I went into this conversation thinking intelligent contracts were basically just smart contracts with AI added to them. But talking it through with Mochi made me realise that the bigger difference is how they can deal with real world information when things are not always clear or consistent.
The FlyGuard example was what I found most interesting. At first, flight delay insurance sounds pretty simple, but once you ask where the contract gets the flight information from and what happens when different sources disagree, it becomes a much bigger problem.
Seeing how GenVM and the AI validator jury could be used to handle that made the idea of intelligent contracts much easier for me to understand.
I also liked that the conversation eventually moved from how GenLayer works to what people could actually build with it. That was probably my biggest takeaway.
The interesting part is not just adding AI to contracts, but being able to build applications around real world situations that traditional smart contracts cannot easily handle.
Go ask the cat any questions yourself:
https://t.co/8JcEjPWiSH
@GenLayer
The world's largest asset manager just described machine-to-machine commerce:
Agents paying for compute on programmable rails, in stablecoins.
Konnex is building this for physical AI.
Robot labor priced in open markets, settled in stablecoins, proven on-chain.
FUD IS LIVE ON MAINNET.
Permissionless prediction markets for internet money.
Memecoins. Short-term markets. Real money.
Built on @solana launching on @clawpumptech 🫧
#1 Power Cell
⚡️ Just unboxed the #1 Power Cell fragment from @RaxFinance! The core is powered up and the energy levels are off the charts.
Can't wait to integrate this into my final NFT! 🚀
https://t.co/pbzpeMdTnF
#RaxFinance#NFT#Web3
My $VENTRA allocation: 228,960 $VENTRA
Every Arbitrum One transaction I already made counts toward it. Check what you are owed:
https://t.co/wsdNBE1SMh
@ventranxyz
We’re excited to share that 4D Labs has received investment from @yzilabs through @EASYResidency Season 2. ⚡️
We’re building the real-world embodied data layer for physical AI — turning real-world interaction into training-ready embodied data. 🦾
AI has learned to speak.
Now it needs to learn how to act.
A new chapter begins.