In short: Three YouTube content creators, specifically the company behind H3H3 Productions, a solo golf presenter, and a golf channel, have filed a proposed class action lawsuit in Seattle alleging that Amazon bypassed YouTube’s technical protections using virtual machines and rotating IP addresses to scrape their videos without consent, feeding the footage into training datasets for Nova Reel, its generative video AI model available through Amazon Bedrock. The suit invokes the anti-circumvention provisions of the Digital Millennium Copyright Act and is the latest in a series of similar cases the same group has filed against Nvidia, Meta, ByteDance, Snap, OpenAI, and Apple.
Ted Entertainment Inc., the company behind H3H3 Productions and H3 Podcast Highlights, the YouTube channels run by Ethan and Hila Klein, filed the complaint in the US District Court for the Western District of Washington alongside Matt Fisher, who runs the MrShortGame Golf channel, and Golfholics Inc. The three plaintiffs collectively account for more than 2.6 million YouTube subscribers, approximately four billion combined views, and more than 5,800 original videos. The suit names Amazon as the defendant and targets Nova Reel specifically as the product built, in part, on their content.
The complaint and its legal theory
The lawsuit rests on Section 1201 of the Digital Millennium Copyright Act, the anti-circumvention provision that prohibits bypassing technological protection measures put in place by copyright holders to restrict access to their works. The plaintiffs argue that YouTube’s systems for protecting its video files constitute such technological protection measures and that Amazon circumvented them deliberately and at scale to extract training data. If the theory holds in court, it would establish that the act of downloading YouTube videos for AI training purposes constitutes a DMCA violation regardless of whether the content is publicly viewable, because circumventing the technical mechanisms that enforce terms of service crosses the statutory line.
The complaint draws attention to what the plaintiffs describe as the permanent nature of the harm: “Once AI ingests content, that content is stored in its neural network and not capable of deletion or retraction.” The plaintiffs are seeking both damages and injunctive relief, the latter potentially forcing Amazon to stop distributing a model trained in part on their content or to retrain it without the disputed material.
How the scraping allegedly worked
The complaint centres on two academic datasets: HD-VILA-100M, produced by Microsoft Research Asia in 2021, and HD-VG-130M, produced by researchers from Peking University and Microsoft. Both were published for academic purposes and consist of URL identifiers pointing to YouTube videos rather than the video files themselves. That distinction is legally significant: to use either dataset for AI model training, a company must download the actual video files from YouTube, and the plaintiffs allege Amazon did exactly that.
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According to the complaint, Amazon did not simply download the videos. It deployed automated programmes combined with virtual machines that rotated IP addresses continuously to evade YouTube’s detection and blocking systems. The combination of these technical measures, namely automated mass downloading, virtual machine infrastructure, and IP rotation, is characterised in the complaint as a deliberate circumvention of the technological protection measures YouTube maintains over its video library. The same evasion pattern was alleged in this group of plaintiffs’ earlier suit against Nvidia, which the complaint in that case said had downloaded 38.5 million video URLs using comparable infrastructure.
Nova Reel and Amazon’s video AI ambitions
Nova Reel is Amazon’s text-to-video generative AI model, launched in December 2024 and made available through Amazon Bedrock. The model accepts text prompts and images as inputs and generates video clips ranging from six seconds to two minutes in length, with a watermarking feature that Amazon positions as a content authenticity measure. It sits within the broader Nova model family, which Amazon has been expanding across text, image, and video modalities as competition in enterprise AI accelerates.
The competitive pressure on Amazon to build capable video AI is substantial. Nova Reel represents the company’s attempt to compete with Sora, Google Veo, and other text-to-video systems for enterprise workloads. Amazon’s wider AI infrastructure investment, including its partnership with Uber to deploy custom Trainium chips for large-scale model training via AWS, reflects the breadth of the company’s ambitions across the AI stack, from cloud compute to generative media. The capital available to frontier AI developers has intensified the competitive pressure to acquire training data at speed and at scale, with SoftBank’s $40 billion bridge loan to OpenAI illustrating the resources flowing into the race for generative AI supremacy.
A pattern of lawsuits, and a legal theory in development
The three plaintiffs arrived at this complaint with prior litigation experience. The year 2025 was one in which AI training data practices moved from an industry footnote to the subject of co-ordinated legal action. In December 2025, Ted Entertainment, Fisher, and Golfholics filed a proposed class action against Nvidia in California federal court, alleging that Nvidia scraped their YouTube content using the same HD-VILA-100M and HD-VG-130M datasets and the same IP-rotation and virtual machine infrastructure to train its Cosmos video model. In January 2026 the group extended the strategy, filing suits against Meta, ByteDance, and Snap. In the first week of April, parallel complaints against OpenAI and Apple were filed in the Northern District of California. The Amazon suit, filed in Seattle, is the most recent entry in the sequence.
The suits arrive as the broader wave of copyright litigation against AI developers continues to grow. The number of US copyright cases filed against AI companies has now surpassed 100, a figure that includes a March 2026 complaint from Encyclopaedia Britannica and Merriam-Webster against OpenAI, alleging that nearly 100,000 of Britannica’s articles were used as training inputs without consent. That case, like the YouTuber suits, relies on the argument that AI developers have systematically extracted content from publishers and creators whose work underpins the capabilities that those developers are now commercialising.
The academic dataset mechanism sits at the centre of what the plaintiffs’ legal theory is attempting to challenge. By alleging that downloading video files pointed to by an academic URL index constitutes a DMCA violation, the suits target the gap between the published URL list — which carries a veneer of academic legitimacy — and the actual extraction activity required to use it. Questions about how frontier AI models source and handle their training data have come into sharper focus in 2026, as scrutiny of the industry’s data supply chain has intensified. If courts accept the plaintiffs’ reading of Section 1201, the practical consequence would be that AI developers using academic video URL datasets as a path to training footage face the same exposure as developers who downloaded that footage directly. Amazon, like the other defendants in this series of suits, has not commented publicly on the filing.
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