Every cycle there’s one infra layer that shifts the meta in the core stacks of the market. I think @AlloraNetwork might be that piece with its own thesis on AI oracle. It’s an intelligence oracle layer where thousands of competing models collaborate, forecast each other’s weaknesses, and self-improve. The result is a feed that predicts what comes next, based on: → Collective intelligence from 288K+ worker models → Forecasts of each model’s future accuracy under real conditions (volatility, timeframes...) → Predictive feeds that are both context-aware and time-aware In short, instead of just “What’s the ETH price now?” → Allora answers “What’s the ETH trajectory under low volatility, within 4 hours?” Backtests show BTC/ETH forecasts plugged into Runbot & Rivalz, hitting ~53% short-term directional accuracy and generating 24% monthly yields after fees. You can already see Allora powering full-loop DeFi strategies that evolve with the market: → On @milky_way_zone, ppl...
I’ve been spending time studying @AlloraNetwork, and I see it as the missing layer between $TAO and $LINK, the intelligence oracle that crypto didn’t have until now. Let me explain why this matters. – @opentensor gives decentralized compute and coordination for AI models. – @chainlink delivers secure, tamper-proof external data on-chain. But DeFi & RWA need more than just compute or raw data, they need intelligence that adapts to context, and proofs that it’s real. I’ve been seeking around but only to notice that @AlloraNetwork is exactly the only one brings that solution. Their 2 most important tech that separate Allora from the rest: → Context-aware inference → Models push raw data and even synthesize signals with awareness of market conditions, sentiment, and macro shifts. → Verifiable predictions → Every output can be validated transparently without exposing private data or model internals. That combination unlocks real, high-value use cases as I pitche bellow. –...
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