DATA Ecosystem

Home of the Data Foundation ecosystem.

[DATA Ecosystem @Data_Ecosystem]

24 hours left in the DATA on Sui: Content Quest.

To enter:
▸ Create: original content about DATA on Sui
▸ Amplify: quote 3 of our DATA on Sui posts with your take.

Entries close Oct 28, 11:59pm PT. Last call ↓

[DATA Ecosystem @Data_Ecosystem]

@psdnai @corl_conf Nice work!

[Poseidon (✈️ CoRL) @psdnai]

We're honored to present research at @corl_conf.

Our team studied 500 hours of crowdsourced egocentric video to better understand where data collection goes wrong, and how to improve quality control for Physical AI.

One key finding: 90% of footage in flagged clips falls outside labeled failure intervals. Rejecting entire clips can mean discarding a lot of potentially useful data.

Tremendous work by @iamrashminagpal, @sebliu, @jdubpark, and Sandeep Chinchali.

First look at our research poster below. Catch us tomorrow at the 'Oops, I Erred' #CoRL2026 workshop ↴

[The DATA Foundation @datafdn]

Verifiable data infrastructure is coming to enterprise AI and finance with @spaceandtime.

Proud to be a launch partner as we continue building toward a future where data provenance, privacy, and verifiability are foundational to AI.

[DATA Ecosystem @Data_Ecosystem]

@psdnai @corl_conf @sebliu Go @sebliu 🦾

[Poseidon (✈️ CoRL) @psdnai]

Come say hello to the team at @corl_conf.

@sebliu will present our paper "When Crowdsourced Egocentric Video Goes Wrong: Failure Modes, Metadata, and Quality Control" at the "Oops, I Erred" workshop.

🗓️ November 12
📍JW Marriott Austin

[Poseidon (✈️ CoRL) @psdnai]

See you at @corl_conf 2026.

Our paper, "When Crowdsourced Egocentric Video Goes Wrong: Failure Modes, Metadata, and Quality Control," was accepted to the "Oops, I Erred" workshop at CoRL, a leading robotics research conference.

If you'll be in Austin, say hi: @sebliu + team will present our research on a critical challenge for Physical AI: how to ensure crowdsourced, real-world video data is reliable and useful for training robots.

https://t.co/lWrxDRSEu2

[DATA Ecosystem @Data_Ecosystem]

See rules and announcements in Discord ↓

https://t.co/qIUXB6HANg

[DATA Ecosystem @Data_Ecosystem]

24 hours left in the DATA on Sui: Content Quest.

To enter:
▸ Create: original content about DATA on Sui
▸ Amplify: quote 3 of our DATA on Sui posts with your take.

Entries close Oct 28, 11:59pm PT. Last call ↓

[DATA Ecosystem @Data_Ecosystem]

@otodotearth Nice work!

[DATA Ecosystem @Data_Ecosystem]

Our friends at @otodotearth are searching for contributors to support AI Training via video chats.

See post for details ↓

[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

[DATA Ecosystem @Data_Ecosystem]

Official Rules ↓

https://t.co/fX7o08ROOn

[DATA Ecosystem @Data_Ecosystem]

Help us tell the DATA on Sui story.

▸ $5,000 USDC prize pool
▸ 9 winners total
▸ Every prize $500+

Two ways to win ↓

[DATA Ecosystem @Data_Ecosystem]

Create: Make a thread, video, visual or meme about @datafdn x @SuiNetwork. $1k grand prize, 4 × $500 prizes, and a dedicated KR-language prize.

Amplify: QT our DATA x Sui posts with your take on why rights-cleared AI data matters. 4 × $500 prizes.

Closes Oct 28 11:59pm PT.

Full Details on Discord ↓
https://t.co/YDcH5ZJZms

[The DATA Foundation @datafdn]

The lifecycle of data, as told by the DATA protocol → @SuiNetwork.

[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.

[Altcoin Buzz @Altcoinbuzzio]

SUI is making a move for the AI data economy.

DATA Network is bringing its Trace registry to Sui, with Walrus as the default storage layer, giving AI labs a single place to source rights-cleared training data.

Why does that matter? AI models need data, but using data without clear rights can become a legal headache.

$SUI is positioning itself right where AI, data ownership, and decentralized storage collide. And that could get interesting fast.

[Mookie @MookieNFT]

Sui Foundation is investing $30 Million into $DATA.

That's a big deal friends.

Sui Foundation is becoming DATA's largest institutional investor. That's a strong sign of how much they believe in what @datafdn is building.

And this comes while the market is tough. A lot of teams are slowing down but DATA keeps leveling up.

Here's a quick look at what's going on:

> Sui Foundation is putting $30M into $DATA, becoming its largest institutional investor

> DATA has a product called Trace that helps track where AI training data comes from and whether companies have permission to use it

> Trace has already recorded 250M+ receipts since June

> DATA is planning to move from its own blockchain to Sui with Walrus becoming the default storage layer for DATA Foundation apps

> $DATA stays as the protocol token, with no immediate changes for holders

The part I like is that DATA already has something to build on.

Trace is live and growing and now the team has Sui Foundation's backing behind its plans.

Running a blockchain takes time and money, so moving to Sui could give DATA more time and resources to improve Trace and get more companies using it.

And with AI growing so fast, companies need more training data they can use without worrying about copyright or permission issues.

That's why I think DATA is focusing on the right thing.

They already have a working product and now with $30M in backing from Sui Foundation, the team has a great opportunity to grow.

Personally I like this move and I'm looking forward to seeing what DATA builds next. 🫡

[Ranjeet @0xranjeet]

@SuiNetwork @datafdn @WalrusProtocol DATA Foundation 🤝 Sui Foundation

[William | 116.sui @williamm168]

🤯 One of the wildest announcements I heard at Sui Basecamp day 2:

@Datafdn, formerly Story Protocol, is retiring its own L1 and plans to run natively on Sui. 😳

Think about that for a second.

Story spent years building a dedicated Layer 1 for programmable IP.

Then it became The DATA Foundation and shifted toward AI training data, with Trace already tracking massive amounts of provenance data.

And now the next step is apparently:

Stop maintaining a standalone L1 and build directly on Sui.

That’s much more interesting than another “partnership” announcement.

Sometimes the strongest endorsement of infrastructure is when another chain decides it doesn’t need to be a chain anymore.

This is a big one for @SuiNetwork.

[Eli5DeFi @Eli5defi]

After recording 250M+ Trace receipts, DATA’s next big challenge is turning all that activity into a stronger AI data business.

That’s why @datafdn’s planned move to Sui makes sense.

It could free the team to focus on what AI labs actually pay for: useful training data with clear rights and verifiable origins.

DATA began as Story Protocol, pursuing a broad vision for programmable intellectual property. In June, it narrowed its focus to AI training data, with Trace as its flagship audit product.

Now its infrastructure strategy is following that sharper focus.

Running an independent Layer 1 means maintaining blockchain software, coordinating upgrades, and supporting validator infrastructure. Those responsibilities draw on the same resources needed to improve products and win customers.

One team. Two demanding jobs.

For DATA, the strongest source of value is connecting data supply, permissions, and verification into something buyers can use with confidence.

Trace helps buyers inspect records of data origins, consent, licensing terms, and payment status, while keeping the underlying content confidential.

As I said before, DATA reports 250M+ receipts recorded by Trace.

The planned division of work is straightforward:

- Sui → shared blockchain infrastructure for DATA’s protocol

- Walrus → the planned default storage layer for DATA Foundation apps, suited to large files like images and video

- Trace → the audit and provenance product DATA can keep evolving around its specific market

The wider Sui stack also offers Seal for access control and Nautilus for verifiable offchain compute, giving DATA additional building blocks as implementation progresses.

The efficiency thesis is simple: Better resource allocation.

If shared infrastructure reduces the burden of maintaining a standalone chain, more engineering effort can go toward better verification tools, smoother integrations, and broader adoption.

Sui Foundation’s announced $30M investment adds institutional commitment to that direction. The partnership also gives Sui’s infrastructure a substantial data supply to support.

Execution still matters. Migration takes work, shared infrastructure comes with tradeoffs, and DATA will depend on another ecosystem. The efficiency gains need to become tangible.

The transition is still ahead. $DATA remains the protocol token, nothing changes immediately for holders, and more migration details will follow.

I think this is a credible comeback strategy both for DATA and SUI where both can apply the lessons from the broader experiment and concentrate resources where the product has the clearest purpose.

NFA. DYOR.