1 Question, 1 Answer about
@cortensor
Q: How does Cortensor ensure that model execution happens in the right order across decentralized nodes?
A: Running AI models isn’t just about doing the math — it’s about doing it in the right sequence. Every transformer, every neural net, every forward pass has a precise flow of operations. If the order breaks, the output is garbage.
That’s why Cortensor builds and tracks a computation DAG (Directed Acyclic Graph) for every task. This graph maps the entire flow of tensor ops — from matrix multiplies to activations — and ensures each step is only triggered when its dependencies are complete.
The best part? It works across multiple nodes. Each node gets assigned a chunk of the graph. The protocol handles coordination and makes sure results from upstream nodes are passed down securely and verifiably.
Cortensor isn’t just running AI — it’s orchestrating it, step by step, on-chain.
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