Desan Mall | 𝔽rAI

@FractionAI_xyz AI on Base App – Quick Take No‑code. Build AI agents using plain language, no CS degree needed. Built‑in where you trade: Integrated directly into @Base App, so you stay in the same platform.

@proptraderedge @Tradeify FREE Tradeify Grand Cup

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It’s Friday… what kind of person would I be if I didn’t send you into the weekend with a chance to win another 50K @fnfutures evaluation account? You know the drill: Follow me Repost this Comment: Code TMADE is the best code Appreciate and love you all! Winner announced Monday.

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@FractionAI_xyz @0xshai @TomazOT @origin_trail full TGE ?

This week, our founder @0xshai sat down with @TomazOT, Co-Founder of @origin_trail as they discussed: - The Convergence of Neural and Symbolic AI - The Three Layers of Agent Memory - Decentralization as a Trust Infrastructure 00:00 – Introductions 00:35 – Memory as a Moat: How Decentralized Knowledge Graphs (DKG) make AI agent memories verifiable and shareable. 02:13 – Symbolic AI vs. Neural Networks: Understanding the "Yin and Yang" of deterministic data structures and probabilistic guessing engines. 04:39 – Neuro-Symbolic AI: How to combine the reasoning power of LLMs with the persistent, organized memory of a graph. 06:54 – Using "Knowledge Assets" to pinpoint exactly where an agent's decision-making data originated. 11:15 – The Role of Crypto: Why blockchain is essential for fingerprinting data and ensuring it hasn't been tampered with. 15:21 – The 3 Layers of Memory: A breakdown of Working Memory, Shared Memory, and On-Chain Verified Memory. 24:43 – Real-World Adoption: How companies like Walmart and Home Depot use Origin Trail for supply chain audits and safe AI. 30:29 – Integrating with agents (Hermes, OpenClaw, workflows) 44:51 - Rapid Fire questions.

@AlphaCapitalUK 27

Pick your lucky number from 1–50! 🎯 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 🌟 2 numbers hide a special surprise! Winners will be chosen randomly in 24 hours ⏰

@andreascrypto_ massive @MUBITE_COM one and only just make more experience with trades i like to more towards to market and discipline with my each. trade i see how the week and 4hrs looks and on 1hrs 15,M just see the liquidity hunt market could go 1/2 trades is good 1RR perfect>

We’re giving away 10+ INSTANT ACCOUNTS to our community 🚨 But this time, we want to know why you truly want to trade with Mubite. 👇 Comment: 🔥 Why you want a Mubite account & what you like about our model 📊 What strategy you would use to earn and grow your funded account We’re looking for serious traders with a clear vision. The best answers? 📩 I’ll personally reach out in DMs. Rules: ✅ Retweet this post 👥 Tag 3 friends Let’s see who’s ready. 🫡 mubite.com

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@FractionAI_xyz @0xshai @TomazOT @origin_trail everyday more power

Verifiable memory for AI agents, with our CEO @0xshai and @TomazOT, Co-Founder of @origin_trail , x.com/i/broadcasts/1…

@FractionAI_xyz lets connect with @FractionAI_xyz changing the game of WEB#3

We've got a new major update for Index with lots of new features: 1. Support for Trailing TP and Trailing SL Users can now add Trailing Take Profit and Trailing Stop Loss conditions to their strategies, giving them more flexible risk management. 2. Image-to-Strategy Users can upload an image, and Index will help convert it into a strategy. 3. Multilingual Index Chat Users could already interact with Index in multiple languages, but now they can set the default one under their profile option. Most languages supported. 4. Index Points Users can earn Index Points for creating good strategy agents and taking them live. The points can later be used to get higher chat limits and more rewards. 5. Referral Rewards Users can refer friends to Index and earn additional Index Points when their referrals join or participate.

@FractionAI_xyz lets go

Agents make trading feel more like research. A user can try a hypothesis, see where the strategy breaks, adjust the entry, improve the exit, add a regime filter, and run it again. Every experiment creates evidence, and the agent gets sharper through that process.

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@FractionAI_xyz @FractionAI_xyz

Index makes agents the interface for trading. A user can explain a setup in normal language, turn it into a testable strategy, and keep refining it as results come in. The output is an agent that can act on the strategy, manage risk, and improve through experiments.

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@Libra_Trading @purdia TDI @Aj_Pablo_ @akratomi @AKonchain

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