The DATA Foundation @datafdn
AI-native infrastructure for real-world data. Formerly known as Story. datafdn.org Joined December 2021-
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Today at @WeAreDevs World Congress North America, DATA Foundation CEO Andrea Muttoni @devrelius joins The New Security Stack to discuss what needs to change as AI takes on more of the work. → Tech Leaders Stage → 1:30pm PT → San José, CA See you there.
Every piece of human contributed data is a unique asset and gets a fingerprint on Trace! 250M assets and counting..
Just released visual updates to Trace, the public audit ledger for AI training data. It's now a little easier for AI labs to verify the data they're purchasing, and for data companies to turn the raw data they collect into verifiable, sellable datasets.
Just released visual updates to Trace, the public audit ledger for AI training data. It's now a little easier for AI labs to verify the data they're purchasing, and for data companies to turn the raw data they collect into verifiable, sellable datasets.
250M+ data registrations on Trace. That’s 250M+ verifiable receipts for where data came from, how it was collected, and the rights attached to it. Receipts make your data easier for AI labs to trust, evaluate, and buy. Every company can be a data company.
Blasting towards 250M AI training data assets registered on Trace!
Trace the frontier
Every company will become a data company sooner or later. It’s just a matter of when, and for who. This is why Trace exists, to help companies become data companies in the correct way, with the right transparency and full auditability.
Fun fact for those not in the industry: a month ago the AI Office got the power to fine AI providers up to 3% of global turnover...and is already sending formal requests to labs that couldn't produce a detailed summary of what they trained on. Trace preemptively solves this.
81% of enterprises surveyed have delayed, scaled back or abandoned an AI initiative because of data permission and governance gaps. 93% encountered permission or governance issues within the AI lifecycle. Valuable data ≠ sellable data We're building Trace to close that gap.
Trace is where labs verify provenance, contributors confirm consent, and regulators audit the source. For AI labs and data contributors, you can verify your data easily. Try for yourself ↓ trace.datafdn.org/verify#your-da…
81% of enterprises surveyed have delayed, scaled back or abandoned an AI initiative because of data permission and governance gaps. 93% encountered permission or governance issues within the AI lifecycle. Valuable data ≠ sellable data We're building Trace to close that gap.
Every company is a data company
The days of black box AI training are quickly coming to an end. When companies, individuals and governments come knocking and asking whether their data is in a model, you’ll wish you had kept track. This is what Trace does. Future proofing your AI.
Physical AI is a data problem before it’s a deployment problem. It’s exactly the challenge Poseidon is built to address.
Physical AI has a data problem. To operate in the real world, models need to learn from human experience. The scale of what that demands is increasingly clear: ↳ $7T potential humanoid market by 2050 ↳ $11.9B → $49.8B AI training dataset market by 2031 ↳ ~100K hours of
Awesome progress from the Oto team! 🔥 ps All contributions fully attributed on Trace 💪
We fine-tuned a public end-of-turn model on full-duplex conversation we collected ourselves, with turn-taking labels on every pause. False interruptions fell from 63.0% to 33.0%.
Browse all data registrations. Over 210M receipts and counting: Trace.datafdn.org
A cheat sheet for understanding Trace: ▸ Each Trace registration creates an auditable record ▸ Those records persist as data moves between parties ▸ It doesn't store underlying data ▸ The data is never public Think of it as a ledger for data.
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