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    <title><![CDATA[StreamingMeme — NETINT Technologies coverage]]></title>
    <link>https://www.streamingmeme.com</link>
    <description><![CDATA[Articles mentioning NETINT Technologies.]]></description>
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    <lastBuildDate>Fri, 11 Sep 2026 00:00:00 GMT</lastBuildDate>
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      <title><![CDATA[StreamingMeme — NETINT Technologies coverage]]></title>
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    <item>
      <title><![CDATA[NetActuate expands NETINT Quadra VPU-as-a-Service to 15 global locations]]></title>
      <link><![CDATA[https://cioinfluence.com/security/netactuate-expands-vpu-as-a-service-to-15-global-locations-with-netint-vpu-acceleration/]]></link>
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      <pubDate>Fri, 11 Sep 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NetActuate has expanded its VPU-as-a-Service offering to 15 global locations, utilizing NETINT Quadra video processing units. The service allows engineering teams to attach dedicated video silicon to virtual machines or Kubernetes nodes as an alternative to hyperscaler transcoding APIs.]]></description>
      <content:encoded><![CDATA[NetActuate has expanded its VPU-as-a-Service offering to 15 global locations, utilizing NETINT Quadra video processing units. The service allows engineering teams to attach dedicated video silicon to virtual machines or Kubernetes nodes as an alternative to hyperscaler transcoding APIs.]]></content:encoded>
      <dc:creator><![CDATA[CIO Influence]]></dc:creator>
      <author><![CDATA[CIO Influence]]></author>
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    <item>
      <title><![CDATA[MainConcept releases Codec SDK 17.0 with Arm and VPU transcoding support]]></title>
      <link><![CDATA[https://www.thebroadcastbridge.com/content/entry/22279/mainconcept-boosts-efficiency-at-ibc-2026?cat_id=134]]></link>
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      <pubDate>Fri, 11 Sep 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[MainConcept launched Codec SDK 17.0 at IBC 2026, featuring support for NETINT VPUs and NVIDIA GPUs on Linux Arm. The release also introduces new partnerships with Qualabs for real-time VMAF-E quality monitoring and Colorfront for MV-HEVC stereoscopic encoding for Apple Vision Pro.]]></description>
      <content:encoded><![CDATA[MainConcept launched Codec SDK 17.0 at IBC 2026, featuring support for NETINT VPUs and NVIDIA GPUs on Linux Arm. The release also introduces new partnerships with Qualabs for real-time VMAF-E quality monitoring and Colorfront for MV-HEVC stereoscopic encoding for Apple Vision Pro.]]></content:encoded>
      <dc:creator><![CDATA[The Broadcast Bridge]]></dc:creator>
      <author><![CDATA[The Broadcast Bridge]]></author>
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    <item>
      <title><![CDATA[Scalstrm and NETINT partner to reduce streaming TCO by 50 percent]]></title>
      <link><![CDATA[https://scalstrm.com/eu-cloud-sovereignty-has-a-deadline-operators-can-meet-it-without-paying-the-premium/]]></link>
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      <pubDate>Thu, 10 Sep 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[Scalstrm and NETINT have announced a video processing platform designed to meet upcoming EU Data Act sovereignty requirements. The solution utilizes NETINT video processing units to achieve claimed reductions in power consumption and total cost of ownership for broadcast-grade channel deployments.]]></description>
      <content:encoded><![CDATA[Scalstrm and NETINT have announced a video processing platform designed to meet upcoming EU Data Act sovereignty requirements. The solution utilizes NETINT video processing units to achieve claimed reductions in power consumption and total cost of ownership for broadcast-grade channel deployments.]]></content:encoded>
      <dc:creator><![CDATA[Scalstrm]]></dc:creator>
      <author><![CDATA[Scalstrm]]></author>
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    <item>
      <title><![CDATA[MainConcept adds Arm and NETINT VPU support to Easy Video API]]></title>
      <link><![CDATA[https://www.prlog.org/13169110-mainconcept-easy-video-api-extends-full-transcoding-to-arm-and-netint-vpus.html]]></link>
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      <pubDate>Tue, 08 Sep 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[MainConcept has expanded its Easy Video API to support video transcoding on NETINT video processing units and Arm-based systems utilizing NVIDIA GPUs. The update allows streaming providers to maintain a unified video stack across diverse hardware architectures without requiring separate codec integrations.]]></description>
      <content:encoded><![CDATA[MainConcept has expanded its Easy Video API to support video transcoding on NETINT video processing units and Arm-based systems utilizing NVIDIA GPUs. The update allows streaming providers to maintain a unified video stack across diverse hardware architectures without requiring separate codec integrations.]]></content:encoded>
      <dc:creator><![CDATA[PRLog]]></dc:creator>
      <author><![CDATA[PRLog]]></author>
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    <item>
      <title><![CDATA[MainConcept launches Codec SDK 17.0 with VVC and Arm hardware support]]></title>
      <link><![CDATA[https://blog.mainconcept.com/mainconcept-at-ibc2026?hsLang=en]]></link>
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      <pubDate>Fri, 04 Sep 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[MainConcept has released Codec SDK 17.0, featuring VVC efficiency improvements, expanded Arm-based hardware support for NVIDIA and NETINT, and MV-HEVC encoding for Apple Vision Pro. The update also introduces real-time VMAF-E quality monitoring through a partnership with Qualabs using CMSD/CMCD standards.]]></description>
      <content:encoded><![CDATA[MainConcept has released Codec SDK 17.0, featuring VVC efficiency improvements, expanded Arm-based hardware support for NVIDIA and NETINT, and MV-HEVC encoding for Apple Vision Pro. The update also introduces real-time VMAF-E quality monitoring through a partnership with Qualabs using CMSD/CMCD standards.]]></content:encoded>
      <dc:creator><![CDATA[MainConcept]]></dc:creator>
      <author><![CDATA[MainConcept]]></author>
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    <item>
      <title><![CDATA[Zapping reduces server count 75% using NETINT VPUs for live OTT]]></title>
      <link><![CDATA[https://netint.com/research/blog/zapping-live-streaming-netint-vpus/?utm_source=rss&utm_medium=rss&utm_campaign=zapping-live-streaming-netint-vpus]]></link>
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      <pubDate>Wed, 02 Sep 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[Latin American OTT platform Zapping migrated its live streaming infrastructure from CPU and GPU servers to NETINT VPUs. The transition reduced the company's server footprint by 75% and lowered encoding power consumption by 90% while supporting low-latency delivery for live sports.]]></description>
      <content:encoded><![CDATA[Latin American OTT platform Zapping migrated its live streaming infrastructure from CPU and GPU servers to NETINT VPUs. The transition reduced the company's server footprint by 75% and lowered encoding power consumption by 90% while supporting low-latency delivery for live sports.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
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    <item>
      <title><![CDATA[Scalstrm pairs NETINT VPUs with modular software for 110-channel rack density]]></title>
      <link><![CDATA[https://scalstrm.com/ibc2026-why-software-not-silicon-is-driving-10x-greater-video-processing-efficiency/]]></link>
      <guid isPermaLink="false">3a118e4a-a7ba-4bc4-a61e-193070a5b3a1</guid>
      <pubDate>Tue, 01 Sep 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[Scalstrm claims its software architecture enables 110 broadcast-grade HD channels per rack unit by utilizing NETINT video processing units. The company argues that modular, service-based software design is essential to fully leverage specialized hardware acceleration for improved density and power efficiency.]]></description>
      <content:encoded><![CDATA[Scalstrm claims its software architecture enables 110 broadcast-grade HD channels per rack unit by utilizing NETINT video processing units. The company argues that modular, service-based software design is essential to fully leverage specialized hardware acceleration for improved density and power efficiency.]]></content:encoded>
      <dc:creator><![CDATA[Scalstrm]]></dc:creator>
      <author><![CDATA[Scalstrm]]></author>
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    <item>
      <title><![CDATA[Scalstrm to demo 110 HD channels on one 1U server at IBC2026]]></title>
      <link><![CDATA[https://scalstrm.com/ibc-2026-the-software-behind-110-hd-channels-in-1u-a-new-economics-for-live-video/]]></link>
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      <pubDate>Thu, 27 Aug 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[Scalstrm has announced a microservice-native platform designed to transcode 110 HD channels in a single 1U rack unit using NETINT video processing units. The company claims this architecture reduces total cost of ownership by 50% by optimizing power consumption and hardware density.]]></description>
      <content:encoded><![CDATA[Scalstrm has announced a microservice-native platform designed to transcode 110 HD channels in a single 1U rack unit using NETINT video processing units. The company claims this architecture reduces total cost of ownership by 50% by optimizing power consumption and hardware density.]]></content:encoded>
      <dc:creator><![CDATA[Scalstrm]]></dc:creator>
      <author><![CDATA[Scalstrm]]></author>
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    <item>
      <title><![CDATA[Zixi and NETINT integrate VPUs for scalable live video transcoding]]></title>
      <link><![CDATA[https://netint.com/research/blog/reliable-live-video-processing/?utm_source=rss&utm_medium=rss&utm_campaign=reliable-live-video-processing]]></link>
      <guid isPermaLink="false">05eff3d8-4f03-40d2-a6fe-69ab80c9f256</guid>
      <pubDate>Mon, 24 Aug 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[Zixi and NETINT have published a technical overview detailing the integration of Zixi's software-based transport and control plane with NETINT's hardware-based video processing units. The collaboration aims to improve live streaming workflow reliability and transcoding density by offloading processing tasks from general-purpose CPUs to purpose-built hardware.]]></description>
      <content:encoded><![CDATA[Zixi and NETINT have published a technical overview detailing the integration of Zixi's software-based transport and control plane with NETINT's hardware-based video processing units. The collaboration aims to improve live streaming workflow reliability and transcoding density by offloading processing tasks from general-purpose CPUs to purpose-built hardware.]]></content:encoded>
      <dc:creator><![CDATA[NETINT]]></dc:creator>
      <author><![CDATA[NETINT]]></author>
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    <item>
      <title><![CDATA[NETINT and i3D.net Integrate Quadra VPUs for Latency-Sensitive Video Workloads]]></title>
      <link><![CDATA[https://netint.com/research/blog/performance-critical-video-workloads/]]></link>
      <guid isPermaLink="false">31a1a3df-217a-40da-a494-9965261a7d89</guid>
      <pubDate>Wed, 19 Aug 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT and i3D.net have announced a partnership to integrate NETINT's Quadra video processing units (VPUs) into i3D.net's managed bare metal and private cloud infrastructure. The collaboration aims to provide dedicated hardware-based encoding for latency-sensitive workloads such as cloud gaming and interactive streaming.]]></description>
      <content:encoded><![CDATA[NETINT and i3D.net have announced a partnership to integrate NETINT's Quadra video processing units (VPUs) into i3D.net's managed bare metal and private cloud infrastructure. The collaboration aims to provide dedicated hardware-based encoding for latency-sensitive workloads such as cloud gaming and interactive streaming.]]></content:encoded>
      <dc:creator><![CDATA[NETINT]]></dc:creator>
      <author><![CDATA[NETINT]]></author>
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    </item>

    <item>
      <title><![CDATA[NETINT details seven-step technical framework for VPU migration and infrastructure]]></title>
      <link><![CDATA[https://netint.com/research/blog/vpu-migration-video-pipeline/?utm_source=rss&utm_medium=rss&utm_campaign=vpu-migration-video-pipeline]]></link>
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      <pubDate>Tue, 28 Jul 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT Technologies has released a seven-step technical framework for migrating streaming video workloads from CPU-based processing to their Quadra Video Processing Units (VPUs). The guide provides engineering teams with recommended strategies for validating hardware, ensuring service equivalence through feature parity, and establishing reliable rollback paths during the transition.]]></description>
      <content:encoded><![CDATA[NETINT Technologies has released a seven-step technical framework for migrating streaming video workloads from CPU-based processing to their Quadra Video Processing Units (VPUs). The guide provides engineering teams with recommended strategies for validating hardware, ensuring service equivalence through feature parity, and establishing reliable rollback paths during the transition.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
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    <item>
      <title><![CDATA[NETINT Quadra VPU benchmarks reveal 7x throughput gain over CPUs]]></title>
      <link><![CDATA[https://netint.com/research/blog/cpu-vs-dedicated-video-hardware/?utm_source=rss&utm_medium=rss&utm_campaign=cpu-vs-dedicated-video-hardware]]></link>
      <guid isPermaLink="false">86bcdb23-fa57-40be-a15a-6b215ded7429</guid>
      <pubDate>Fri, 24 Jul 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT Technologies explains the operational advantages of using dedicated video processing units (VPUs) over general-purpose CPUs for video encoding pipelines. The technical breakdown details how keeping decode, scaling, and encode stages on a single hardware device reduces data bus contention and increases aggregate throughput for multi-session streaming workflows.]]></description>
      <content:encoded><![CDATA[NETINT Technologies explains the operational advantages of using dedicated video processing units (VPUs) over general-purpose CPUs for video encoding pipelines. The technical breakdown details how keeping decode, scaling, and encode stages on a single hardware device reduces data bus contention and increases aggregate throughput for multi-session streaming workflows.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
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    <item>
      <title><![CDATA[VPU shift over software: Priority for encoding moves to hardware architecture]]></title>
      <link><![CDATA[https://netint.com/research/blog/which-encoder-or-which-silicon/?utm_source=rss&utm_medium=rss&utm_campaign=which-encoder-or-which-silicon]]></link>
      <guid isPermaLink="false">5d51ebc3-0075-4d88-bac8-e5efa594283c</guid>
      <pubDate>Mon, 20 Jul 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT provides a technical argument for prioritizing silicon architectural selection over software-based encoder choice for video processing workflows. The analysis advocates for a heterogeneous compute model where purpose-built VPUs handle intensive video encoding to improve density and power efficiency relative to traditional CPU-based implementations.]]></description>
      <content:encoded><![CDATA[NETINT provides a technical argument for prioritizing silicon architectural selection over software-based encoder choice for video processing workflows. The analysis advocates for a heterogeneous compute model where purpose-built VPUs handle intensive video encoding to improve density and power efficiency relative to traditional CPU-based implementations.]]></content:encoded>
      <dc:creator><![CDATA[NETINT]]></dc:creator>
      <author><![CDATA[NETINT]]></author>
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    <item>
      <title><![CDATA[NETINT taps ZoneMinder developer to optimize AI-ready surveillance infrastructure]]></title>
      <link><![CDATA[https://www.youtube.com/watch?v=Unsy6f0SIEk]]></link>
      <guid isPermaLink="false">02f1670d-b476-47d3-998b-a0b70bd856ec</guid>
      <pubDate>Thu, 16 Jul 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT Technologies has hired developer Isaac Connor to integrate its video processing units (VPUs) with the open-source video management system ZoneMinder. The partnership aims to modernize legacy CCTV security infrastructure by leveraging hardware-accelerated decoding and AV1 encoding for improved efficiency and scalability.]]></description>
      <content:encoded><![CDATA[NETINT Technologies has hired developer Isaac Connor to integrate its video processing units (VPUs) with the open-source video management system ZoneMinder. The partnership aims to modernize legacy CCTV security infrastructure by leveraging hardware-accelerated decoding and AV1 encoding for improved efficiency and scalability.]]></content:encoded>
      <dc:creator><![CDATA[YouTube]]></dc:creator>
      <author><![CDATA[YouTube]]></author>
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    </item>

    <item>
      <title><![CDATA[NETINT advocates VPUs over CPUs to solve high-density encoding constraints]]></title>
      <link><![CDATA[https://netint.com/research/blog/encoding-efficiency-is-an-infrastructure-decision/?utm_source=rss&utm_medium=rss&utm_campaign=encoding-efficiency-is-an-infrastructure-decision]]></link>
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      <pubDate>Thu, 16 Jul 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT CMO Mark Donnigan argues that media companies should prioritize video processing units (VPUs) over general-purpose CPUs for large-scale encoding workloads to improve density and power efficiency. The article highlights the company's Quadra T1U hardware as a solution for achieving higher streams per server in modern data centers.]]></description>
      <content:encoded><![CDATA[NETINT CMO Mark Donnigan argues that media companies should prioritize video processing units (VPUs) over general-purpose CPUs for large-scale encoding workloads to improve density and power efficiency. The article highlights the company's Quadra T1U hardware as a solution for achieving higher streams per server in modern data centers.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
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    </item>

    <item>
      <title><![CDATA[AV1 adoption to hit 57% as AI moves into core encoding pipelines]]></title>
      <link><![CDATA[https://netint.com/2026-state-of-video-encoding/]]></link>
      <guid isPermaLink="false">415dcbad-8387-43bc-b0d5-ffc3cbed4b13</guid>
      <pubDate>Tue, 07 Jul 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[This report from NETINT surveys video encoding professionals on current and future trends including the adoption of AV1, the shift toward hybrid infrastructure, and growing integration of machine learning. The data highlights a transition away from GPU-only hardware and emphasizes that budget and capacity constraints remain the primary barriers to adoption for most organizations.]]></description>
      <content:encoded><![CDATA[This report from NETINT surveys video encoding professionals on current and future trends including the adoption of AV1, the shift toward hybrid infrastructure, and growing integration of machine learning. The data highlights a transition away from GPU-only hardware and emphasizes that budget and capacity constraints remain the primary barriers to adoption for most organizations.]]></content:encoded>
      <dc:creator><![CDATA[NETINT]]></dc:creator>
      <author><![CDATA[NETINT]]></author>
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    <item>
      <title><![CDATA[NETINT Quadra VPUs target CPU inefficiencies with high-density AV1 encoding]]></title>
      <link><![CDATA[https://netint.com/research/blog/av1-video-encoding-vpu/?utm_source=rss&utm_medium=rss&utm_campaign=av1-video-encoding-vpu]]></link>
      <guid isPermaLink="false">ceebcbf0-bbef-4d3d-92a2-6ed2a90106be</guid>
      <pubDate>Fri, 03 Jul 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT Technologies introduced its Quadra VPU product family, utilizing the company's Codensity G5 ASICs for hardware-based AV1, HEVC, and H.264 encoding. The product line is designed to replace CPU-based transcoding in data center, edge, and cloud gaming environments to increase stream density and reduce power consumption.]]></description>
      <content:encoded><![CDATA[NETINT Technologies introduced its Quadra VPU product family, utilizing the company's Codensity G5 ASICs for hardware-based AV1, HEVC, and H.264 encoding. The product line is designed to replace CPU-based transcoding in data center, edge, and cloud gaming environments to increase stream density and reduce power consumption.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
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    <item>
      <title><![CDATA[NETINT benchmarks claim VPUs deliver 5.8x better efficiency for AV1]]></title>
      <link><![CDATA[https://netint.com/scaling-av1-video-encoding/]]></link>
      <guid isPermaLink="false">a8e4a5ee-4ea1-4ded-9862-4bf05d72142e</guid>
      <pubDate>Mon, 29 Jun 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT published a technical blog post arguing that AV1 adoption at scale requires moving encoding workloads from CPUs to purpose-built video silicon. The post cites Quadra VPU benchmarks and quality tests claiming lower watts per stream and bitrate savings versus CPU/GPU-based approaches, including AV1 savings at 1080p and higher density at rack scale.]]></description>
      <content:encoded><![CDATA[NETINT published a technical blog post arguing that AV1 adoption at scale requires moving encoding workloads from CPUs to purpose-built video silicon. The post cites Quadra VPU benchmarks and quality tests claiming lower watts per stream and bitrate savings versus CPU/GPU-based approaches, including AV1 savings at 1080p and higher density at rack scale.]]></content:encoded>
      <dc:creator><![CDATA[NETINT]]></dc:creator>
      <author><![CDATA[NETINT]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/a8e4a5ee-4ea1-4ded-9862-4bf05d72142e.jpg" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[NETINT VPUs turn retired servers into 320-stream encoders]]></title>
      <link><![CDATA[https://netint.com/recommission-old-video-servers/]]></link>
      <guid isPermaLink="false">3ae49c4f-af8e-4695-8d38-1d7420862a31</guid>
      <pubDate>Thu, 25 Jun 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT advocates recommissioning decommissioned servers with its Video Processing Units (VPUs) to expand video encoding capacity. The approach offloads H.264, HEVC, and AV1 encoding to low-power VPUs, achieving up to 32 1080p30 streams per card. This method targets organizations facing GPU/server supply chain delays and seeks to free new servers for AI workloads.]]></description>
      <content:encoded><![CDATA[NETINT advocates recommissioning decommissioned servers with its Video Processing Units (VPUs) to expand video encoding capacity. The approach offloads H.264, HEVC, and AV1 encoding to low-power VPUs, achieving up to 32 1080p30 streams per card. This method targets organizations facing GPU/server supply chain delays and seeks to free new servers for AI workloads.]]></content:encoded>
      <dc:creator><![CDATA[NETINT]]></dc:creator>
      <author><![CDATA[NETINT]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/3ae49c4f-af8e-4695-8d38-1d7420862a31.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[NetActuate deploys NETINT VPUs for hardware-accelerated C-band to IP migration]]></title>
      <link><![CDATA[https://netactuate.com/blog/c-band-transition-extending-to-video-infrastructure-at-the-edge]]></link>
      <guid isPermaLink="false">3244496b-24b4-4897-9622-b559aa279f39</guid>
      <pubDate>Thu, 25 Jun 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[VIDEO_STREAMING_PLATFORMS_AND_INFRASTRUCTURE]]></category>
      <description><![CDATA[NetActuate has integrated NETINT Video Processing Units into its global edge infrastructure platform to provide hardware acceleration for broadcasters transitioning from C-band satellite to IP-based distribution. The offering allows operators to deploy virtualized video processing, such as FFmpeg and Gstreamer pipelines, across NetActuate's footprint for multi-site broadcast architectures.]]></description>
      <content:encoded><![CDATA[NetActuate has integrated NETINT Video Processing Units into its global edge infrastructure platform to provide hardware acceleration for broadcasters transitioning from C-band satellite to IP-based distribution. The offering allows operators to deploy virtualized video processing, such as FFmpeg and Gstreamer pipelines, across NetActuate's footprint for multi-site broadcast architectures.]]></content:encoded>
      <dc:creator><![CDATA[NetActuate]]></dc:creator>
      <author><![CDATA[NetActuate]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/3244496b-24b4-4897-9622-b559aa279f39.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Decoding bottleneck emerges as primary constraint for cloud-scale AI surveillance]]></title>
      <link><![CDATA[https://netint.com/decode-bottleneck-ai-surveillance]]></link>
      <guid isPermaLink="false">cf0d522d-762b-453f-9f74-50311b150f3d</guid>
      <pubDate>Mon, 15 Jun 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[PRODUCTION_HARDWARE]]></category>
      <description><![CDATA[NETINT's CMO, Mark Donnigan, states that video decoding, not AI models, is the primary bottleneck for cloud-scale AI surveillance. The article highlights that dedicated video processing hardware (VPUs), like those from NETINT, can offload decode workloads from CPUs and GPUs, significantly reducing power consumption and increasing stream density for AI video analytics. This efficiency is crucial as modern codecs increase compute requirements and edge deployments grow.]]></description>
      <content:encoded><![CDATA[NETINT's CMO, Mark Donnigan, states that video decoding, not AI models, is the primary bottleneck for cloud-scale AI surveillance. The article highlights that dedicated video processing hardware (VPUs), like those from NETINT, can offload decode workloads from CPUs and GPUs, significantly reducing power consumption and increasing stream density for AI video analytics. This efficiency is crucial as modern codecs increase compute requirements and edge deployments grow.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies - The world’s 1st commercial supplier of ASIC VPUs (video processing units) for building scalable and profitable video streaming platforms.]]></dc:creator>
      <author><![CDATA[NETINT Technologies - The world’s 1st commercial supplier of ASIC VPUs (video processing units) for building scalable and profitable video streaming platforms.]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/cf0d522d-762b-453f-9f74-50311b150f3d.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[NETINT launches VPU-as-a-Service to bridge cloud flexibility and hardware efficiency]]></title>
      <link><![CDATA[https://netint.com/vpu-as-a-service-video/]]></link>
      <guid isPermaLink="false">68f05618-7059-4cec-9c1f-9b494fb1ed77</guid>
      <pubDate>Thu, 11 Jun 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT Technologies outlines a new operating model called VPU-as-a-Service for cloud video processing, which uses purpose-built Video Processing Units (VPUs) to enhance efficiency for complex and high-volume transcoding workloads. This approach aims to improve codec economics and facilitate practical AV1 adoption by separating the execution layer from the main workflow logic, offering specialized hardware acceleration via a cloud-style deployment. The article positions VPU-as-a-Service as a balance between flexible CPU-based transcoding and fully managed services, allowing engineering teams to retain workflow control while benefiting from dedicated video hardware.]]></description>
      <content:encoded><![CDATA[NETINT Technologies outlines a new operating model called VPU-as-a-Service for cloud video processing, which uses purpose-built Video Processing Units (VPUs) to enhance efficiency for complex and high-volume transcoding workloads. This approach aims to improve codec economics and facilitate practical AV1 adoption by separating the execution layer from the main workflow logic, offering specialized hardware acceleration via a cloud-style deployment. The article positions VPU-as-a-Service as a balance between flexible CPU-based transcoding and fully managed services, allowing engineering teams to retain workflow control while benefiting from dedicated video hardware.]]></content:encoded>
      <dc:creator><![CDATA[NETINT technologies - The world’s 1st commercial supplier of ASIC VPUs (video processing units) for building scalable and profitable video streaming platforms.]]></dc:creator>
      <author><![CDATA[NETINT technologies - The world’s 1st commercial supplier of ASIC VPUs (video processing units) for building scalable and profitable video streaming platforms.]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/68f05618-7059-4cec-9c1f-9b494fb1ed77.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[2026 State of Video Encoding Report Findings]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/netint-technologies_survey-report-distribution-activity-7464737130519457793-C-ym?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGj3J3cBsZGOZmmcJusO0taePKS39nOld8w]]></link>
      <guid isPermaLink="false">8e3e144e-4609-4b5e-b140-58dc3722344c</guid>
      <pubDate>Mon, 25 May 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT Technologies has released findings from its "2026 State of Video Encoding Report," based on a survey of 286 video professionals across five global regions. Key findings indicate that AV1 codec adoption is projected to reach 57% combined by the end of 2026, and 70% of encoding teams are expanding AI within their workflows. The report also highlights that GPU and VPU evaluation rates are nearing parity, and 41% of hardware users are already employing mixed GPU + VPU stacks.]]></description>
      <content:encoded><![CDATA[NETINT Technologies has released findings from its "2026 State of Video Encoding Report," based on a survey of 286 video professionals across five global regions. Key findings indicate that AV1 codec adoption is projected to reach 57% combined by the end of 2026, and 70% of encoding teams are expanding AI within their workflows. The report also highlights that GPU and VPU evaluation rates are nearing parity, and 41% of hardware users are already employing mixed GPU + VPU stacks.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
      
    </item>

    <item>
      <title><![CDATA[The Evolution and Validation of the Video Processing Unit (VPU) Category]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/markdonnigan_vpu-videoinfrastructure-streaming-activity-7463239490933788672-LaMF?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGjMznEBvBCCDQGu31fBUIiBwQGoZo2Hd5U]]></link>
      <guid isPermaLink="false">17550df0-f113-4d79-9a1f-5b00f241f7d8</guid>
      <pubDate>Thu, 21 May 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The article discusses the evolution and validation of the Video Processing Unit (VPU) category, highlighting that the need for VPUs emerged due to the increasing cost and energy consumption of video processing on general-purpose compute.
It cites NETINT Technologies' role in developing the first commercially available ASIC-based video transcoder in 2018 and the recognition of efficient hardware video accelerators at the 75th Technology and Engineering Emmy Awards, alongside companies like AMD, Google, and Meta.]]></description>
      <content:encoded><![CDATA[The article discusses the evolution and validation of the Video Processing Unit (VPU) category, highlighting that the need for VPUs emerged due to the increasing cost and energy consumption of video processing on general-purpose compute.
It cites NETINT Technologies' role in developing the first commercially available ASIC-based video transcoder in 2018 and the recognition of efficient hardware video accelerators at the 75th Technology and Engineering Emmy Awards, alongside companies like AMD, Google, and Meta.]]></content:encoded>
      <dc:creator><![CDATA[Mark Donnigan]]></dc:creator>
      <author><![CDATA[Mark Donnigan]]></author>
      
    </item>

    <item>
      <title><![CDATA[The Value of Dedicated Video Silicon in Production Environments]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/nbsimon_datacenterops-videoinfrastructure-activity-7463261613412868097-fIWU?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGjMznEBvBCCDQGu31fBUIiBwQGoZo2Hd5U]]></link>
      <guid isPermaLink="false">ffcc8995-a6cc-43d7-8f94-8081f17a2af1</guid>
      <pubDate>Thu, 21 May 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[This article discusses the value of dedicated video silicon, specifically the Video Processing Unit (VPU) category, for managing density and power constraints in production environments. It explains the evolution of VPUs over the past decade in video infrastructure. The LinkedIn post serves as an introduction to a longer piece on Netint's website.]]></description>
      <content:encoded><![CDATA[This article discusses the value of dedicated video silicon, specifically the Video Processing Unit (VPU) category, for managing density and power constraints in production environments. It explains the evolution of VPUs over the past decade in video infrastructure. The LinkedIn post serves as an introduction to a longer piece on Netint's website.]]></content:encoded>
      <dc:creator><![CDATA[Nico Simon]]></dc:creator>
      <author><![CDATA[Nico Simon]]></author>
      
    </item>

    <item>
      <title><![CDATA[NetActuate Expands Amsterdam Infrastructure to Deliver Hybrid Cloud and Edge Services Across Europe]]></title>
      <link><![CDATA[https://www.prnewswire.com/news-releases/netactuate-expands-amsterdam-infrastructure-to-deliver-hybrid-cloud-and-edge-services-across-europe-302779128.html]]></link>
      <guid isPermaLink="false">0ce01d15-55eb-4c5c-b69d-e4caed6021cd</guid>
      <pubDate>Thu, 21 May 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[VIDEO_DELIVERY_AND_CDN]]></category>
      <description><![CDATA[NetActuate announced the expansion of its infrastructure in Amsterdam to enhance hybrid cloud and edge services across Europe. This expansion aims to support growing demand for data processing at the edge, leveraging Amsterdam as a key digital hub. The company will showcase this expansion with a NETINT VPU ecosystem at IBC 2026.]]></description>
      <content:encoded><![CDATA[NetActuate announced the expansion of its infrastructure in Amsterdam to enhance hybrid cloud and edge services across Europe. This expansion aims to support growing demand for data processing at the edge, leveraging Amsterdam as a key digital hub. The company will showcase this expansion with a NETINT VPU ecosystem at IBC 2026.]]></content:encoded>
      <dc:creator><![CDATA[PR Newswire]]></dc:creator>
      <author><![CDATA[PR Newswire]]></author>
      <enclosure url="https://mma.prnewswire.com/media/2985438/Amsterdam_is_a_global_digital_hub.jpg?p=facebook" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[How the Video Processing Unit Became a Category]]></title>
      <link><![CDATA[https://netint.biz/4duf3Nl]]></link>
      <guid isPermaLink="false">293cf052-9ea6-412e-a45d-5ade0e494092</guid>
      <pubDate>Wed, 13 May 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT Technologies, a pioneer in Video Processing Units (VPUs), reflects on its journey to category creation, marked by receiving a 75th Technology and Engineering Emmy Award alongside AMD, Google, and Meta for efficient hardware video accelerators. The article highlights the growing industry shift toward purpose-built silicon for video encoding, driven by escalating video demand and the limitations of general-purpose CPUs and GPUs. NETINT details its product development, ecosystem integration efforts, and customer success stories demonstrating the power efficiency and density benefits of VPUs.]]></description>
      <content:encoded><![CDATA[NETINT Technologies, a pioneer in Video Processing Units (VPUs), reflects on its journey to category creation, marked by receiving a 75th Technology and Engineering Emmy Award alongside AMD, Google, and Meta for efficient hardware video accelerators. The article highlights the growing industry shift toward purpose-built silicon for video encoding, driven by escalating video demand and the limitations of general-purpose CPUs and GPUs. NETINT details its product development, ecosystem integration efforts, and customer success stories demonstrating the power efficiency and density benefits of VPUs.]]></content:encoded>
      <dc:creator><![CDATA[NETINT]]></dc:creator>
      <author><![CDATA[NETINT]]></author>
      <enclosure url="https://netint.com/wp-content/uploads/2026/05/Building-a-category-in-plain-insight-VPU.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[NetActuate Joins the NETINT VPU Ecosystem for Global Video Acceleration]]></title>
      <link><![CDATA[https://netactuate.com/blog/netactuate-joins-the-netint-vpu-ecosystem-global-video-acceleration-ai-native-deployment-and-a-strong-partner-bench]]></link>
      <guid isPermaLink="false">bf32bdf5-4145-4e4e-aa8f-7ab8fe2fcb58</guid>
      <pubDate>Tue, 28 Apr 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NetActuate has partnered with NETINT Technologies to offer global, on-demand infrastructure for hardware-accelerated video processing. The service utilizes NETINT's Smart VPUs deployed across NetActuate's network, allowing customers to access video encoding, decoding, and AI-native processing as-a-service. Customers can deploy the VPUs on pre-installed virtual machines or request custom builds.]]></description>
      <content:encoded><![CDATA[NetActuate has partnered with NETINT Technologies to offer global, on-demand infrastructure for hardware-accelerated video processing. The service utilizes NETINT's Smart VPUs deployed across NetActuate's network, allowing customers to access video encoding, decoding, and AI-native processing as-a-service. Customers can deploy the VPUs on pre-installed virtual machines or request custom builds.]]></content:encoded>
      <dc:creator><![CDATA[NetActuate]]></dc:creator>
      <author><![CDATA[NetActuate]]></author>
      
    </item>

    <item>
      <title><![CDATA[AI Hardware Alliance: Advantech & NETINT Boost Transcoding]]></title>
      <link><![CDATA[https://www.aicerts.ai/news/ai-hardware-alliance-advantech-netint-boost-transcoding/]]></link>
      <guid isPermaLink="false">1697e2d0-4ec4-4f01-adcc-401adc61bc01</guid>
      <pubDate>Mon, 20 Apr 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[Advantech and NETINT describe a joint effort to package NETINT’s Quadra VPU encoding cards into Advantech’s half-rack Vega 6321 chassis as a turnkey “Quadra Mini Server” for edge and compact deployments. The article cites vendor-reported metrics (including Akamai-reported tests) claiming materially higher encoding throughput per watt versus CPU-only systems, with support for H.264, HEVC, and AV1. It also highlights ecosystem enablement such as FFmpeg/GStreamer plugins, MainConcept Easy Video API integration, and Akamai cloud instance availability while noting the need for third-party benchmarking and potential codec-obsolescence risks.]]></description>
      <content:encoded><![CDATA[Advantech and NETINT describe a joint effort to package NETINT’s Quadra VPU encoding cards into Advantech’s half-rack Vega 6321 chassis as a turnkey “Quadra Mini Server” for edge and compact deployments. The article cites vendor-reported metrics (including Akamai-reported tests) claiming materially higher encoding throughput per watt versus CPU-only systems, with support for H.264, HEVC, and AV1. It also highlights ecosystem enablement such as FFmpeg/GStreamer plugins, MainConcept Easy Video API integration, and Akamai cloud instance availability while noting the need for third-party benchmarking and potential codec-obsolescence risks.]]></content:encoded>
      <dc:creator><![CDATA[AI Certs]]></dc:creator>
      <author><![CDATA[AI Certs]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/1697e2d0-4ec4-4f01-adcc-401adc61bc01.jpg" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[The Architecture Beneath the Accelerator]]></title>
      <link><![CDATA[https://netint.com/vpu-system-architecture/?utm_source=rss&utm_medium=rss&utm_campaign=vpu-system-architecture]]></link>
      <guid isPermaLink="false">400a50e7-24be-4304-bab2-42290da475a9</guid>
      <pubDate>Thu, 02 Apr 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[PRODUCTION_HARDWARE]]></category>
      <description><![CDATA[NETINT and Advantech describe how real-world performance of VPU-based video encoding depends on server-level architecture rather than silicon specifications alone. The article highlights key design constraints for dense accelerator deployments—PCIe topology, power delivery, thermal management, mechanical serviceability, and edge-environment limits—and cites Advantech server families intended to sustain 24/7 VPU throughput.]]></description>
      <content:encoded><![CDATA[NETINT and Advantech describe how real-world performance of VPU-based video encoding depends on server-level architecture rather than silicon specifications alone. The article highlights key design constraints for dense accelerator deployments—PCIe topology, power delivery, thermal management, mechanical serviceability, and edge-environment limits—and cites Advantech server families intended to sustain 24/7 VPU throughput.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
      <enclosure url="https://netint.com/wp-content/uploads/2026/04/Advantech_The-Architecture-Beneath-the-Accelerator-2.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[2026 State of Video Encoding – What 286 Professionals Told Us]]></title>
      <link><![CDATA[https://netint.biz/41i6kYS]]></link>
      <guid isPermaLink="false">ba54bfa7-9b40-4361-a579-b781c34abd14</guid>
      <pubDate>Thu, 26 Mar 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT's "2026 State of Video Encoding" report, based on a survey of 286 professionals, highlights key trends including the diversification away from GPU-only hardware for encoding, the increasing adoption of the AV1 codec with a projected 231% growth rate, and the integration of AI/ML into core encoding workflows.
It also identifies organizational barriers like budget constraints and team capacity as primary blockers, alongside a significant portion of the market lacking formalized Total Cost of Ownership (TCO) methodology, and the emergence of hybrid software/hardware solutions for large-scale operations.]]></description>
      <content:encoded><![CDATA[NETINT's "2026 State of Video Encoding" report, based on a survey of 286 professionals, highlights key trends including the diversification away from GPU-only hardware for encoding, the increasing adoption of the AV1 codec with a projected 231% growth rate, and the integration of AI/ML into core encoding workflows.
It also identifies organizational barriers like budget constraints and team capacity as primary blockers, alongside a significant portion of the market lacking formalized Total Cost of Ownership (TCO) methodology, and the emergence of hybrid software/hardware solutions for large-scale operations.]]></content:encoded>
      <dc:creator><![CDATA[NETINT]]></dc:creator>
      <author><![CDATA[NETINT]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/ba54bfa7-9b40-4361-a579-b781c34abd14.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[The Control Plane Imperative: Operating Video at Scale]]></title>
      <link><![CDATA[https://netint.com/video-control-plane/?utm_source=rss&utm_medium=rss&utm_campaign=video-control-plane]]></link>
      <guid isPermaLink="false">9de5d626-e6e4-4b31-b37e-49d30ae0030d</guid>
      <pubDate>Thu, 26 Mar 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[VIDEO_STREAMING_PLATFORMS_AND_INFRASTRUCTURE]]></category>
      <description><![CDATA[NETINT argues that as video pipelines scale, operational coordination (a “video control plane”) becomes a larger bottleneck than raw encoding performance, especially in event-driven architectures and Just-In-Time (JIT) transcoding. The article positions partner platform Scalstrm as a unified control plane across ingest, transcoding, packaging, and delivery (including origin/CDN functions), citing operational features like intent-based scheduling, backpressure, and failure isolation plus claimed cost/power/footprint reductions when orchestrating CPU/GPU/VPU resources.]]></description>
      <content:encoded><![CDATA[NETINT argues that as video pipelines scale, operational coordination (a “video control plane”) becomes a larger bottleneck than raw encoding performance, especially in event-driven architectures and Just-In-Time (JIT) transcoding. The article positions partner platform Scalstrm as a unified control plane across ingest, transcoding, packaging, and delivery (including origin/CDN functions), citing operational features like intent-based scheduling, backpressure, and failure isolation plus claimed cost/power/footprint reductions when orchestrating CPU/GPU/VPU resources.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/9de5d626-e6e4-4b31-b37e-49d30ae0030d.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Where Video Compute Belongs: A Latency-First Perspective]]></title>
      <link><![CDATA[https://netint.com/distributed-video-transcoding/?utm_source=rss&utm_medium=rss&utm_campaign=distributed-video-transcoding]]></link>
      <guid isPermaLink="false">ed4053d9-d422-4277-83b4-6368669253de</guid>
      <pubDate>Mon, 23 Mar 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT Technologies argues that latency-sensitive workloads (interactive streaming, cloud gaming, real-time applications) push video transcoding closer to end users, making distributed transcoding a core architectural requirement rather than an optimization. The article describes how purpose-built VPUs can reduce per-site power, space, and capacity-planning uncertainty, and positions i3D.net’s multi-location infrastructure footprint as a deployment layer for running transcoding in regional sites with tight latency budgets. It also notes ongoing operational constraints for distributed deployments, including network variability and regional regulatory/import considerations (e.g., NIS2).]]></description>
      <content:encoded><![CDATA[NETINT Technologies argues that latency-sensitive workloads (interactive streaming, cloud gaming, real-time applications) push video transcoding closer to end users, making distributed transcoding a core architectural requirement rather than an optimization. The article describes how purpose-built VPUs can reduce per-site power, space, and capacity-planning uncertainty, and positions i3D.net’s multi-location infrastructure footprint as a deployment layer for running transcoding in regional sites with tight latency budgets. It also notes ongoing operational constraints for distributed deployments, including network variability and regional regulatory/import considerations (e.g., NIS2).]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/ed4053d9-d422-4277-83b4-6368669253de.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[From Silicon to Rack: Why Deployable Video Infrastructure Demands a New Design Philosophy]]></title>
      <link><![CDATA[https://netint.com/deployable-video-infrastructure/?utm_source=rss&utm_medium=rss&utm_campaign=deployable-video-infrastructure]]></link>
      <guid isPermaLink="false">65df2ba1-6fdc-4b27-9170-7514221fbb82</guid>
      <pubDate>Thu, 19 Mar 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[PRODUCTION_HARDWARE]]></category>
      <description><![CDATA[NETINT argues that at data-center scale, video processing deployments are constrained less by raw encode performance and more by rack-level power, thermal limits, density, and operational serviceability. The article claims VPU-based acceleration can provide more deterministic power/thermal behavior and higher streams-per-server density than CPU/GPU approaches, and highlights Dell PowerEdge server design (e.g., PCIe expansion, cooling, and fleet management tooling) as enabling production-grade, maintainable VPU deployments over multi-year lifecycles.]]></description>
      <content:encoded><![CDATA[NETINT argues that at data-center scale, video processing deployments are constrained less by raw encode performance and more by rack-level power, thermal limits, density, and operational serviceability. The article claims VPU-based acceleration can provide more deterministic power/thermal behavior and higher streams-per-server density than CPU/GPU approaches, and highlights Dell PowerEdge server design (e.g., PCIe expansion, cooling, and fleet management tooling) as enabling production-grade, maintainable VPU deployments over multi-year lifecycles.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/65df2ba1-6fdc-4b27-9170-7514221fbb82.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Video Transcoding Economics: Escape the Compute Trap]]></title>
      <link><![CDATA[https://netint.com/video-compute-trap/]]></link>
      <guid isPermaLink="false">23531b78-954a-4bb4-ab39-599ee6a0caa6</guid>
      <pubDate>Mon, 16 Mar 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT argues that scaling transcoding on general-purpose CPU instances creates a compounding “compute trap” driven by compute growth, energy/density constraints, egress costs, and operational complexity. The article presents a reference architecture combining NETINT Quadra T1U VPU-accelerated transcoding with Akamai Distributed Cloud services (including Accelerated Compute, Media Services Live, and Adaptive Media Delivery) and cites benchmarks claiming 4–6x better watts-per-stream efficiency and egress as low as $0.005/GB. It also states the approach can be deployed via Kubernetes worker nodes and Terraform to fit modern CI/CD workflows.]]></description>
      <content:encoded><![CDATA[NETINT argues that scaling transcoding on general-purpose CPU instances creates a compounding “compute trap” driven by compute growth, energy/density constraints, egress costs, and operational complexity. The article presents a reference architecture combining NETINT Quadra T1U VPU-accelerated transcoding with Akamai Distributed Cloud services (including Accelerated Compute, Media Services Live, and Adaptive Media Delivery) and cites benchmarks claiming 4–6x better watts-per-stream efficiency and egress as low as $0.005/GB. It also states the approach can be deployed via Kubernetes worker nodes and Terraform to fit modern CI/CD workflows.]]></content:encoded>
      <dc:creator><![CDATA[NETINT technologies]]></dc:creator>
      <author><![CDATA[NETINT technologies]]></author>
      <enclosure url="https://netint.com/wp-content/uploads/2026/03/Akamai-Essay-When-the-Economics-of-Video-Break_-A-Framework-for-Escaping-the-Compute-Trap.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[When the Economics of Video Break: A Framework of Escaping the Compute Trap]]></title>
      <link><![CDATA[https://netint.com/video-compute-trap/?utm_source=rss&utm_medium=rss&utm_campaign=video-compute-trap]]></link>
      <guid isPermaLink="false">711b8e71-db07-47b4-b592-702588db64a9</guid>
      <pubDate>Mon, 16 Mar 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT argues that large-scale streaming platforms relying on general-purpose CPU compute face a compounding cost "compute trap" driven by compute scaling, power/density limits, egress fees, and operational complexity. The article presents a reference architecture combining NETINT Quadra VPUs for transcoding with Akamai Distributed Cloud services (Accelerated Compute, Media Services Live, and Adaptive Media Delivery) to reduce watts-per-stream and lower compute-to-delivery egress costs. It cites published and vendor benchmarks claiming roughly 4–6x better energy efficiency versus CPU/GPU approaches and egress pricing as low as $0.005/GB when compute and delivery are aligned within Akamai’s infrastructure.]]></description>
      <content:encoded><![CDATA[NETINT argues that large-scale streaming platforms relying on general-purpose CPU compute face a compounding cost "compute trap" driven by compute scaling, power/density limits, egress fees, and operational complexity. The article presents a reference architecture combining NETINT Quadra VPUs for transcoding with Akamai Distributed Cloud services (Accelerated Compute, Media Services Live, and Adaptive Media Delivery) to reduce watts-per-stream and lower compute-to-delivery egress costs. It cites published and vendor benchmarks claiming roughly 4–6x better energy efficiency versus CPU/GPU approaches and egress pricing as low as $0.005/GB when compute and delivery are aligned within Akamai’s infrastructure.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
      <enclosure url="https://netint.com/wp-content/uploads/2026/03/Akamai-Essay-When-the-Economics-of-Video-Break_-A-Framework-for-Escaping-the-Compute-Trap.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Why Energy Efficiency Will Decide the Future of Video Infrastructure in Europe]]></title>
      <link><![CDATA[https://netint.com/energy-efficiency-video-europe/?utm_source=rss&utm_medium=rss&utm_campaign=energy-efficiency-video-europe]]></link>
      <guid isPermaLink="false">780fa5da-a132-41b5-8ade-757bd75d3d52</guid>
      <pubDate>Mon, 09 Mar 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT argues that in major European data-center hubs (Frankfurt, London, Amsterdam, Paris, Dublin), grid connection delays and power caps are making energy efficiency a primary constraint on scaling video platforms, particularly for compute-heavy transcoding. The article claims CPU-based software encoding struggles to scale for 4K/UHD and modern codecs (HEVC/AV1) under fixed power envelopes, and promotes a shift to ASIC-based Video Processing Units (VPUs) using metrics like “watts per stream” and “cost per stream.” It links infrastructure choices to European regulatory and reporting pressures including the Energy Efficiency Directive (EED), Germany’s EnEfG, and sustainability disclosures (CSRD).]]></description>
      <content:encoded><![CDATA[NETINT argues that in major European data-center hubs (Frankfurt, London, Amsterdam, Paris, Dublin), grid connection delays and power caps are making energy efficiency a primary constraint on scaling video platforms, particularly for compute-heavy transcoding. The article claims CPU-based software encoding struggles to scale for 4K/UHD and modern codecs (HEVC/AV1) under fixed power envelopes, and promotes a shift to ASIC-based Video Processing Units (VPUs) using metrics like “watts per stream” and “cost per stream.” It links infrastructure choices to European regulatory and reporting pressures including the Energy Efficiency Directive (EED), Germany’s EnEfG, and sustainability disclosures (CSRD).]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
      <enclosure url="https://netint.com/wp-content/uploads/2026/02/Energy-Drives-Future-JA-1.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Ecosystem - NETINT technologies]]></title>
      <link><![CDATA[https://netint.com/ecosystem/]]></link>
      <guid isPermaLink="false">b827b1b9-849a-4a03-916f-2f2bafcb6673</guid>
      <pubDate>Sun, 01 Mar 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT Technologies launched its "VPU Ecosystem" initiative, a global network of partners, architectures, and deployments for its video processing units (VPUs). This ecosystem aims to provide the "open market" with a deployment system for scalable and cost-efficient video encoding, enabling it to compete with "walled gardens" that develop proprietary silicon. The initiative includes validation of partners across cloud, software, hardware, and infrastructure to integrate NETINT VPUs into various stages of the video pipeline, from ingest to delivery.]]></description>
      <content:encoded><![CDATA[NETINT Technologies launched its "VPU Ecosystem" initiative, a global network of partners, architectures, and deployments for its video processing units (VPUs). This ecosystem aims to provide the "open market" with a deployment system for scalable and cost-efficient video encoding, enabling it to compete with "walled gardens" that develop proprietary silicon. The initiative includes validation of partners across cloud, software, hardware, and infrastructure to integrate NETINT VPUs into various stages of the video pipeline, from ingest to delivery.]]></content:encoded>
      <dc:creator><![CDATA[NETINT]]></dc:creator>
      <author><![CDATA[NETINT]]></author>
      <enclosure url="https://netint.com/wp-content/uploads/2023/09/Linkedin-NETINT-Products-Compilation-logan-quadra.jpg" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Ecosystem - NETINT technologies]]></title>
      <link><![CDATA[https://netint.biz/4eHCNzH]]></link>
      <guid isPermaLink="false">cedffd92-7194-4f42-8fab-712e5182f1e5</guid>
      <pubDate>Sun, 01 Mar 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[NETINT Technologies has detailed its 'VPU Ecosystem,' a network of partners providing validated architectures and production deployments for its Video Processing Unit (VPU) technology. This ecosystem aims to enable the 'Open Market' to achieve architectural efficiency comparable to 'Walled Gardens' that develop proprietary silicon, addressing challenges posed by modern codecs and rising infrastructure costs.]]></description>
      <content:encoded><![CDATA[NETINT Technologies has detailed its 'VPU Ecosystem,' a network of partners providing validated architectures and production deployments for its Video Processing Unit (VPU) technology. This ecosystem aims to enable the 'Open Market' to achieve architectural efficiency comparable to 'Walled Gardens' that develop proprietary silicon, addressing challenges posed by modern codecs and rising infrastructure costs.]]></content:encoded>
      <dc:creator><![CDATA[NETINT]]></dc:creator>
      <author><![CDATA[NETINT]]></author>
      <enclosure url="https://netint.com/wp-content/uploads/2023/09/Linkedin-NETINT-Products-Compilation-logan-quadra.jpg" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Is Public Cloud Costing Your Video Workflows 5x More Than Necessary?]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/netint-technologies_netint-arcadian-markdonnigan-activity-7431760427778392064-Ssii?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGRMgkEBrb44arrx_MTI6dHDVz-PxEgi93k]]></link>
      <guid isPermaLink="false">16cc008c-b50b-4ae9-9f86-47ba891fbb23</guid>
      <pubDate>Mon, 23 Feb 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The piece argues that general-purpose public cloud infrastructure can be up to 5x more expensive than specialized hardware for certain video workflows, particularly high-density live encoding. It highlights VPUs available at around $0.42 per hour that can support up to 32 simultaneous 1080p30 encodes across AV1, HEVC, and H.264, and cites companies like Arcadian using NETINT hardware to shift heavy video processing off standard cloud instances. The post promotes a hybrid approach where control logic remains in the cloud while compute-intensive video tasks move to optimized infrastructure.]]></description>
      <content:encoded><![CDATA[The piece argues that general-purpose public cloud infrastructure can be up to 5x more expensive than specialized hardware for certain video workflows, particularly high-density live encoding. It highlights VPUs available at around $0.42 per hour that can support up to 32 simultaneous 1080p30 encodes across AV1, HEVC, and H.264, and cites companies like Arcadian using NETINT hardware to shift heavy video processing off standard cloud instances. The post promotes a hybrid approach where control logic remains in the cloud while compute-intensive video tasks move to optimized infrastructure.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
      
    </item>

    <item>
      <title><![CDATA[Power Is the New Bottleneck: Scaling Video Platforms in an Energy-Constrained Europe]]></title>
      <link><![CDATA[https://netint.com/video-infrastructure-power-constraints/?utm_source=rss&utm_medium=rss&utm_campaign=video-infrastructure-power-constraints]]></link>
      <guid isPermaLink="false">5e46cd59-048c-42d5-964e-ae10014147ea</guid>
      <pubDate>Mon, 23 Feb 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The article argues that for European video platforms, power availability, rack density, and energy costs have become primary constraints on scaling, shifting focus from server count and peak throughput to metrics like watts per stream and sustained streams per kilowatt. It compares CPU-only, hardware-accelerated, and cloud-based encoding architectures, contending that dedicated video acceleration such as NETINT’s Quadra VPU can improve rack-level efficiency, power predictability, and long-term capacity planning in energy-constrained environments.]]></description>
      <content:encoded><![CDATA[The article argues that for European video platforms, power availability, rack density, and energy costs have become primary constraints on scaling, shifting focus from server count and peak throughput to metrics like watts per stream and sustained streams per kilowatt. It compares CPU-only, hardware-accelerated, and cloud-based encoding architectures, contending that dedicated video acceleration such as NETINT’s Quadra VPU can improve rack-level efficiency, power predictability, and long-term capacity planning in energy-constrained environments.]]></content:encoded>
      <dc:creator><![CDATA[NETINT Technologies]]></dc:creator>
      <author><![CDATA[NETINT Technologies]]></author>
      <enclosure url="https://cfvnzurrxjvihtctgdku.supabase.co/storage/v1/object/public/article_thumbnails/5e46cd59-048c-42d5-964e-ae10014147ea.png" type="image/jpeg" length="0"/>
    </item>

    <item>
      <title><![CDATA[Voices of Video: NETINT's Multi-Layer AV1 and Multiview Encoding Deep Dive]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/randal-horne-99a957_voicesofvideo-vpu-av1-activity-7429555742128439296-ed-y?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGRW4icBpagAqfU3-IY2dnbokDzQ0bit30k]]></link>
      <guid isPermaLink="false">5b9fdab5-39b1-4225-b2e8-01f265145985</guid>
      <pubDate>Tue, 17 Feb 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The post promotes a 'Voices of Video' episode in which NETINT's Kenneth Robinson explains multi-layer AV1 for delivering a single bitstream with targeted overlays or ads and multiview encoding that enables flexible 2×2 or quad layouts without re-encoding. It also highlights NETINT's customer-driven 2025 roadmap, including WHIP/WHEP contribution, RTP, SMPTE 2110, audio level control, possible RIST and NDI support, and expanded statistics and monitoring.]]></description>
      <content:encoded><![CDATA[The post promotes a 'Voices of Video' episode in which NETINT's Kenneth Robinson explains multi-layer AV1 for delivering a single bitstream with targeted overlays or ads and multiview encoding that enables flexible 2×2 or quad layouts without re-encoding. It also highlights NETINT's customer-driven 2025 roadmap, including WHIP/WHEP contribution, RTP, SMPTE 2110, audio level control, possible RIST and NDI support, and expanded statistics and monitoring.]]></content:encoded>
      <dc:creator><![CDATA[Randal Horne]]></dc:creator>
      <author><![CDATA[Randal Horne]]></author>
      
    </item>

    <item>
      <title><![CDATA[Voices of Video: NETINT's Multi-Layer AV1 and Multiview Encoding Preview]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/anita-flejter_voicesofvideo-vpu-av1-activity-7429555741574750208-3flm?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGRW4icBpagAqfU3-IY2dnbokDzQ0bit30k]]></link>
      <guid isPermaLink="false">0bf788ae-faf8-40f9-863c-95355acff9dd</guid>
      <pubDate>Tue, 17 Feb 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The post promotes a 'Voices of Video' episode featuring NETINT’s preview of multi-layer AV1 capabilities for delivering a single bitstream with targeted overlays or ads and multiview encoding that enables flexible 2×2 or quad layouts without re-encoding. It also outlines a customer-driven 2025 roadmap including WHIP/WHEP contribution, RTP, SMPTE 2110 support, audio level control, potential RIST and NDI support, and enhanced statistics and monitoring.]]></description>
      <content:encoded><![CDATA[The post promotes a 'Voices of Video' episode featuring NETINT’s preview of multi-layer AV1 capabilities for delivering a single bitstream with targeted overlays or ads and multiview encoding that enables flexible 2×2 or quad layouts without re-encoding. It also outlines a customer-driven 2025 roadmap including WHIP/WHEP contribution, RTP, SMPTE 2110 support, audio level control, potential RIST and NDI support, and enhanced statistics and monitoring.]]></content:encoded>
      <dc:creator><![CDATA[Anita Flejter, EMBA, MSBA]]></dc:creator>
      <author><![CDATA[Anita Flejter, EMBA, MSBA]]></author>
      
    </item>

    <item>
      <title><![CDATA[Voices of Video: NETINT Multi-Layer AV1 and Multiview Encoding Preview]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/kennethrobinson08_voicesofvideo-vpu-av1-activity-7429555785187356673--JMQ?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGRW4icBpagAqfU3-IY2dnbokDzQ0bit30k]]></link>
      <guid isPermaLink="false">589fac30-1141-4df9-9485-fc481b764a2d</guid>
      <pubDate>Tue, 17 Feb 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The post promotes a 'Voices of Video' episode where Kenneth Robinson previews NETINT’s multi-layer AV1 and multiview encoding capabilities, enabling single-bitstream delivery with targeted overlays/ads and flexible multi-camera layouts without re-encoding. It also outlines a 2025 roadmap adding WHIP/WHEP, RTP, SMPTE 2110, audio level control, evaluation of RIST and NDI, and deeper statistics and monitoring for live and hybrid workflows.]]></description>
      <content:encoded><![CDATA[The post promotes a 'Voices of Video' episode where Kenneth Robinson previews NETINT’s multi-layer AV1 and multiview encoding capabilities, enabling single-bitstream delivery with targeted overlays/ads and flexible multi-camera layouts without re-encoding. It also outlines a 2025 roadmap adding WHIP/WHEP, RTP, SMPTE 2110, audio level control, evaluation of RIST and NDI, and deeper statistics and monitoring for live and hybrid workflows.]]></content:encoded>
      <dc:creator><![CDATA[Kenneth Robinson]]></dc:creator>
      <author><![CDATA[Kenneth Robinson]]></author>
      
    </item>

    <item>
      <title><![CDATA[Voices of Video: How Scalstrm Leveraged NETINT VPUs to Transform Live Esports Streaming]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/nbsimon_voicesofvideo-vpu-esportsstreaming-activity-7428468576686178304-VeI0?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGRbQFoBkQW8zqK6-ciWj6szpIGtRekxexI]]></link>
      <guid isPermaLink="false">1a51e756-8945-4d6b-97e4-b685316db70e</guid>
      <pubDate>Sat, 14 Feb 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The post promotes a 'Voices of Video' episode detailing how Scalstrm integrated NETINT VPUs at the API level to support up to 20 live esports channels per card and fine-tune rate control, buffer settings, and ABR logic. It describes operational gains such as faster startup times, reduced idle compute between events, and more predictable performance compared with GPU instances that may be diverted to AI training. Listeners are directed to the full episode for additional technical context.]]></description>
      <content:encoded><![CDATA[The post promotes a 'Voices of Video' episode detailing how Scalstrm integrated NETINT VPUs at the API level to support up to 20 live esports channels per card and fine-tune rate control, buffer settings, and ABR logic. It describes operational gains such as faster startup times, reduced idle compute between events, and more predictable performance compared with GPU instances that may be diverted to AI training. Listeners are directed to the full episode for additional technical context.]]></content:encoded>
      <dc:creator><![CDATA[Nico Simon]]></dc:creator>
      <author><![CDATA[Nico Simon]]></author>
      
    </item>

    <item>
      <title><![CDATA[Two Economies of Video Engineering: What NETINT's 2026 Encoding Survey Reveals About Live vs. VOD]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/markdonnigan_videoengineering-streamingtech-vod-activity-7428105688637251584-an_h?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGQiBksBKzNt48HezJ009ZYv4gy2kCpq9MY]]></link>
      <guid isPermaLink="false">e57d88c2-34b4-4682-a6ae-515f33cd4db8</guid>
      <pubDate>Fri, 13 Feb 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The article discusses findings from NETINT Technologies' 2026 State of Video Encoding Survey, highlighting divergent economic and operational priorities between VOD and live streaming operators. VOD services primarily focus on reducing distribution and storage costs through more efficient codecs, while live streaming operators are more constrained by team capacity and operational complexity, driving interest in VPUs, edge infrastructure, and AI-driven automation. The post notes that both segments are exploring AI/ML, with VOD teams seeking smarter encoding and live teams seeking workflow management and reliability gains.]]></description>
      <content:encoded><![CDATA[The article discusses findings from NETINT Technologies' 2026 State of Video Encoding Survey, highlighting divergent economic and operational priorities between VOD and live streaming operators. VOD services primarily focus on reducing distribution and storage costs through more efficient codecs, while live streaming operators are more constrained by team capacity and operational complexity, driving interest in VPUs, edge infrastructure, and AI-driven automation. The post notes that both segments are exploring AI/ML, with VOD teams seeking smarter encoding and live teams seeking workflow management and reliability gains.]]></content:encoded>
      <dc:creator><![CDATA[Mark Donnigan]]></dc:creator>
      <author><![CDATA[Mark Donnigan]]></author>
      
    </item>

    <item>
      <title><![CDATA[How NETINT VPUs Transformed Live Esports Streaming Economics for Scalstrm]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/activity-7427988663705350144-YoeH?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGR9ZtYBHfvwN_OmrQQ7f3ubBSv2APa7dCY]]></link>
      <guid isPermaLink="false">5c7398af-b7c4-4ea7-bb6c-5f8fe3197f1b</guid>
      <pubDate>Fri, 13 Feb 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The post promotes a podcast episode detailing how Scalstrm integrated NETINT VPUs at the API level to support up to 20 live esports channels per card, faster startup times, and more efficient use of compute compared with GPU-based workflows. It highlights how low-level control over rate control, buffer tuning, and ABR logic improved streaming economics and maintained predictable performance when GPU instances were constrained by AI training demand.]]></description>
      <content:encoded><![CDATA[The post promotes a podcast episode detailing how Scalstrm integrated NETINT VPUs at the API level to support up to 20 live esports channels per card, faster startup times, and more efficient use of compute compared with GPU-based workflows. It highlights how low-level control over rate control, buffer tuning, and ABR logic improved streaming economics and maintained predictable performance when GPU instances were constrained by AI training demand.]]></content:encoded>
      <dc:creator><![CDATA[Leo N.]]></dc:creator>
      <author><![CDATA[Leo N.]]></author>
      
    </item>

    <item>
      <title><![CDATA[MaelStrom: Modern Live Encoding Technology Built for Robustness]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/stefvdziel_maelstrom-its2026-mediatech-activity-7427636250490204160-dWOz?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGRq65MBEyzsCIwQfSQPBgSGz8x41g9XDak]]></link>
      <guid isPermaLink="false">f0881d76-f775-4705-abcf-60734bc72363</guid>
      <pubDate>Thu, 12 Feb 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The post introduces MaelStrom, a cloud-native live encoding technology designed to lower per-channel costs, reduce rack space and bandwidth usage, and cut energy consumption by leveraging NETINT VPUs and ARM architectures. It highlights support for modern codecs (H.264, H.265, AV1), SRT I/O, VMAF optimization, integrated origins with thundering herd protection, and optional integration with Unified Streaming’s packager and Jet-Stream’s Multi-CDN.]]></description>
      <content:encoded><![CDATA[The post introduces MaelStrom, a cloud-native live encoding technology designed to lower per-channel costs, reduce rack space and bandwidth usage, and cut energy consumption by leveraging NETINT VPUs and ARM architectures. It highlights support for modern codecs (H.264, H.265, AV1), SRT I/O, VMAF optimization, integrated origins with thundering herd protection, and optional integration with Unified Streaming’s packager and Jet-Stream’s Multi-CDN.]]></content:encoded>
      <dc:creator><![CDATA[Stef van der Ziel]]></dc:creator>
      <author><![CDATA[Stef van der Ziel]]></author>
      
    </item>

    <item>
      <title><![CDATA[The Road to AV1: Challenges and Expectations for 2026]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/markdonnigan_av1-videoencoding-streaminginfrastructure-activity-7426761833056976896-_0RZ?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGRFL0AB_EPGTnuUK0_qLn2O39H_x73iLXM]]></link>
      <guid isPermaLink="false">8b9a5d36-31c8-401e-8205-8f6e37d47f52</guid>
      <pubDate>Tue, 10 Feb 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The article discusses findings from the 2026 NETINT Technologies State of Encoding Survey indicating a sharp increase in AV1 adoption, with 17% of respondents using AV1 in production today and 40% planning deployment in 2026. It highlights the high computational cost of software-based AV1 encoding as a key barrier and describes a resulting shift toward dedicated hardware acceleration (VPUs and GPUs) to manage OPEX and enable scalable next-gen codec workflows.]]></description>
      <content:encoded><![CDATA[The article discusses findings from the 2026 NETINT Technologies State of Encoding Survey indicating a sharp increase in AV1 adoption, with 17% of respondents using AV1 in production today and 40% planning deployment in 2026. It highlights the high computational cost of software-based AV1 encoding as a key barrier and describes a resulting shift toward dedicated hardware acceleration (VPUs and GPUs) to manage OPEX and enable scalable next-gen codec workflows.]]></content:encoded>
      <dc:creator><![CDATA[Mark Donnigan]]></dc:creator>
      <author><![CDATA[Mark Donnigan]]></author>
      
    </item>

    <item>
      <title><![CDATA[Rethinking Video Engineering: Beyond Size to Operational Complexity]]></title>
      <link><![CDATA[https://www.linkedin.com/posts/markdonnigan_videoengineering-streamingvideo-streamingmedia-activity-7426486050472009728-5KCu?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAGP5XREBvqIJulZ-SFoIZ-wc333cY4dyvtE]]></link>
      <guid isPermaLink="false">b0a82f06-4e37-4c28-b194-7e39ddf28dd5</guid>
      <pubDate>Mon, 09 Feb 2026 00:00:00 GMT</pubDate>
      <category><![CDATA[ENCODING_AND_SOFTWARE]]></category>
      <description><![CDATA[The article discusses findings from NETINT Technologies' 2026 State of Encoding Survey, which re-frames 'video engineering at scale' in terms of operational complexity rather than company size, distinguishing between Live-focused and VOD-focused operators with different primary constraints (talent vs. budget). It reports that 54% of respondents plan to evaluate GPUs and 52% plan to evaluate VPUs/ASICs in 2026, positioning hardware acceleration as a converging solution to both live and VOD bottlenecks. The piece emphasizes aligning technical and financial narratives when making encoding and infrastructure decisions for streaming operations.]]></description>
      <content:encoded><![CDATA[The article discusses findings from NETINT Technologies' 2026 State of Encoding Survey, which re-frames 'video engineering at scale' in terms of operational complexity rather than company size, distinguishing between Live-focused and VOD-focused operators with different primary constraints (talent vs. budget). It reports that 54% of respondents plan to evaluate GPUs and 52% plan to evaluate VPUs/ASICs in 2026, positioning hardware acceleration as a converging solution to both live and VOD bottlenecks. The piece emphasizes aligning technical and financial narratives when making encoding and infrastructure decisions for streaming operations.]]></content:encoded>
      <dc:creator><![CDATA[Mark Donnigan]]></dc:creator>
      <author><![CDATA[Mark Donnigan]]></author>
      
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