Andrea

Building the world's AI data network. CEO @datafdn

[Andrea @devrelius]

Data exclusivity is a massive problem in the ai training data space.

Vendors sell “exclusive” data to multiple buyers and they can’t verify it’s actually exclusive without some audit trail. That is what Trace is.

If you are buying an exclusive dataset you should be confident it’s actually exclusive. The best way to check is to see if that data already exists on Trace.

Force your data vendor to use Trace and protect yourself!

[Andrea @devrelius]

@lou3ee Lovely work sir

[Andrea @devrelius]

Help train AI, earn 50 bucks an hour and you have the peace of mind that all your contributions will be fully tracked on Trace!

[oto @otodotearth]

We're looking for people to help train AI through video chats with a friend!
Up to $50/h per eligible recorded hour, per person.
10-minute chats. US residents 18+. Face and voice used in commercial AI datasets.
Hours not guaranteed. Eligibility and rates: https://t.co/NCu9F1hJQe

[Andrea @devrelius]

@otodotearth Great work!

[Andrea @devrelius]

https://t.co/zzrGBLTz7p

[Andrea @devrelius]

@EmanAbio @WalrusProtocol Excited to partner with you!

[Adeniyi.sui @EmanAbio]

soon you'll see more and more AI use cases landing on @WalrusProtocol

THIS IS JUST A START

[Andrea @devrelius]

100%. This is why what we are doing with Trace is so important.

and you can all now see why we are teaming up with Sui and Walrus.

[Kimberly Logan @kimblgn]

One of the defining questions of the AI era is going to be “How do you know?”

How do you know what is real when anything can be generated? How do you know what really happened versus what you were told happened? How do you know where a piece of data came from? How do you know it has not been changed? How do you know what an agent actually did on your behalf?

I think about this all the time

Verifiability is going to matter as much as intelligence

[Andrea @devrelius]

@Moshaikh Solid take. Very much agree that we will see more and more consolidation in the industry, and this convergence will actually help interoperability as a whole as well.

[Andrea @devrelius]

One of the main reasons Sui stood out is they already built a lot of the components needed for Trace to grow as the data layer end to end:
- storage (walrus),
- dynamic access control (seal),
- verifiable (but off chain) compute like inference in TEEs (nautilus).

Sourcing, access control, processing and inference can now be all on the same stack, and Trace’s audit layer can formally prove and verify every single step giving more depth and weight to the metadata it stores in turn becoming a source of truth for AI data.

This is the master plan for Trace.

[The DATA Foundation @datafdn]

The lifecycle of data, as told by Data Network → @SuiNetwork.

[jacob @jacobmtucker]

Trace registers over 3M data receipts EVERY DAY

Currently, we are able to surface tons of metadata related to a receipt's provenance:

- Did the contributor sign ToS/PP?
- Where did the data come from?
- When was it captured/uploaded? By what device?

This is the 1st major step in making the data that apps like @useKled collect SELLABLE to AI labs

But the next step is actually verifying ourselves that this information is true:

- Scanning the file itself to discover its metadata
- Verifying the data wasn't tampered with
- Keeping the original copy

By storing files on @WalrusProtocol, we can verify that every data receipt is what is says it is

And give frontier AI labs the complete confidence needed to purchase data in bulk

Trace turns any company into a data company

[Andrea @devrelius]

@shivst3r Great progress! Slow but sustainable progress beats optimal/obsessive but unsustainable progress (which I have been guilty of in the past). Sounds like you definitely found the former! Keep it up 💪

[The DATA Foundation @datafdn]

DATA is coming to Sui. So, what happens next?

Read on ↓

[Andrea @devrelius]

@theSYlee @datafdn Excited for this new chapter 💪

[Andrea @devrelius]

This is a big step forward for DATA with a $30M investment from Sui. This makes Sui Foundation the largest holder of DATA, above DATA Foundation and PIP Labs.

Our founder SY Lee is also joining Sui as a strategic adviser on AI and training data.

Most importantly, bringing Trace and the 275M+ data receipts onto the Sui stack gives us the infrastructure to go beyond provenance alone, with reference data storage, access control, and stronger verification for the real-world data AI increasingly depends on.

Excited for what we will build together.

[The DATA Foundation @datafdn]

DATA is coming to @SuiNetwork.

The DATA Network and Trace are joining the Sui stack, bringing a live supply of rights-cleared AI training data to infrastructure built for AI workloads.

With 250M+ receipts already recorded by Trace, AI labs will be able to source real-world data with verifiable provenance, while @WalrusProtocol provides the underlying storage layer.

Sui Foundation is investing $30 million in the DATA Network, establishing the largest institutional stake in the network, alongside the continuing holdings of PIP Labs and the DATA Foundation. Furthering the alignment, SY Lee, founder of the DATA Network and CEO of PIP Labs, joins Sui Foundation as Strategic Advisor.

In the coming months:

▸ The DATA Network will be upgraded to run as a protocol natively on Sui
▸ Walrus becomes the default storage layer for DATA Foundation apps
▸ $DATA remains the token of the DATA protocol

The next chapter of DATA starts here.

[Andrea @devrelius]

Big day today 👀

[The DATA Foundation @datafdn]

CEO @devrelius has been busy at:

▸ @WeAreDevs
▸ @kbwofficial
▸ @token2049

Next stop: Sui Basecamp @SuiNetwork.

[Andrea @devrelius]

watching frontier traders compete is fun but did u know there’s a ultra high concentration of Nobel prize winners discussing AI and data rn in Singapore?

Sir Konstantin Novoselov - Nobel Prize in Physics 2010
Prof. Benjamin List - Nobel Prize in Chemistry 2021
Fred Ramsdell - Nobel Prize in Physiology or Medicine 2025
Sir Christopher Pissarides - Nobel Memorial Prize in Economic Sciences 2010
Prof. Omar M. Yaghi - Nobel Prize in Chemistry 2025

[Andrea @devrelius]

Expert data is the bottleneck

[MTS @MTSlive]

Paradigm GP @danrobinson says even 10,000 Ilyas in a data center wouldn’t necessarily lead to runaway RSI because compute and expert data would become the bottleneck:

"I'd say I'm very RSI pilled. This may be marginally less RSI pilled."

"Even if we had 10,000 Ilyas in a data center, are we gonna give them 10,000 times as much compute? We just don't have that in the world. Are we gonna somehow generate 10,000 times as much human expert data? We don't really have the ability to do that."

"You can actually go quite far probably with just automating labor, but then you quickly are gonna run into these other bottlenecks."

"That said, you can still get obviously very insane results even in the presence of those bottlenecks."
@paradigm

[Andrea @devrelius]

@0xNock Trying this out! Thanks for the tip

[Andrea @devrelius]

@GoKiteAI @catdaly @Cindyshi0907 @spaceandtime @datafdn Was a pleasure sharing the stage with you!