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@Jia_Lilly01 0x6a471b1d14faf96347957ef4cf762e0965a27c26
for my Daughter's Birthday she wants a Cake on her Birthday and Go in the Mall watchings Movies playing in The Kidzoona
Hi Guys Just finished the Baranos AI whitepaper v2.0 and cleared the Educational Quest, including Protocol Architect.
1/
My biggest takeaway:
The hard part of AI onchain isn't putting a model on a blockchain.
It's making an AI answer something a smart contract can safely act on.
Here's what @BaranosAI is building. 👇
2/
The AI oracle problem
Today, AI decisions involving money often depend on:
→ private APIs
→ committees
→ token votes
→ trusted operators
But "the API said so" isn't evidence.
Baranos tackles this by making AI execution reproducible and verifiable.
3/
The core idea
Same model + same inputs + same execution rules = same result.
Before execution, Baranos commits:
• model + weights
• runtime/tokenizer
• prompt
• evidence root
• decoding + seed
• output schema
• execution policy
AI becomes a defined computation, not just an answer you have to trust.
4/
Optimistic verification
Baranos uses two modes:
🔹 Confirmation: AI runs offchain and the result + commitments go onchain.
🔹 Replay: disputed computation can be replayed onchain.
A challenger doesn't need to prove the entire AI system wrong. They challenge the specific bad step.
Commit → Challenge → Replay → Verify.
5/
Why Fogo?
The system needs high throughput, low cost and low latency.
Baranos is deployed on Fogo, targeting fast result and challenge resolution.
The roles are separate:
Baranos: verifies AI execution
Fogo: secures the canonical blockchain history
Validators aren't deciding what the AI should think.
6/
What exists vs. what still needs proof
✅ Deployed on Fogo
✅ Confirmation + Replay
✅ Deterministic execution specification
✅ Challenge mechanism
✅ Model/evidence/policy/job/result registries
Still to validate:
⏳ minute-scale resolution
⏳ actual costs
⏳ independent-run determinism
⏳ performance under load
I like that the whitepaper openly identifies risks instead of pretending AI verification solves everything.
7/
My Protocol Architect design: FairStay
I designed a verifiable booking-dispute system.
AI receives a frozen evidence bundle:
• listing + photo hashes
• timestamps
• messages
• refund policy
It outputs:
FULL_REFUND / PARTIAL / NONE
with a structured evidence-based rationale.
Before execution, everything is committed.
8/
The guest, host or platform can challenge a specific computational step.
If challenged, that step is replayed under the same rules.
If confirmed, or the challenge window expires, the escrow contract can release funds automatically.
The key principle:
Challenge the first incorrect step, not just the final answer.
9/
The Educational Quest made this principle very clear.
If an AI produces 25 when the agreed rule produces 23, a later calculation might be perfectly correct while using the wrong number.
That's why verifiable AI needs more than a final answer.
10/
The pipeline I'll remember:
AI Decision → Commitment → Replay → Verified
AI answers.
The rules and inputs are locked.
Disputed computation gets replayed.
The verified result becomes something another smart contract can safely depend on.
And Congrats I also get certificate from
@BaranosAI and thanks to @fogo also.
MegPrime Pay is now available on the App Store and Google Play.
App Store
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Google Play
https://t.co/MftVAc073A
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