AI inference distributed
AI inference is becoming distributed. Rollups are becoming execution layers. But who captures the value generated in between? We’re entering an efficiency era. In AI, optimization techniques (quantization, sparsity, distributed…
AI inference is becoming distributed. Rollups are becoming execution layers. But who captures the value generated in between?
We’re entering an efficiency era. In AI, optimization techniques (quantization, sparsity, distributed inference) bend the cost curve of compute. In Web3, rollups bend the scalability curve. But neither automatically captures economic value.
Every active rollup generates structural MEV — arbitrage, liquidations, cross-chain spreads. Even 2–5 bps on $200M daily volume implies $40K–$100K/day of potential protocol revenue. Most of this still leaks to private searchers.
Radius sits at this intersection.
Through Secure Block Building (SBB) and encrypted ordering (PVDE), it separates user flow from competitive bidding. Toxic MEV is suppressed, while “searcher alpha” becomes structured protocol revenue.
Now layer AI on top:
As AI agents increasingly execute trades, rebalance portfolios, manage liquidity, and coordinate across chains, transaction ordering becomes high-frequency economic infrastructure. Inference generates decisions. Ordering determines value capture.
If distributed AI drives 5–10× transaction velocity in the next cycle, the monetization layer compounds with it.
Throughput scales systems.
Inference scales intelligence.
But owning the ordering layer scales margins.
That’s the frontier.
#AI #Web3 #Ethereum #Layer2 #MEV #Inference #BlockchainEconomics
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