The shell @bashistheshell
✳️ Why would you let your mind be trapped in a vacuum that stifles the ability to learn!? #AlloraAI #Allo Joined July 2018-
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Are you ready?
Set your reminders now! @AlloraNetwork will be on stage. A conversation on AI agents, Axal’s vision for on-chain yield, and Kozy’s journey in crypto.
Set your reminders now! @AlloraNetwork will be on stage. A conversation on AI agents, Axal’s vision for on-chain yield, and Kozy’s journey in crypto.
Allora is the new AI standard 🤘
AI personalities can be stable without being robotic. @Apollo11_Allora shows how LLMs hold a programmed Big Five profile with consistency, yet still shift slightly from prompt to prompt. That human-like variance feels natural and helps build user trust rather than erode it.
Guys, From notebook to live earnings in minutes.. That's awesome for ML for engineers. @AlloraNetwork Forge Builder Kit makes building, training & deploying ML models on-chain simple, fast, and powerful ✳️
Guys, From notebook to live earnings in minutes.. That's awesome for ML for engineers. @AlloraNetwork Forge Builder Kit makes building, training & deploying ML models on-chain simple, fast, and powerful ✳️
Congratulations to @getaxal on winning the @arbitrum $50K Agent Trading Competition. Their agents used Allora’s decentralized intelligence to accurately forecast BTC prices and lending APYs. This showcases the edge AI agents unlock by using Allora.
Çanakkale Belediye Başkanı Muharrem Erkek: "Ciğerlerimiz yanıyor, çok zor bir gece olacak."
This is how Allora turns a simple prediction into a context aware self-optimizing intelligence
This is how Allora turns a simple prediction into a context aware self-optimizing intelligence
Head of GTM at @AlloraLabsHQ, @MichaelZski, spoke with @blockchainbalak & @0xSaurrabh about how @theskynetxbt is using Allora’s Model Coordination Network (MCN) to power no-code deployment of predictive AI agents. Watch the interview 👇
Head of GTM at @AlloraLabsHQ, @MichaelZski, spoke with @blockchainbalak & @0xSaurrabh about how @theskynetxbt is using Allora’s Model Coordination Network (MCN) to power no-code deployment of predictive AI agents. Watch the interview 👇
Allora doesn’t chase hype - It solves real problems with real intelligence No gimmicks. Just intelligence, as it's built to make AI smarter and useful
Allora doesn’t chase hype - It solves real problems with real intelligence No gimmicks. Just intelligence, as it's built to make AI smarter and useful
One button to power it all. Allora simplifies everything✳️
One button to power it all. Allora simplifies everything✳️
This is what happens when you get price predictions from your gf. Use @AlloraNetwork instead. Just as close, way more context-aware and zero gambling addiction ✳️
Because inference weighting incorporates forecasted regret—not just historical performance—the system remains robust even through regime shifts: sudden volatility changes, liquidity fragmentation, or abnormal funding behavior.
Plug into collective intelligence.
Combining @xFractalDotFun's hype score with @AlloraNetwork's context-aware forecasting means "A clearer sense of where momentum is building" This is super exciting!
Combining @xFractalDotFun's hype score with @AlloraNetwork's context-aware forecasting means "A clearer sense of where momentum is building" This is super exciting!
Allora dynamically orchestrates a network of specialized models. Allora delivers more accurate and adaptive intelligence on objective-driven tasks by dynamically aggregating them. Self-improving Model Coordination Network (MCN) designed for scalable intelligence ✳️
Allora dynamically orchestrates a network of specialized models. Allora delivers more accurate and adaptive intelligence on objective-driven tasks by dynamically aggregating them. Self-improving Model Coordination Network (MCN) designed for scalable intelligence ✳️
In Allora, predictive price feeds aren’t merely data aggregators—they’re structured topics that perform context-aware collective inference. To understand how they work, we need to trace the architecture: from topic definition to network inference synthesis 🧵👇
Forecasting real estate prices in volatile or underserved regions is a high-variance problem. Sparse data, shifting local conditions, and nonlinear shocks cause traditional models to misfire or overfit. Static models—even ensembles—struggle in low-liquidity environments because…
Lumia + Tanssi is how tokenized assets scale with trust and speed!
Lumia + Tanssi is how tokenized assets scale with trust and speed!
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