author>
      <enclosure url="https://content-technology.com/wp-content/uploads/2026/05/Overcast-and-12.jpg" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Vespa Integrates TwelveLabs for Scalable Video Retrieval]]></title>
      <link><![CDATA[https://letsdatascience.com/news/vespa-integrates-twelvelabs-for-scalable-video-retrieval-f2379ce4]]></link>
      <guid isPermaLink="false">244f8eb9-2fe4-4a6b-9882-700fb8258c6e</guid>
      <pubDate>Sun, 26 Apr 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[Vespa, a vector search engine, has published a guide demonstrating an integration with video understanding AI company TwelveLabs. The integration allows for scalable semantic video search using TwelveLabs' `Marengo-retrieval-2.7` embedding model. The announcement was made via a Vespa blog post detailing a quick-start implementation.]]></description>
      <content:encoded><![CDATA[Vespa, a vector search engine, has published a guide demonstrating an integration with video understanding AI company TwelveLabs. The integration allows for scalable semantic video search using TwelveLabs' `Marengo-retrieval-2.7` embedding model. The announcement was made via a Vespa blog post detailing a quick-start implementation.]]></content:encoded>
      <dc:creator><![CDATA[letsdatascience.com]]></dc:creator>
      <author><![CDATA[letsdatascience.com]]></author>
      
    </item>

    <item>
      <title><![CDATA[AWS Partners driving AI adoption and bringing the future to life for media and entertainment customers worldwide]]></title>
      <link><![CDATA[https://aws.amazon.com/blogs/media/aws-partners-driving-ai-adoption-and-bringing-the-future-to-life-for-media-and-entertainment-customers-worldwide/]]></link>
      <guid isPermaLink="false">d299caab-4330-4264-a96e-d8f660fcbd90</guid>
      <pubDate>Thu, 23 Apr 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[An AWS blog post recaps a podcast with partners Thoughtworks, TwelveLabs, and LucidLink on media and entertainment trends. The discussion covered the use of AI for semantic content understanding and automated editing (TwelveLabs), the shift to iterative, cloud-based workflows enabling remote collaboration (LucidLink), and the need for platform modernization to deliver personalized experiences (Thoughtworks). The common themes identified were the need for speed, personalization, and efficient cloud-based workflows to manage rising content volumes.]]></description>
      <content:encoded><![CDATA[An AWS blog post recaps a podcast with partners Thoughtworks, TwelveLabs, and LucidLink on media and entertainment trends. The discussion covered the use of AI for semantic content understanding and automated editing (TwelveLabs), the shift to iterative, cloud-based workflows enabling remote collaboration (LucidLink), and the need for platform modernization to deliver personalized experiences (Thoughtworks). The common themes identified were the need for speed, personalization, and efficient cloud-based workflows to manage rising content volumes.]]></content:encoded>
      <dc:creator><![CDATA[AWS for Media & Entertainment Blog]]></dc:creator>
      <author><![CDATA[AWS for Media & Entertainment Blog]]></author>
      <enclosure url="https://d2908q01vomqb2.cloudfront.net/fb644351560d8296fe6da332236b1f8d61b2828a/2026/04/19/AWS-Partners-driving-AI-adoption-and-bringing-the-future-to-life-for-media-and-entertainment-customers-worldwide.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Quickplay Expands AI Partnerships with AWS and Twelve Labs]]></title>
      <link><![CDATA[https://twitter.com/AWSInsider/status/2042241691294310550]]></link>
      <guid isPermaLink="false">343e4c25-4c03-4f28-bed3-2ddcf1e153ab</guid>
      <pubDate>Thu, 09 Apr 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[Quickplay announced expanded partnerships with AWS and Twelve Labs to integrate cloud infrastructure and video understanding technology into AI-driven media workflows. The collaboration is positioned to support capabilities such as workflow automation and personalization for streaming/OTT use cases.]]></description>
      <content:encoded><![CDATA[Quickplay announced expanded partnerships with AWS and Twelve Labs to integrate cloud infrastructure and video understanding technology into AI-driven media workflows. The collaboration is positioned to support capabilities such as workflow automation and personalization for streaming/OTT use cases.]]></content:encoded>
      <dc:creator><![CDATA[AWS Insider]]></dc:creator>
      <author><![CDATA[AWS Insider]]></author>
      <enclosure url="Unable to Scrape" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Mapping the Future of Interactive Streaming and Commerce Technologies]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/karl-l-b525ab399_nabshow-streaming-ctv-activity-7443221546682368002-LLbm?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGY1QlkBUQ8oR4MogZEiG19JkX81qCrmZpY]]></link>
      <guid isPermaLink="false">4f9b0539-55aa-4b4f-9c65-6cb2a2f425fa</guid>
      <pubDate>Fri, 27 Mar 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[MONETIZATION_AND_AD_TECH]]></category>
      <description><![CDATA[The post highlights an emerging trend at the intersection of CTV/FAST, metadata intelligence, interactive advertising, and commerce-enabled streaming ahead of the April NAB Show. It calls out vendors including ThinkAnalytics, Comcast Technology Solutions, Amagi, Frequency, and Sound Dimension for capabilities spanning metadata enrichment, contextual ad delivery, FAST channel creation/monetization, and second-screen synchronized “scene commerce,” and lists additional companies to watch such as Viaccess-Orca, Accedo.tv, TwelveLabs, Yospace, and Brightcove.]]></description>
      <content:encoded><![CDATA[The post highlights an emerging trend at the intersection of CTV/FAST, metadata intelligence, interactive advertising, and commerce-enabled streaming ahead of the April NAB Show. It calls out vendors including ThinkAnalytics, Comcast Technology Solutions, Amagi, Frequency, and Sound Dimension for capabilities spanning metadata enrichment, contextual ad delivery, FAST channel creation/monetization, and second-screen synchronized “scene commerce,” and lists additional companies to watch such as Viaccess-Orca, Accedo.tv, TwelveLabs, Yospace, and Brightcove.]]></content:encoded>
      <dc:creator><![CDATA[Karl L]]></dc:creator>
      <author><![CDATA[Karl L]]></author>
      
    </item>

    <item>
      <title><![CDATA[Gesture-controlled 3D Semantic Video Search]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/garystafford_generativeai-twelvelabs-aws-activity-7441846305762557952-e3Rj?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGYCJ4IBdJ3oFCAy65Utl9GekfXU7-7t8AQ]]></link>
      <guid isPermaLink="false">fd8972cf-7a65-4301-8cd3-21f27d3e825c</guid>
      <pubDate>Mon, 23 Mar 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[Gary Stafford describes a prototype called Nebula, an AI-powered content intelligence tool that performs semantic video search and displays results as an interactive 3D visualization navigable via hand gestures and voice commands. The system uses TwelveLabs models (Marengo and Pegasus) on AWS Bedrock for multimodal video understanding, Amazon OpenSearch Serverless for vector search, Lambda for orchestration, and CloudFront for delivery, with on-device gesture inference and 3D rendering via WebAssembly.]]></description>
      <content:encoded><![CDATA[Gary Stafford describes a prototype called Nebula, an AI-powered content intelligence tool that performs semantic video search and displays results as an interactive 3D visualization navigable via hand gestures and voice commands. The system uses TwelveLabs models (Marengo and Pegasus) on AWS Bedrock for multimodal video understanding, Amazon OpenSearch Serverless for vector search, Lambda for orchestration, and CloudFront for delivery, with on-device gesture inference and 3D rendering via WebAssembly.]]></content:encoded>
      <dc:creator><![CDATA[Gary Stafford]]></dc:creator>
      <author><![CDATA[Gary Stafford]]></author>
      
    </item>

    <item>
      <title><![CDATA[Building Pegasus 1.5: From Clip-Based QA to Time-Based Metadata]]></title>
      <link><![CDATA[https://www.twelvelabs.io/blog/introducing-pegasus-1-5]]></link>
      <guid isPermaLink="false">627c1976-70b4-4afc-b65e-5e6c9f987ac6</guid>
      <pubDate>Fri, 29 May 2026 04:39:39 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[Twelve Labs introduced Pegasus 1.5, an update to its AI model that transforms video into structured, time-based metadata. This version utilizes schema-driven segmentation, custom evaluation metrics, and reinforcement learning to align with real-world video workflows.]]></description>
      <content:encoded><![CDATA[Twelve Labs introduced Pegasus 1.5, an update to its AI model that transforms video into structured, time-based metadata. This version utilizes schema-driven segmentation, custom evaluation metrics, and reinforcement learning to align with real-world video workflows.]]></content:encoded>
      <dc:creator><![CDATA[Twelve Labs]]></dc:creator>
      <author><![CDATA[Twelve Labs]]></author>
      <enclosure url="https://framerusercontent.com/images/vjne4CkTndBiJt2JgW9oPALmU.png?width=9600&amp;height=5040" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Marengo 3.0: Real-World Multimodal Embedding AI]]></title>
      <link><![CDATA[https://www.twelvelabs.io/blog/marengo-3-0]]></link>
      <guid isPermaLink="false">d057db49-8f0c-47e9-a1b0-2c2aedcfe639</guid>
      <pubDate>Fri, 29 May 2026 04:39:19 GMT</pubDate>
      <category><![CDATA[ARTIFICIAL_INTELLIGENCE_FOR_VIDEO_APPLICATIONS]]></category>
      <description><![CDATA[TwelveLabs has announced Marengo 3.0, a new multimodal embedding model designed for video retrieval. This iteration supports advanced features including composed queries, multilingual search capabilities, and the processing of long-form video content.]]></description>
      <content:encoded><![CDATA[TwelveLabs has announced Marengo 3.0, a new multimodal embedding model designed for video retrieval. This iteration supports advanced features including composed queries, multilingual search capabilities, and the processing of long-form video content.]]></content:encoded>
      <dc:creator><![CDATA[Twelve Labs]]></dc:creator>
      <author><![CDATA[Twelve Labs]]></author>
      <enclosure url="https://framerusercontent.com/assets/IEAmqfsHng0UfGP2QqP05gAfA.png" type="image/jpeg" length="0"/>
    </item>
  </channel>
</rss>