How Constellation Network and Common Crawl Are Revolutionizing AI Training Data

3 min readDec 18, 2024

The Web3 space and AI landscape are rapidly evolving, but one of the biggest challenges remains: ensuring the integrity and trustworthiness of data. Constellation Network, in collaboration with the Common Crawl Foundation, just dropped some big news that cuts through the hype and delivers real innovation.

Together, they’ve built the first cryptographically secure, immutable archive of internet data for AI training and development. And it’s a game-changer.

Check out today’s livestream hosted by Genfinity:
https://x.com/i/broadcasts/1OwGWNQPAkRKQ

Check out the official press release: https://www.prnewswire.com/news-releases/common-crawl-foundation-and-constellation-network-announce-partnership-to-bridge-blockchain-and-ai-302283983.html

The Big Picture: Why This Matters

AI’s rapid growth is fueled by data — mountains of it. But here’s the rub: the provenance, integrity, and ethical sourcing of that data are often murky at best. Enter Constellation and Common Crawl, who are tackling these challenges head-on with a blockchain-based solution that ensures transparency, security, and accountability.

Think about it: 17 years of internet crawl data — a whopping 9 petabytes (that’s the equivalent of 2.25 million HD movie files @ 4 Gigs each!) — that’s used by 80% of Large Language Models (LLMs) is now accessible through an immutable, cryptographically secured network. Built on Constellation’s blockchain, this archive is not just a technical marvel; it’s a leap forward for ethical AI development.

According to Common Crawl’s Head of Development, Wayne Yamamoto:

“There’s a huge demand from all of the LLMs that say we want to know the provenance of the data, where it’s coming from, and have it be authenticated.”

How It Works: The Tech Behind the Magic

Constellation and Common Crawl’s partnership introduces a metagraph (an application-specific blockchain running on Constellation’s Hypergraph network) that’s tailored for AI developers. Here’s what makes it stand out:

Comprehensive Data Archiving: The entire history of internet crawls can now be securely stored in an immutable format. This means AI developers can trace their training datasets back to their source with unprecedented transparency.
End-to-End Encryption: Cryptographic security ensures the integrity of data from collection to AI model training, addressing a critical gap in the current AI development lifecycle.
Ethical AI Framework: By providing traceable and secure data, this solution tackles the growing concerns around how data is collected, stored, and used in AI.

And here’s the kicker: this system uses Constellation’s $DAG token to compensate validators to secure the network, showing how cryptocurrencies like $DAG are not just speculative assets but functional tools for business operations.

Real-World Applications: Who’s Already Using It?

The buzz isn’t just theoretical. Advanced AI research initiatives are already taking notice. Take TraceAI, for example. This project, developed under the National Science Foundation (NSF) and SBIR program, is leveraging Constellation’s blockchain to enhance their training models with immutability, auditability, and proof of authorship. They’re even working on advanced watermarking technologies to track the origin of data — a huge win for ethical AI.

What’s Next?

This is just the beginning. Over the coming months, Constellation and Common Crawl will expand their offerings, integrating cryptographically validated access into the standard distribution of internet crawls.

Developers can already explore these verified historical crawls for their AI applications using Constellation’s $DAG explorer: https://mainnet.dagexplorer.io/

Kevin Jackson, VP of Space Domain Communications at Forward EdgeAI, highlighted the significance:

“If you think of the internet as a repository of global knowledge, adding tags to that knowledge and implementing governance to ensure AI remains ethical can create a powerful cycle. The AI can then improve the tagging process, and this recursive system has the potential to benefit us in many ways.”

Ben Jorgensen, Constellation CEO, summed up Constellation’s role:

“We’re focused on creating a machine learning lifecycle that starts with the origin of data. Constellation then processes it through a verification checklist, enabling the creation of custom training models. From there, we add watermarks to those models, establishing a new pedigree for the data. This enhances the flywheel effect by putting that verified data pedigree onto a blockchain, ensuring it has gone through the proper checks and balances.
This space is still in its early stages, but I believe we’re among the first movers here.”