The PRL @BinanceWallet Alpha Trading Competition just launched, with $200K in rewards available for participants!
Early Bird multipliers are already active, and qualified users can also unlock the Rising Trader Boost.
Don’t miss this one. Get all the info here 👇
binance.com/en/support/annou…
Join the #Binance Alpha PRL Trading Competition now!
🔸 Trade PRL with $200K worth of rewards up for grabs.
🔸 Click [Join] on the Binance App event page to start tracking trade volume.
🔸 New: Rising Trader Boost — Qualified Alpha competition traders can unlock a 1.2x trading volume boost. See campaign details to check your eligibility.
🔸 Early Bird Multiplier is on — the earlier you trade, the higher the boost. Day 1 trades enjoy a 2.5x multiplier.
🔸 Only buy volume counts (selling is excluded).
Don’t miss out 👇
binance.com/en/support/annou…
Perle in NYC 🗽
Our team will be at @ethconf by @ETHGlobal next week.
If you're attending, come say hi 👋
We'll be around throughout the event meeting builders, teams, and anyone interested in the intersection of AI and human intelligence.
See you there.
There’s a quiet shift happening underneath AI development.
The most valuable training data is no longer just labeled at scale. It is reviewed, validated, and improved by people with real domain expertise.
A thread on why the next era of AI data needs an expert economy 👇
The next generation of AI data infrastructure should work differently.
Contributor history should be tracked.
Domain specialization should be visible.
Reputation should compound over time.
Access to higher-value work should be tied to demonstrated quality.
That is how an expert economy forms.
At Perle, this is the future we are building toward:
✅ Expert-validated data.
✅ Reputation-based contribution.
✅ Transparent incentives.
✅ Human expertise that compounds over time.
Because the next era of AI will depend on better systems for finding, verifying, and rewarding the people who make that data trustworthy.
Last week, we talked about why the strongest AI systems still need humans in the loop.
Not as a bottleneck, but as the layer of judgment behind better data, safer evaluations, and more reliable model behavior.
The next question is just as important: Can that human work be traced? ⬇️
The next generation of AI infrastructure needs to make that trust native.
Every contribution should have a record.
Every contributor should have a reputation.
Every validation step should be traceable.
Every dataset should carry its own history.
That is where on-chain audit trails become relevant: a tamper-resistant record of how data was created, who verified it, and why it can be trusted.
At Perle Labs, this is the foundation we are building toward:
Expert-validated.
Human-verified.
On-chain auditable.
Because the next era of AI will not only depend on better human feedback.
It will depend on whether that feedback can be traced, verified, and trusted.