Edge
When people hear Oracles, they think of price or risk feeds—crucial tools for decentralized finance. For instance, our own Edge Price Oracle has already secured over $40 billion in assets. But that's just one application.
We’re expanding the definition of an Oracle. At its core, an Oracle is more than a protocol to source and deliver high-integrity, reliable, authentic, and secure data between networks. It adds a crucial truth-seeking layer of verification and filtering. Oracles don’t just deliver data—they ensure it’s trustworthy. Using truth-seeking algorithms, Oracles will filter out misinformation and manipulated data, safeguarding the applications and networks they serve.
The exact models and heuristics Oracles will use will vary by domain—whether it’s blockchain, web apps, or private networks—but every application will need this layer of protection. In a world flooded with AI-generated content and misinformation, trust will become the ultimate currency.
This essay explores a different use case for Oracles. As AI makes fakes abundant, the need to preserve truth becomes critical. Here, we focus on understanding the problem. Future posts will dive into the solutions we’re building at Chaos Labs to combat this growing epidemic.
The Age of Fake Everything
The ease with which fake content can now be generated is alarming. AI can spit out texts, voices, and even simulated interactions almost indistinguishable from reality. Meanwhile, Sybil attacks—where one entity pretends to be many—are cheaper and more scalable than ever.
How Much Does it Cost to Build a Fake Empire?
In the age of AI, creating an empire of fake content is no longer a question of resources but one of scale. With the ability to mass-produce convincing replies, posts, or even entire conversations at minimal cost, the barriers to flooding the internet with synthetic data have disappeared. The real challenge isn’t producing content—it’s filtering it. As generative AI drives the cost of creating fake data to near zero, the value shifts to those who can distinguish real from fake. Let’s break down how cheap it is to build this fake empire.
- GPT-4 Pricing:
- Input: $5 per 1 million tokens.
- Output: $15 per 1 million tokens.
- Token Breakdown (per tweet):
- Input tokens: 20 tokens (tweet).
- Output tokens: 10 tokens (reply).
- Cost per Reply:
- Input: 20 tokens = $0.0001
- Output: 10 tokens = $0.00015
- Total: $0.00025 per reply.
- Scaling:
- 10,000 replies = $2.50
- 1 million replies = $250
In short, Generative AI makes fake data abundant—authenticity becomes a scarce, valuable resource.
When Everything Is Fake, What Matters?
In a world flooded with AI-generated content, how do we know what's real?
A slick app won’t cut it—AI will commoditize design. The true test will be whether apps can prove their data and interactions are authentic. This will be the line that separates the good from the worthless.
Oracles will be essential here. Like spam filters save your inbox from junk, oracles will save your app from fake data and interactions.
Scale Is Solved, Authenticity Isn’t
Technology has solved a lot of the hard problems. Consider three shifts:
- Code is getting automated. AI tools like GPT-o1 can generate code faster than human developers, making app building quicker and cheaper.
- Scaling apps is trivial. Cloud infrastructure means even tiny teams can scale to millions of users.
- User experience is commoditized. AI-powered design tools mean every app can now look polished and professional.
If code, scale, and design are no longer differentiators, what's left? Data authenticity and network effects.
The Value of Authentic Networks
What’s the most valuable part of any application? It’s the network of users. That’s where the data, content, and interactions come from. But as bots get better at mimicking human behavior, authenticity becomes the rarest and most valuable commodity.
Real users, real data, and real interactions will define the winning applications of the future. The networks that can maintain trust will thrive. Oracles will be the key to ensuring that the data feeding those networks is real.
Oracles: The New Backbone of the Web
AI-generated content is already everywhere. Soon, the need for data integrity will be as universal as the need for electricity.
Think of Oracles as the filters of the future web:
- They’ll screen data before it’s allowed into your app.
- They’ll reject fake inputs generated by bots and bad actors.
- They’ll ensure that interactions are based on verified, authentic data.
Without Oracles, the digital world will collapse under the weight of fake users and fake information. The more this happens, the faster trust erodes—and once trust is gone, everything else falls apart.
Oracles: The Infrastructure of Trust
As AI-generated fakes flood the digital world, trust becomes the most valuable asset. Success won’t come from flashy interfaces but from authentic, verifiable networks. Oracles are the key to ensuring that only verified data enters these systems.
From blockchains to web apps, platforms will depend on Oracles to filter and authenticate data. The future belongs to those who understand that trust is the new competitive edge.
In an era of abundant fakes, Oracles form the foundation of a digital world built on authenticity.