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H3 Company withdraws from Nvidia AI scraping lawsuit

Ted Entertainment dropped its individual claims in a class action against Nvidia, though the broader lawsuit regarding AI training data continues.

October 27, 2026Date of Ted Entertainment's withdrawal

The short version

Why it matters

This shift shows how individual creators may choose different legal paths even when facing the same tech giants. It highlights the ongoing legal uncertainty surrounding how AI companies gather training data from public platforms.

The withdrawal of H3 claims

Ted Entertainment, Inc., the company that produces the H3 Podcast, officially stepped back from its specific legal claims against Nvidia. The company filed this notice on October 27, 2026, regarding a proposed class action lawsuit. This move means the H3 Company is no longer pursuing its own independent set of claims against the chipmaker.

The notice specifies that the dismissal was made without prejudice. In legal terms, this means that Ted Entertainment has not waived its right to participate in the lawsuit in the future. The company can still potentially join as a member of the class or recover damages if the case eventually reaches a settlement or a court ruling.

While the H3 Company is stepping out of the lead role, the legal action itself is not being dropped entirely. The lawsuit will now be captioned as Fisher v. Nvidia Corporation. This change reflects a narrowing of the specific plaintiffs leading the charge while keeping the core legal arguments intact.

The ongoing Fisher lawsuit

Matt Fisher, a well-known golf content creator, is staying on as a plaintiff in the ongoing litigation. Because he remains involved, the proposed class action continues to move forward in the court system. The case focuses on how major technology companies interact with content hosted on YouTube.

The lawsuit originated from a series of parallel proposed class actions filed between November 2025 and April 2026. These filings targeted several major tech entities including Nvidia, Meta, ByteDance, Snap, Apple, OpenAI, and Amazon. Each of these actions stems from similar allegations regarding the collection of data for artificial intelligence.

The primary focus of these legal challenges is the method by which these companies obtain their training materials. The plaintiffs argue that these tech giants have circumvented specific technological protections. They claim these actions violate the Digital Millennium Copyright Act, which is a federal law intended to protect copyrighted works from unauthorized distribution.

How AI scraping works

At the heart of this dispute is the process of scraping, which involves using automated tools to collect large amounts of data from the internet. In this specific case, the allegations center on scraping videos from YouTube to train AI models. AI training requires massive datasets to help machines learn patterns, speech, and visual information.

The plaintiffs allege that the companies involved bypassed the technical barriers YouTube puts in place to protect its content. By bypassing these protections, the companies could allegedly access and use video data in ways that the platform did not intend. This has sparked a significant debate over the boundaries of fair use and copyright in the age of machine learning.

The companies being sued, including Nvidia, have consistently disputed these claims. They maintain that their practices do not violate the law or the terms of service of the platforms involved. Because these cases are still in the early stages, no defendant has been found liable and no class has been officially certified by a court.

Impact on content creators

For creators like those behind the H3 Podcast or Matt Fisher, these lawsuits represent a fight over the ownership of digital content. Many creators worry that their videos are being used to build commercial products without their permission or compensation. The legal outcome could determine how much control creators have over their work once it is uploaded to public platforms.

The fact that multiple creators filed parallel suits suggests a coordinated effort to address perceived systemic issues in AI development. By forming a class action, creators hope to have a larger impact on how tech companies handle data. However, the withdrawal of one major creator shows that different entities may have different strategies for handling these complex legal battles.

Currently, there is nothing for creators to claim because the case has not reached a final judgment. The court has not yet certified a class, which is a formal process where a judge decides that a group of people can sue as a single unit. Until that happens, the legal status of these claims remains in a state of flux.

What to expect next

The legal battle will continue under the new caption of Fisher v. Nvidia Corporation. The court will need to determine whether the technological protections of YouTube were actually bypassed and if those actions constitute a violation of the DMCA. This process can take a significant amount of time as it involves complex technical evidence and legal arguments.

Observers will be watching to see if more creators join the class or if other companies are added to the litigation. The outcome could set a precedent for how AI companies are allowed to gather training data from social media and video platforms. It may also influence the terms of service that platforms like YouTube offer to their users.

If the court eventually certifies the class or if a settlement is reached, all potential class members would be notified through the official court process. For now, the case serves as a significant marker in the ongoing tension between the creators of the internet and the companies building the next generation of AI tools.

What to watch

Try it

Check the official court records for 'Fisher v. Nvidia Corporation' to see the current status of the proposed class action.

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First reported by openclassactions.com · Read the original. Written by the SI Agent News Desk from the reporting above.Written with AI from the source above. Every number is checked against the source. Spot a mistake? Corrections.

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