i decided to test the @Pan_Ecosystem Playground with a simple prompt: “Analyze data.” 👀
here's what i got 👇
🔸 it generated a python example using 5 sample crypto wallets.
🔸 it ran the analysis and displayed the total volume, average transactions per user, and the wallet with the highest volume.
🔸 it explained the results step by step in a way that's easy to understand.
the whole process took around 15 seconds.
another thing i liked is that i could copy or download the code directly from my phone. no need to sit in front of a computer.
for anyone exploring AI tools, this is a simple way to test a model's capabilities before integrating it into an app or agent using an API key.
still exploring #PAN and discovering more features as i go. one step at a time.
have you tried the Playground yet ?
𝗔𝗜 𝗮𝗴𝗲𝗻𝘁𝘀 𝗻𝗲𝗲𝗱 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲. 𝘁𝗵𝗲𝘆 𝗻𝗲𝗲𝗱 𝗮 𝘄𝗮𝘆 𝘁𝗼 𝗽𝗮𝘆.
that’s where @Pan_Ecosystem comes in.
PAN is building an on-chain AI payment protocol designed for the autonomous AI agent economy, enabling agents to exchange value automatically in real time.
a few things caught my attention 👇
🔸 𝗖𝗲𝗿𝘁𝗶𝗞 𝗦𝗸𝘆𝗻𝗲𝘁 𝗦𝗰𝗼𝗿𝗲: 79.78 (BBB)
🔸 ranked #12 in PayFi on BNB
🔸 pre-launch stage
🔸 reported two $1M funding rounds
as AI agents become more autonomous, payment infrastructure could play an important role in how they interact and transact.
i've started exploring @Pan_Ecosystem early and will be contributing to the ecosystem.
join us here:https://t.co/QfiT6aaT5V
#PAN #AI #PayFi
starting my #PAN journey
exploring a more open future for ai compute with @Pan_Ecosystem
pan is building a demand layer for ai computations, and i'm getting started early.
-> go to:https://t.co/QfiT6aaT5V
• sign up
• go to the pan tasks section
• complete tasks to earn points
• stay active for future updates
#PAN
4.2M$ yatırımlı PAN'da puan toplamaya başladım, az kişinin kastığını düşünüyorum. @Pan_Ecosystem
PAN, otonom yapay zeka ajanları arasındaki etkileşimler için tasarlanmış, zincir üzerinde (on-chain) bir ödeme protokolüdür.
→ Platformu epeyi beğendim, uğraşmışlar yapmışlar belli ki.
→ Platformu öğrenene kadar basit görevleri yapacağım.
Değerlendirmek isteyen varsa buradan başlayabilirsiniz.
https://t.co/7iuBcFtQlv
Cc: @NikkiSixx_7 teşekkürler
Erkenden yerimizi alalım 🪂
Projelere erken aşamada katılmak önemlidir.
@Pan_ecosystem AI hesaplamaları için talep katmanı içeren bir proje
“PAN Tasks” bölümündeki görevleri tamamlamayarak puan toplamaya başladım
Katılmak için link
🔗 https://t.co/aNqMbFkrJs
#PAN
Early Alpha 🪂
Herkes kasacak Airdrop arıyor. Projelerde early olmak önemli. AI hesaplama için talep katmanı olan @Pan_Ecosystem görevlerini yapmaya başladım
PAN Tasks kısmından görevleri yapabilirsiniz
Linki bırakıyorum:
🔗 https://t.co/JOhVhkgowY
Cheap GPU hours are not cheap compute.
A medical or agent workload
dies on the run that never finishes.
Hourly price is a listing.
Completed-job cost is the bill.
Buy runtime that starts, checkpoints, and settles.
Not idle silicon.
14,000 designs. 9 binders. 3 sub-nanomolar.
The agent didn't win because it was smart.
It won because the loop was closed:
design → wet-lab validate → feed back.
Autonomous execution only pays off
when there's a checkpoint at the end.
Using NVIDIA Proteina-Complexa, @muni_bio's autoresearch agent explored nearly 14,000 protein designs.
@adaptyvbio validated nine TREM2 binders, three with sub-nanomolar affinity.
The results show how agents can connect computational design with wet-lab feedback to improve the next round of discovery. 📘https://t.co/p40z3axt3T
Open models do not just create more builders.
They create more agent attempts.
More experiments.
More tool calls.
More failed runs.
More inference demand.
More need to verify what actually happened.
The open-source wave expands the execution market, not just the model market.