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272 273<style id="wp-custom-css"> 274/* Fix for iframe in the full width template */ 275.full-width-layout__article-copy-section { 276 .full-width-layout__copy { 277 p:has(iframe[src*="youtube.com"]), p:has(iframe[src*="youtu.be"]) { 278 aspect-ratio: 16 / 9; 279 max-width: 100%; 280 width: 100%; 281 282 iframe { 283 height: 100%; 284 width: 100%; 285 } 286 @media (min-width: 640px) and (max-width: 1024px) { 287 max-width: 630px; 288 left: 50%; 289 position: relative; 290 transform: translateX(-50%); 291 width: min(100vw, 630px); 292 293 } 294 @media (min-width: 1025px) and (max-width: 1350px) { 295 max-width: 954px; 296 left: 50%; 297 position: relative; 298 transform: translateX(-50%); 299 width: min(100vw, 954px); 300 } 301 @media (min-width: 1351px) { 302 left: 50%; 303 max-width: 1070px; 304 position: relative; 305 transform: translateX(-50%); 306 width: min(100vw, 1070px); 307 } 308 } 309 } 310} 311 312.full-width-layout__sections { 313 a { 314 text-decoration-color: #76b900 !important; 315 } 316} 317.full-width-layout__copy { p, h1, h2, h3, h4, h5, h6, ol, ul, dl, address, table, figure, pre { margin-bottom: 15px; 318 } h1, h2, h3, h4, h5, h6 { 319 margin-top: 15px; 320 } 321 ol, ul { 322 padding-left: 20px; 323 } 324 li ol, 325 li ul { 326 margin-bottom: 0; 327 } 328 dd { 329 margin-left: 10px; 330 } 331 blockquote { 332 margin-inline: 10px; 333 } 334 p:last-child, 335 h1:last-child, h2:last-child, h3:last-child, 336 h4:last-child, h5:last-child, h6:last-child { 337 margin-bottom: 0; 338 } 339 } 340 341.wp-theme-nvidia-blog-v6.single-post { 342 .nvidia-content { 343 h1, h2, h3, h4, h5, h6 { 344 margin-bottom: 15px; 345 } 346 figure { 347 width: 100% !important; 348 padding: 15px 0 5px 0; 349 margin-bottom: 15px; 350 figcaption { 351 margin: 5px 0; 352 } 353 } 354 figure.alignleft,figure.alignright { 355 width: 100% !important; 356 padding: 15px 0 5px 0; 357 margin-bottom: 15px; 358 text-align:center; 359 img { 360 width: auto; 361 margin: 0 auto; 362 } 363 figcaption { 364 margin: 5px 0; 365 } 366 } 367 } 368} 369 370/** GTC FIX FOR SCROLLING **/ 371.full-width-layout__article-copy-section { 372 & .full-width-layout__copy { 373 & p:has(iframe[src*="youtube.com"]), & p:has(iframe[src*="youtu.be"]) { 374 iframe { 375 aspect-ratio: 16 / 9; 376 } 377 } 378 } 379} 380 381body.postid-91623 { 382.full-width-layout { 383 .full-width-layout-container { 384 video { 385 aspect-ratio: 16 / 9; 386 } 387 } 388} 389} 390 391/** GTC FIX FOR SCROLLING **/ 392 393 394</style> 395</head> 396 397<body class="wp-singular post-template-default single single-post postid-98109 single-format-standard wp-embed-responsive wp-theme-nvidia-blog-v6 site-lang-en group-blog has-body"> 398<img src="https://www.nvidia.com/content/dam/1x1-00000000.png" width="1" height="1" style="display:none;" alt="country_code"> 399<div id="page" class="site"> 400 <a class="skip-link screen-reader-text" href="#primary">Skip to content</a> 401 402 <div id="nvidia-header"></div> 403<div id="primary" class="content-area"> 404 <main id="main" class="site-main" role="main"> 405 <div class="nvidia-container"> 406 <article 407 id="post-98109" 408 class="post-with-sidebar grid grid-cols-1 laptop:grid-cols-4 desktop:grid-cols-4 w-full gap-[30px] post-98109 post type-post status-publish format-standard has-post-thumbnail hentry category-generative-ai category-pro-graphics tag-artificial-intelligence tag-events tag-holoscan-for-media tag-media-and-entertainment tag-nvidia-nim" data-url="https://blogs.nvidia.com/blog/ibc-news-2026/" 409 data-identifier="98109 https://blogs.nvidia.com/?p=98109" 410 data-title="NVIDIA Brings Real-Time AI to Broadcast, Sports and Global Streaming at IBC"> 411 412 <header class="entry-header laptop:col-span-4 desktop:col-span-4"> 413 <div class="inner3"> 414 <!-- TITLE --> 415 <h1 class="nvidia-heading-large mb-[15px]">NVIDIA Brings Real-Time AI to Broadcast, Sports and Global Streaming at IBC</h1> 416 <div class="author_meta text-xs text-nvidia-text-tertiary mb-[15px]"> 417 <span class="entry-date">September 9, 2026</span> <span class="meta-sep">by</span> <span class="author vcard">
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553At IBC 2026 in Amsterdam, NVIDIA announced a major expansion to NVIDIA AI for Media — a collection of GPU-accelerated software development kits (SDKs), NVIDIA NIM microservices, playbooks, and blueprints that enhance audio, video and augmented-reality effects for media and entertainment workflows — to unlock new ways to understand motion, verify and enhance video, localize programming and build AI-powered media applications. </span></p> 554<p><span style="font-weight: 400;">The </span><a target="_blank" href="https://build.nvidia.com/nvidia/synthetic-video-detector"><b>NVIDIA Synthetic Video Detector</b></a><b> (SVD)</b><span style="font-weight: 400;"> NIM microservice, announced earlier this year at </span><a href="https://blogs.nvidia.com/blog/siggraph-news-2026/#synthetic-video"><span style="font-weight: 400;">SIGGRAPH</span></a><span style="font-weight: 400;">,</span> <span style="font-weight: 400;">helps organizations assess the probability of whether footage is authentic or AI-generated, giving editorial, content-authentication, digital-forensics and media-integrity teams another point of analysis in their review process.</span></p> 555<p><span style="font-weight: 400;">Since its initial release, SVD’s accuracy has reached 99.3% for text-to-video content and 97.7% for image-to-video content, with especially large gains on difficult image-to-video cases. </span></p> 556<p><span style="font-weight: 400;">Dalet is integrating SVD into a secure, cloud-hosted verification workflow for news organizations. This allows editorial teams to submit footage through SVD, inspect and review the resulting scores and metadata within a Dalet interface. </span></p> 557<p><span style="font-weight: 400;">TwelveLabs announced the general availability of Compliance by TwelveLabs, its first application built on the company’s video intelligence platform, helping media and broadcast teams rapidly screen content against regional and custom compliance standards. The solution integrates SVD to add frame-level authenticity signals and confidence scores, enabling media teams to identify potentially synthetic media within the same compliance workflow.</span></p> 558<p><span style="font-weight: 400;">Wowza</span><i><span style="font-weight: 400;">, </span></i><span style="font-weight: 400;">whose</span> <a target="_blank" href="https://www.wowza.com/streaming-engine"><span style="font-weight: 400;">Wowza Streaming Engine</span></a><span style="font-weight: 400;"> media server technology powers more than 35,000 video deployments across over 170 countries, will distribute SVD through the</span> <a target="_blank" href="https://www.wowza.com/video-intelligence-framework"><span style="font-weight: 400;">Wowza Video Intelligence Framework</span></a><span style="font-weight: 400;">. The solution, powered by NVIDIA-accelerated infrastructure, will enable broadcasters, streaming providers and other organizations to analyze live video feeds and extract data around detected objects, scenes and signs of AI generation in real time. It can be deployed and run on premises, at the edge, in the cloud, across hybrid deployments or fully air-gapped, giving organizations greater control over critical media workflows.</span></p> 559<p><b>NVIDIA 3D Body Pose </b><span style="font-weight: 400;">estimates 2D and 3D human joint locations and angles from video captured by a single camera, helping turn motion into structured data without marker-based capture systems.</span></p> 560<p><span style="font-weight: 400;">For sports organizations, that data can support player and athlete movement tracking, biomechanics and performance analysis, replay enhancement, officiating and adjudication workflows, player-safety applications, and virtual interaction and immersive experiences. </span></p> 561<p><span style="font-weight: 400;">The technology can also provide structured human-motion data for content-creation workflows. When mapped to a compatible character rig, joint and motion data can serve as input for animation blocking, digital doubles, character retargeting and virtual-production experiences.</span></p> 562<p><span style="font-weight: 400;">Vizrt is using Body Pose technology in live virtual-studio environments, with tracked body movement driving real-time 3D lighting effects such as reflections, shadows and environmental rendering.</span></p> 563<p><b>Video Frame Generation (VFG) </b><span style="font-weight: 400;">makes video motion appear smoother by using generative AI to create new frames between the original frames of a video. It can increase frame rates by 2x or 4x while preserving visual quality and temporal consistency, enabling more fluid sports, slow-motion replays, live media and other high-motion video experiences. VFG also supports frame-rate conversion and frame boosting for generative AI video workflows.</span></p> 564<p><span style="font-weight: 400;">
564Ross Video is integrating VFG into its Rio Replay platform to create AI-assisted slow-motion video for sports production.</span></p> 565<p><span style="font-weight: 400;">The work supports 6x slow-motion generation for sports replay. Development is underway toward 8x interpolation, meaning generated intermediate frames can give replay teams smoother motion without requiring every frame to be captured by an ultrahigh-frame-rate source camera. </span></p> 566<p><b>NVIDIA Video Super Resolution</b><span style="font-weight: 400;"> (VSR) uses AI to upscale video while reducing noise, blur and compression artifacts. New streaming modes let developers choose between real-time performance and higher image quality, while adjustable controls help achieve the desired level of enhancement. VSR also adds 10-bit video support and improves overall performance and quality. VSR is available through the NVIDIA Video Effects SDK and a NIM microservice for use in streaming, broadcast, conferencing, video playback and content-creation applications. </span></p> 567<p><span style="font-weight: 400;">The technology can support video players, conferencing applications, creator tools, streaming services, transcoders and broadcast systems through a common interface.</span></p> 568<p><b>NVIDIA TrueHDR</b><span style="font-weight: 400;"> converts standard-dynamic-range video into high-dynamic-range output in real time, reaching up to approximately 2,000 nits while preserving local contrast and adapting brightness to the content.</span></p> 569<p><span style="font-weight: 400;">VSR, VFG and TrueHDR can be combined within a single video-effects pipeline — helping media companies enhance existing content libraries for streaming, transcoding, gaming and creator workflows.  </span></p> 570<p><span style="font-weight: 400;">The </span><a target="_blank" href="https://build.nvidia.com/nvidia/lipsync"><b>NVIDIA LipSync</b></a><span style="font-weight: 400;"> and </span><a target="_blank" href="https://build.nvidia.com/nvidia/active-speaker-detection"><b>Active Speaker Detection</b></a><span style="font-weight: 400;"> NIM microservices help developers build localization systems for interviews, news, sports, entertainment and other programming where multiple people may appear on screen.</span></p> 571<p><span style="font-weight: 400;">LipSync transforms mouth movement in an input video to match a target audio track while preserving natural head pose, blinking and body movement. The new release improves facial occlusion handling and better preserves teeth, lip and facial textures.</span></p> 572<p><span style="font-weight: 400;">The new Active Speaker Detection NIM microservice no longer requires speaker diarization for multiple audio tracks, adds voice activity detection and expands NIM microservice deployment support through a gRPC interface and broader GPU compatibility.</span></p> 573<p><a target="_blank" href="https://ndi.video/stories/press/ndi-nvidia-ai-multilingual-content/"><span style="font-weight: 400;">NDI</span></a> <span style="font-weight: 400;">is using NVIDIA AI for Media, including the NVIDIA LipSync NIM microservice, to enable real-time translation, lip-synced dubbing and regional language adaptation within existing broadcast workflows. By generating multiple language experiences from a common media stream, the approach can help broadcasters reach global audiences while reducing the bandwidth, infrastru
573cture and production complexity traditionally required for multilingual distribution.</span></p> 574<p><b>Studio Voice </b><span style="font-weight: 400;">includes new Microphone Profiles built on NVIDIA Studio Voice NIM microservices, giving users more control over the tonal character of enhanced speech.</span></p> 575<p><span style="font-weight: 400;">The capability is designed to suppress background noise, reduce room reverberation and improve speech clarity, then shape the enhanced output into a selected microphone profile for more polished live communications, streaming, podcasting and content creation.</span></p> 576<p><i><span style="font-weight: 400;">Try </span></i><a target="_blank" href="https://build.nvidia.com/models?label=nvidia+ai+for+media"><i><span style="font-weight: 400;">NVIDIA AI for Media NIM microservices</span></i></a><i><span style="font-weight: 400;">. See the latest NVIDIA and partner workflows at </span></i><a target="_blank" href="https://www.nvidia.com/en-us/events/ibc/"><i><span style="font-weight: 400;">IBC 2026</span></i></a><i><span style="font-weight: 400;">. </span></i></p> 577<hr /> 578<h2 id="mxl"><b>NVIDIA Holoscan for Media Provides Open Media Exchange Layer to Build and Connect Live Media Applications </b><a href="https://blogs.nvidia.com/blog/ibc-news-2026/#mxl"><b><em>🔗</em></b></a><b></b><b></b></h2> 579<p><img decoding="async" class="alignnone size-large wp-image-98113" src="https://blogs.nvidia.com/wp-content/uploads/2026/09/holoscan-for-media-1920x1080-1-1680x945.jpg" alt="" width="1200" height="675" srcset="https://blogs.nvidia.com/wp-content/uploads/2026/09/holoscan-for-media-1920x1080-1-1680x945.jpg 1680w, https://blogs.nvidia.com/wp-content/uploads/2026/09/holoscan-for-media-1920x1080-1-960x540.jpg 960w, https://blogs.nvidia.com/wp-content/uploads/2026/09/holoscan-for-media-1920x1080-1-1280x720.jpg 1280w, https://blogs.nvidia.com/wp-content/uploads/2026/09/holoscan-for-media-1920x1080-1-1536x864.jpg 1536w, https://blogs.nvidia.com/wp-content/uploads/2026/09/holoscan-for-media-1920x1080-1-1290x725.jpg 1290w, https://blogs.nvidia.com/wp-content/uploads/2026/09/holoscan-for-media-1920x1080-1-630x354.jpg 630w, https://blogs.nvidia.com/wp-content/uploads/2026/09/holoscan-for-media-1920x1080-1-300x169.jpg 300w, https://blogs.nvidia.com/wp-content/uploads/2026/09/holoscan-for-media-1920x1080-1-400x225.jpg 400w, https://blogs.nvidia.com/wp-content/uploads/2026/09/holoscan-for-media-1920x1080-1.jpg 1920w" sizes="(max-width: 1200px) 100vw, 1200px" /></p> 580<p><span style="font-weight: 400;">As broadcasters, streaming services and sports organizations adopt software and AI, the infrastructure behind live content is becoming more flexible, more connected and increasingly built on shared accelerated computing.</span></p> 581<p><span style="font-weight: 400;">The integration of Media Exchange Layer (MXL) with </span><a target="_blank" href="https://developer.nvidia.com/holoscan-for-media"><span style="font-weight: 400;">NVIDIA Holoscan for Media</span></a><span style="font-weight: 400;"> accelerates that transition — providing the common exchange layer that helps media applications connect and operate together. </span></p> 582<p><span style="font-weight: 400;">Holoscan for Media is an open reference architecture and developer toolkit for building AI-powered media functions and applications for software-defined live production. MXL adds an open way for those software-based media functions to exchange live video, audio and data across a distributed environment. </span></p> 583<p><span style="font-weight: 400;">As production functions move into software, developers can build applications that share accelerated infrastructure, connect dynamically and evolve independently. That can help media companies use infrastructure more efficiently, introduce new capabilities faster and reduce the amount of custom integration required between applications.</span></p> 584<p><span style="font-weight: 400;">The integration also creates a stronger foundation for AI in live media. AI processing, video applications and traditional media functions can increasingly operate on the same accelerated infrastru
584cture and in the same software-defined environment.</span></p> 585<p><span style="font-weight: 400;">For technology vendors, this expands the opportunity to build applications that can work across broader, multi-vendor ecosystems. For media companies, it creates a path toward infrastructure that can adapt as formats, applications and AI capabilities change.</span></p> 586<p><i><span style="font-weight: 400;">See the demo at IBC in </span></i><a target="_blank" href="https://directory.ibc.org/8_0/floorplan/?hallID=F&level=1&st=exhibitor&selectedBooth=booth%7E10.D21"><i><span style="font-weight: 400;">EBU Stand 10.D21</span></i></a><i><span style="font-weight: 400;">. ​Learn more about </span></i><a target="_blank" href="https://developer.nvidia.com/holoscan-for-media"><i><span style="font-weight: 400;">Holoscan for Media</span></i></a><i><span style="font-weight: 400;">.</span></i></p> 587<hr /> 588<h2 id="sports-intelligence-playbooks"><b>NVIDIA Sports Intelligence Playbooks Chart a Path to Multimodal AI for Sports </b><a href="https://blogs.nvidia.com/blog/ibc-news-2026/#sports-intelligence-playbooks"><b><em>🔗</em></b></a><b></b><b></b></h2> 589<p><img decoding="async" class="alignnone size-large wp-image-98118" src="https://blogs.nvidia.com/wp-content/uploads/2026/09/sports-intelligence-playbooks-1920x1080-1-1680x945.jpg" alt="" width="1200" height="675" srcset="https://blogs.nvidia.com/wp-content/uploads/2026/09/sports-intelligence-playbooks-1920x1080-1-1680x945.jpg 1680w, https://blogs.nvidia.com/wp-content/uploads/2026/09/sports-intelligence-playbooks-1920x1080-1-960x540.jpg 960w, https://blogs.nvidia.com/wp-content/uploads/2026/09/sports-intelligence-playbooks-1920x1080-1-1280x720.jpg 1280w, https://blogs.nvidia.com/wp-content/uploads/2026/09/sports-intelligence-playbooks-1920x1080-1-1536x864.jpg 1536w, https://blogs.nvidia.com/wp-content/uploads/2026/09/sports-intelligence-playbooks-1920x1080-1-1290x725.jpg 1290w, https://blogs.nvidia.com/wp-content/uploads/2026/09/sports-intelligence-playbooks-1920x1080-1-630x354.jpg 630w, https://blogs.nvidia.com/wp-content/uploads/2026/09/sports-intelligence-playbooks-1920x1080-1-300x169.jpg 300w, https://blogs.nvidia.com/wp-content/uploads/2026/09/sports-intelligence-playbooks-1920x1080-1-400x225.jpg 400w, https://blogs.nvidia.com/wp-content/uploads/2026/09/sports-intelligence-playbooks-1920x1080-1.jpg 1920w" sizes="(max-width: 1200px) 100vw, 1200px" /></p> 590<p><span style="font-weight: 400;">Sports is becoming a proving ground for a broader shift in AI: from general-purpose models toward fine-tuned open models built on proprietary data.</span></p> 591<p><span style="font-weight: 400;"><a target="_blank" href="https://nvidia.github.io/sports-intelligence-playbooks/latest/">NVIDIA Sports Intelligence Playbooks</a> are designed to accelerate that transition. They give leagues, media companies and technology providers structured frameworks to fine-tune NVIDIA open models on their own sports footage and annotations, creating multimodal AI that can understand the rules, players, scoring, strategy and context unique to a sport.</span></p> 592<p><span style="font-weight: 400;">Sports organizations hold large volumes of proprietary video, metadata and performance information that are difficult for competitors to replicate. The playbooks provide a practical blueprint for converting those assets into AI capabilities that can underpin new analytics products, media experiences, automation tools and revenue streams.</span></p> 593<p><span style="font-weight: 400;">The playbooks span the AI lifecycle, including data preparation, fine-tuning, inference, evaluation, optimization and deployment, and bring together NVIDIA technologies including </span><a target="_blank" href="https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/"><span style="font-weight: 400;">Nemotron</span></a><span style="font-weight: 400;">, </span><a target="_blank" href="https://docs.nvidia.com/nemo/automodel"><span style="font-weight: 400;">NeMo AutoModel</span></a><span style="font-weight: 400;">, </span><a target="_blank" href="https://docs.nvidia.com/nemo/megatron-bridge/latest/"><span style="font-weight: 400;">Megatron Bridge</span></a><span style="font-weight: 400;">, </span>
593<a target="_blank" href="https://www.nvidia.com/en-us/ai-data-science/products/nim-microservices/"><span style="font-weight: 400;">NIM microservices</span></a><span style="font-weight: 400;"> and </span><a target="_blank" href="https://www.nvidia.com/en-us/data-center/solutions/accelerated-computing/"><span style="font-weight: 400;">NVIDIA accelerated computing</span></a><span style="font-weight: 400;">. </span></p> 594<p><span style="font-weight: 400;">By providing an integrated path from model customization to production, Sports Intelligence Playbooks can reduce the cost and complexity of building specialized sports AI while increasing demand across its compute, software and inference stack.</span></p> 595<p><span style="font-weight: 400;">Early testing demonstrates the potential of domain specialization. When evaluated on previously unseen footage using question formats similar to those used in training, multiple-choice accuracy increased from approximately 53% to 94% and open-ended evaluation from approximately 5.7% to 66%.</span></p> 596<p><span style="font-weight: 400;">Machina Sports is integrating Sports Intelligence Playbooks with its sports-native data, evaluation and agent infrastru
596cture, enabling rights holders to turn proprietary media and expertise into private, deployable intelligence for live production, content and fan experiences.</span></p> 597<p><span style="font-weight: 400;">The opportunity also expands as agentic AI becomes increasingly adopted. With the </span><a target="_blank" href="https://build.nvidia.com/nvidia/aiq"><span style="font-weight: 400;">NVIDIA AI-Q Blueprint</span></a><span style="font-weight: 400;">, organizations can use their domain-specific sports models as expert intelligence within agents that reason across video, enterprise data and software systems, extending the playbook from sports understanding into decision-making and automation.</span></p> 598<p><span style="font-weight: 400;">Wowza is integrating vision language models, including NVIDIA Cosmos 3 and Nemotron, into the Wowza Video Intelligence Framework, fine-tuned through NVIDIA Sports Intelligence Playbooks to detect sports-specific moments in live streams and reduce time to action. </span></p> 599<p><i><span style="font-weight: 400;">Explore </span></i><a target="_blank" href="https://github.com/NVIDIA/sports-intelligence-playbooks"><i><span style="font-weight: 400;">NVIDIA Sports Intelligence Playbooks</span></i></a><i><span style="font-weight: 400;">.</span></i></p> 600<hr /> 601<h2 id="content-localization"><b>NVIDIA Brings Multilingual Content Localization to Live Broadcast </b><a href="https://blogs.nvidia.com/blog/ibc-news-2026/#content-localization"><b><em>🔗</em></b></a></h2> 602<p><span style="font-weight: 400;">Reaching global audiences with live programming requires more than translating words. Language nuances, voice, timing, facial movement, captions and onscreen graphics must work together in real time, while preserving the editorial intent and production quality of the original program.</span></p> 603<p><span style="font-weight: 400;">To help broadcasters, sports leagues, rights holders and streaming services bring these elements into a unified, software-defined, real-time localization workflow, NVIDIA is bringing its Content Localization technologies to the NVIDIA Holoscan for Media developer toolkit. Designed for broadcast and streaming developers, the reference workflow enables captions, translated audio, dubbing, synchronized video and localized graphics.</span></p> 604<p><span style="font-weight: 400;">Content Localization with Holoscan for Media provides a reference for how localization technologies can work together in software-defined broadcast applications. Developers can select the capabilities needed for each program, market or distribution channel rather than deploying separate infrastructure for every localized version.</span></p> 605<p><span style="font-weight: 400;">Content Localization with Holoscan for Media incorporates the latest advancements from NVIDIA AI for Media, including improved LipSync when faces are partially obscured and enhanced Active Speaker Detection to help applications identify who’s speaking in multi-person scenes.</span></p> 606<h3><b>Expanding the Reach of Live Programming</b></h3> 607<p><span style="font-weight: 400;">Localization can transform the reach and economics of live programming. A shared, composable workflow can help media companies introduce regional coverage faster, serve more audiences and tailor experiences for individual markets — while preserving the timing, visual context and editorial control required for live production.</span></p> 608<p><span style="font-weight: 400;">Technologies from </span><span style="font-weight: 400;">AI-Media</span><span style="font-weight: 400;">, </span><span style="font-weight: 400;">CAMB.AI</span><span style="font-weight: 400;">, Chyron and </span><span style="font-weight: 400;">Panjaya</span><span style="font-weight: 400;"> each address a specific part of content localization with Holoscan for Media, from adapting voice and onscreen delivery to creating multilingual captions and translated audio, localizing graphics, and preserving expression and identity across live and on-demand content.</span></p> 609<p><span style="font-weight: 400;">
609The Content Localization technologies also support file-based, streaming and post-production applications. Developers can use application programming interfaces for on-demand workflows and the Holoscan for Media reference workflow when localization must run as part of a live media environment. Together, they provide a consistent foundation for building multilingual media services across production and distribution.</span></p> 610<p><i><span style="font-weight: 400;">Learn more about NVIDIA </span></i><a target="_blank" href="https://developer.nvidia.com/holoscan-for-media"><i><span style="font-weight: 400;">Holoscan for Media</span></i></a><i><span style="font-weight: 400;"> and </span></i><a target="_blank" href="https://developer.nvidia.com/topics/ai/generative-ai/ai-for-media"><i><span style="font-weight: 400;">AI for Media</span></i></a><i><span style="font-weight: 400;">. </span></i></p> 611<div class="has-social-placeholder has-content-area" data-url="https://blogs.nvidia.com/blog/ibc-news-2026/" data-title="NVIDIA Brings Real-Time AI to Broadcast, Sports and Global Streaming at IBC" data-hashtags="" data-post-id="98109"></div> </div> 612 </div> 613 <div class="nvidia-sidebar order-last laptop:order-none desktop:order-none laptop:col-span-1 desktop:col-span-1"> 614 <div class="entry-sidebar"> 615 616<div id="secondary" class="single-latest-news-widget-area nvidia-sidebar" role="complementary"> 617 <aside id="nvb6_media_card-3" class="widget nvb6-media-card-widget"> 618<div class="media-card-widget nvidia-responsive-grid"> 619 620 <div class="media-card-container nvidia-full-width-content"> 621 <div class="media-card-image-container"> 622 <img src="https://blogs.nvidia.com/wp-content/uploads/2026/06/gtc26-berlin-open-reg-mktg-kit-corp-blog-1920x1080-1-1-960x540.jpg" alt="NVIDIA GTC Berlin Registration Is Now Open" width="960" height="540" class="media-card-image"> </div> 623 624 <div class="media-card-content"> 625 <div class="media-card-content-wrapper"> 626 <h3 class="media-card-title nvidia-heading-smaller"> 627 <a href="https://www.nvidia.com/en-eu/gtc/?nvid=nv-int-tblg-568814"> 628 NVIDIA GTC Berlin Registration Is Now Open </a> 629 </h3> 630 631 <div class="media-card-text nvidia-text-regular"> 632 <p>October 20-22</p> 633 </div> 634 635 <div class="media-card-cta"> 636 <a href="https://www.nvidia.com/en-eu/gtc/?nvid=nv-int-tblg-568814" class="nvidia-btn-secondary"> 637 Register Now <span class="nvidia-btn-secondary-icon"> 638 <svg width="20" height="20" viewBox="0 0 22 22" fill="none" stroke="currentColor" stroke-width="1.25" stroke-linecap="round" stroke-linejoin="round"> 639 <path d="M9 6l6 6-6 6"/> 640 </svg> 641 </span> 642 </a> 643 </div> 644 </div> 645 </div> 646 </div> 647</div></aside><aside id="nvb6_recent_news-2" class="widget nvb6-recent-news-widget"> 648<div class="recent-news-section nvidia-responsive-grid"> 649 <div class="recent-news-title flex gap-30"> 650 <h3 class="recent-news-title nvidia-heading-smaller">Recent News</h3> 651 </div> 652 653 <div class="recent-news-list nvidia-grid-tablet-2"> 654 <article class="recent-news-item recent-news-content-container"> 655 <div class="recent-news-content grid gap-10 justify-start"> 656 <div class="recent-news-category nvidia-badge"> 657 <a href="https://blogs.nvidia.com/blog/category/generative-ai/" class="primary-category-link">AI</a> </div> 658 659 <h3 class="recent-news-post-title nvidia-text-medium"> 660 <a href="https://blogs.nvidia.com/blog/ai-day-singapore/"> 661 At AI Day Singapore, NVIDIA and Partners Showcase AI Advancements Across Southeast Asia </a> 662 </h3> 663 <div class="recent-news-date nvidia-article-date"> 664 <time datetime="2026-09-22T19:30:22-07:00">September 22, 2026</time> </div> 665 </div> 666 </article> 667 <article class="recent-news-item recent-news-content-container"> 668 <div class="recent-news-content grid gap-10 justify-start"> 669 <div class="recent-news-category nvidia-badge"> 670 <a href="https://blogs.nvidia.com/blog/category/robotics/" class="primary-category-link">Robotics</a> </div> 671 672 <h3 class="recent-news-post-title nvidia-text-medium"> 673 <a href="https://blogs.nvidia.com/blog/isaac-ros-5-0-agentic-open-source-robotics/"> 674 NVIDIA Isaac ROS 5.0 Advances Agentic, Open Source Robotics Development </a> 675 </h3> 676 <div class="recent-news-date nvidia-article-date"> 677 <time datetime="2026-09-22T05:00:41-07:00">September 22, 2026</time> </div>
678 </div> 679 </article> 680 <article class="recent-news-item recent-news-content-container"> 681 <div class="recent-news-content grid gap-10 justify-start"> 682 <div class="recent-news-category nvidia-badge"> 683 <a href="https://blogs.nvidia.com/blog/category/corporate/" class="primary-category-link">Corporate</a> </div> 684 685 <h3 class="recent-news-post-title nvidia-text-medium"> 686 <a href="https://blogs.nvidia.com/blog/dsx-ready-ai-factories-power-cooling/"> 687 NVIDIA Launches DSX Ready to Qualify Power and Cooling Products for AI Factories </a> 688 </h3> 689 <div class="recent-news-date nvidia-article-date"> 690 <time datetime="2026-09-21T11:00:07-07:00">September 21, 2026</time> </div> 691 </div> 692 </article> 693 <article class="recent-news-item recent-news-content-container"> 694 <div class="recent-news-content grid gap-10 justify-start"> 695 <div class="recent-news-category nvidia-badge"> 696 <a href="https://blogs.nvidia.com/blog/category/robotics/" 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786 </div> 787 </article> 788 <article class="related-news-item related-news-content-container"> 789 <div class="related-news-content grid gap-10 justify-start"> 790 <div class="related-news-thumbnail mb-[20px]"> 791 <a href="https://blogs.nvidia.com/blog/cvpr-research-grasping-driving-agent-training/"> 792 <div class="aspect-[16/9]"><img width="300" height="169" src="https://blogs.nvidia.com/wp-content/uploads/2026/06/CVPR_blog_still-300x169.png" class="w-full h-full object-cover" alt="NVIDIA Research Unlocks Advanced Grasping, Smarter Autonomous Driving and Agent Training at Scale" sizes="auto, (max-width: 640px) 630px, (min-width: 640px) 300px, 100vw" decoding="async" loading="lazy" srcset="https://blogs.nvidia.com/wp-content/uploads/2026/06/CVPR_blog_still-300x169.png 300w, https://blogs.nvidia.com/wp-content/uploads/2026/06/CVPR_blog_still-960x540.png 960w, https://blogs.nvidia.com/wp-content/uploads/2026/06/CVPR_blog_still-1680x945.png 1680w, https://blogs.nvidia.com/wp-content/uploads/2026/06/CVPR_blog_still-1280x720.png 1280w, https://blogs.nvidia.com/wp-content/uploads/2026/06/CVPR_blog_still-1536x864.png 1536w, https://blogs.nvidia.com/wp-content/uploads/2026/06/CVPR_blog_still-scaled.png 2048w, https://blogs.nvidia.com/wp-content/uploads/2026/06/CVPR_blog_still-1290x725.png 1290w, https://blogs.nvidia.com/wp-content/uploads/2026/06/CVPR_blog_still-630x354.png 630w, https://blogs.nvidia.com/wp-content/uploads/2026/06/CVPR_blog_still-400x225.png 400w" /></div> </a> 793 </div> 794 <div class="related-news-category nvidia-badge"> 795 <a href="https://blogs.nvidia.com/blog/category/nvidia-research/" class="primary-category-link">Research</a> </div> 796 797 <h3 class="related-news-post-title nvidia-heading-smaller"> 798 <a href="https://blogs.nvidia.com/blog/cvpr-research-grasping-driving-agent-training/" class="text-[16px] xl:text-[20px]"> 799 NVIDIA Research Unlocks Advanced Grasping, Smarter Autonomous Driving and Agent Training at Scale </a> 800 </h3> 801 802 <time class="related-news-date nvidia-article-date" datetime="2026-06-03T08:00:57-07:00"> 803 Jun 3, 2026 </time> 804 </div> 805 </article> 806 </div> 807</div> 808</article> 809 </div> 810 </main><!-- #main --> 811</div><!-- #primary --> 812 813 <div id="nvidia-footer"></div> 814</div><!-- #page --> 815 816<link rel='stylesheet' id='highlight-and-share-css' href='https://blogs.nvidia.com/wp-content/plugins/highlight-and-share/dist/has-themes.css?ver=6.0.1' media='all' />
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939
940<script id="load-disqus-single-js" src="https://blogs.nvidia.com/wp-content/themes/nvidia-blog-v6/build/load-disqus.min.js"></script>
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945<script id="dsq-count-scr-js" src="https://nvidiablog.disqus.com/count.js"></script>
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946<script id="page-links-to-js" src="https://blogs.nvidia.com/wp-content/plugins/page-links-to/dist/new-tab.js?ver=3.4.1"></script>
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960
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Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.