From Apes to Algorithms: When Hype Outruns the Law
This weekend, Beeple proved just how fragile digital markets can be.
At a CryptoPunks event in Charleston, he premiered an intentionally crude, AI-altered video claiming the Nakamigos NFT collection was a “V0 Punks” prototype by Larva Labs from 2015. It was satire or so he thought.
The market didn’t wait for fact-checks. Floor prices jumped 140%, $2M in NFTs traded hands, and over 1,200 Nakamigos sold before reality caught up. Beeple followed with a mock statement, trolling buyers with a fake “free NFT” claim and later posting an Everyday titled NO CRYING IN THE CASINO, showing himself in prison with a Nakamigo print.
Some called it performance art. Others called it market manipulation. Either way, it showed how a convincing story can trigger millions in minutes, regardless of whether it’s true.
We’ve seen this movie before.
In July 2025, the US Court of Appeals overturned Yuga Labs’ $8.8M trademark win in a Bored Ape Yacht Club case. Around the same time, they were (and still are) facing a class action accusing them of selling unregistered securities through celebrity NFT promotions. The parallels to Beeple’s stunt are striking: markets driven by perception, fueled by hype, and vulnerable to sudden reversals.
For NFTs, owning a token never guaranteed you owned the art’s copyright.
For AI-generated content, having the output file doesn’t guarantee you can use it commercially without risk.
The AI content parallel
AI’s legal gray zone is as wide, maybe wider, than NFTs ever were. In many jurisdictions, AI-only works can’t be copyrighted at all. If the underlying training data isn’t licensed, the risk of infringement claims rises.
Just as NFTs rode a wave of speculation without always being clear on what buyers were getting, AI content platforms often market “full rights” without the legal framework to back it up. The Beeple incident is a reminder that in hype-driven ecosystems, perception moves faster than truth, and the costs land later.
Why provenance matters more than ownership hype
NFTs proved that possession without clarity is fragile. AI will be no different unless trust is built in from the start. That trust comes from verifiable provenance:
Knowing where content came from
Knowing what data, models, or creators contributed
Knowing how much human creativity was involved
Knowing who can use it, and under what terms
Without that, even well-meaning creators, brands, and platforms risk lawsuits, pulled campaigns, or reputational damage.
The apes had their day in court. Algorithms will too. The winners won’t just be the fastest creators, they’ll be the ones who can prove exactly where their content came from and who’s allowed to use it.
Want to know exactly how this image was created and who holds the rights? See here with Metapyxl Lens.