Crypto ko “everything on-chain” bolna bahut pasand hai jaise usse har infrastructure problem automatically solve ho jati ho. Reality usse kaafi messy hai.
Aaj bhi most AI systems heavily off-chain compute pe depend karte hain because model training, inference, memory systems aur retrieval layers massive hardware resources consume karte hain. Agar har AI operation ko directly traditional blockchain execution environments ke andar force kiya jaye to scalability almost instantly break ho jayegi. Gas fees explode hongi. Latency badhegi. Throughput collapse karega.
Isi liye lately @OpenLedger mujhe interesting lag raha hai.
Ye pretend nahi karta ki GPUs magically blockchain consensus systems ke andar belong karte hain. Instead OpenLedger zyada focus karta dikhta hai important coordination layers ko on-chain lane pe — attribution, permissions, inference accounting, Datanets,
model contribution tracking aur agent deployment infrastructure.
Big distinction there.
Yaha chain compute replace karne ki jagah AI activity ke niche economic coordination layer jaisa behave karti dikhti hai.
Aur honestly, long term me ye approach mujhe kaafi zyada realistic lagta hai compared to most “fully on-chain AI” narratives jo abhi crypto me circulate kar rahe hain.
Kyuki once autonomous agents continuously networks ke across interact karna start karenge, hardest problem intelligence generate karna nahi hoga.
Us intelligence ko coordinate karna hoga.
@OpenLedger $OPEN #OpenLedger #AIBlockchain