IP is Dead, Long Live IP

The Studio Ghibli trend that swept across social media this week wasn't just a flash in the pan—it was a preview of our creative future. Thousands of creators did what humans have always done throughout history: they remixed, recreated, and reimagined.

And here's the truth that IP traditionalists don't want to hear: the cat is already out of the bag, and it's in the style of Studio Ghibli.

Game of Whack-a-Mole

In Game of Thrones Cersei is supposed to face the Seven's tribunal and simply... doesn't show up. Instead, she obliterated the entire problem with wildfire. That's exactly what we're witnessing with AI and copyright enforcement.

Sam Altman and OpenAI showed their hand with their embrace of the Studio Ghibli trend. If they believed there was a legally credible threat or they didn't have enough money to make potential problems disappear, they wouldn't be leaning into this aesthetic so openly. They're following Cersei's playbook: why submit to outdated rules when you can change the game entirely?

The fundamental issue with the enforcement-first approach is that it mistakes "IP" in and of itself for leverage. But in the AI era, that leverage is rapidly eroding. Models will either scrape content anyway and exhaust rights holders with legal battles, or they'll completely disregard certain content altogether and build alternative datasets.

I've Played These Games Before

Back in 2017, I was at Amazon Music negotiating contracts with record labels and publishers to license their music for our streaming services. This was before the Music Modernization Act, when statutory damages for hosting content without proper licensing were severe.

My job? Researching our license coverage to reduce Amazon's risk.

What’s important to know is a song isn't just one piece of IP—it's split between the master recording (typically owned by labels) and the composition (lyrics and production, often split among multiple songwriters and producers).

Getting 100% licensing coverage was practically impossible because:

• Songs frequently came out before all the splits were even negotiated (especially in hip hop)

• Rights weren't registered consistently across music rights organizations, labels, and the Library of Congress

• Some rights holders deliberately failed to register their rights so they could sue for infringement later

This broken system led me to research onchain licensing alternatives like dotblockchainbc and ujomusic—decentralized ledgers that could create transparent, accessible records of music rights.

But here's why those solutions never took off: the legacy players had zero incentive to change the system.

Major labels and publishers preferred going directly to streaming services where they could leverage their market power for better deals. They even grabbed pro-rata shares of revenue from unlicensed music. Meanwhile, streaming platforms weren't motivated to empower independent creators with transparency that might increase their collective bargaining power.

Incumbents profit from confusion and obscured information. Their leverage comes from perceived power, not actual innovation. Creating a more equitable, transparent system ultimately comes at their expense.

Sound familiar? We're seeing the exact same dynamics play out in the AI space today. This is why you see characters from major franchises somewhat protected while smaller creators have no viable alternatives. The largest rightsholders—Disney, Warner, etc.—have the financial resources and legal clout to negotiate agreements with AI models, while independent creators are left out in the cold with no recourse.

This two-tier system isn't just unfair—it's unstable. As AI capabilities advance and multiply, even the giants will struggle to maintain their moats through legal means alone. What's needed isn't more aggressive enforcement but a fundamental rethinking of how creative value is captured and distributed.

The DreamNet Alternative

Instead of playing an endless game of enforcement whack-a-mole, what if we focused on giving creators and communities the tools to work alongside AI?

This is where DreamNet comes in—a protocol that flips the script by building a deep data lake of universes, stories, characters, and places that creators collectively own and benefit from.

Rather than fighting the tide of derivative content, DreamNet uses the memetic attention as a tailwind to drive interest back to the underlying universe. When your IP is remixed, that's not theft—it's an opportunity to bring new audiences into your proprietary data ecosystem.

Think about it: how many people first heard the name "Ghibli" just this week? While Miyazaki-san might disagree with the AI-generated content, I'd bet he's not upset about the new legion of fans who might watch "Spirited Away" or "Princess Mononoke" for the first time.

Creating Value Through Data Moats, Not Legal Fences

The most valuable resource in the future of AI content isn't copyright claims—it's proprietary data that creates experiences others can't replicate.

DreamNet creates a system where:

• Communities collectively own their creative universes

• Contributors are incentivized to build on existing worlds

• Value flows back to creators when their ideas are referenced

• Fans become co-creators rather than passive consumers

The Future of Creative Licensing

There will likely come a day when we have new regulatory frameworks for content licensing, similar to what eventually happened with music streaming. But until then, creators have a choice:

Spend resources fighting an unwinnable battle against remixing and derivation or build a system where remixing and derivation become part of your moat and monetization strategy.

In a world where everything is derivative and everything is a remix, the winners won't be those with the most aggressive legal teams. They'll be the ones who build the richest collaborative data ecosystems that others want to plug into.

The future belongs to those who own their worlds, or they'll be forced to live in someone else's.