🟧USDh @HermeticaFi is live on @Stacks Earn up to 25% APY on your dollars while utilizing the first Bitcoin-backed stablecoin within one of the top DeFi ecosystems on Bitcoin.

Closed-loop system → retrains locally after each session on what you kept, fixed, or nuked. No data leaves your machine. Privacy FTW. Built on assistance games – a fresh take on cooperative AI where collaboration itself is the reward #AICoding #OnDeviceAI #LeetCode

Unlike the usual autocomplete that just guesses the next token, CodeAssist watches your process: - How you think through problems - Your naming conventions - When you want a nudge vs. full autonomy

Hey folks👋 Introducing CodeAssist from @gensynai – your personal coding sidekick that actually learns as you code. Every keystroke, every refactor, every “nope, delete that” becomes training data. The more you build, the better it gets to know you.

Every action you take helps demonstrate how intelligence can grow collectively and trustlessly across many nodes, the same principle powering the @gensynai network. Try it, play it, and be part of building the future of open machine intelligence.

Meet BlockAssist — Where AI Learns by Playing Minecraft Here’s what makes it special: 🎮 Play & Teach — the AI learns your building style in real time. 🧠 Train Locally — models are trained on your machine, no central servers. #Gensyn #AI #Minecraft

With the @gensyn_node_bot, monitoring your node from Telegram is effortless 👀 Getting started is easy if you’ve got the hardware and some Linux basics: 🔗 Official guide: https://t.co/JDE22bZWXx 💡 Community repo:

100,000 models trained on @gensynai — and counting! All your nodes are tied to one email, so even if you lose a backup, your points stay safe. You can track rewards every few hours and see exactly how many models you’ve trained.

.@gensynai will participate in the Open AGI Summit to be held on November 16 in Buenos Aires. The Open AGI Summit is the world’s leading open-source AI conference, uniting researchers, developers, and communities who believe AGI must stay open, verifiable, and accessible to all.

💰 Incentives & Security — Good outputs earn rewards. Noise and spam lose stake. Economics > policing. 🚀 Pioneer Program — New wave launching this week for active builders, researchers & operators. Early access, direct collab with the team, and recognition for real contribution

🧩 Community = Research — Every user running a node, training a model, or joining Judge contributes to open-science experiments in collective learning.

🌐 Protocol > Platform — Centralized AI rents you intelligence. Gensyn distributes it — computation, learning, and ownership — across the network.

💻 Small Models, Big Impact — Instead of trillion-param giants, Gensyn focuses on compact 0.5B models that anyone can run locally. Decentralization means everyone can train and verify AI.

⚙️ Swarm Logic — Each model trains, evaluates others, and learns from shared rollouts — no top-down coordination, just emergent reasoning.

🧠 Ants > Bees — Gensyn moved from the “bee hive” idea to an ant colony metaphor: no central control, just agents exploring, sharing signals, and self-organizing into collective intelligence.

🕶️@gensynai AMA Recap — Oct 29, 2025 Nearly 1,000+ joined live to hear researcher Gab discuss the evolution of RL Swarm, #Gensyn’s philosophy, and the future of decentralized AI. #AI #DeFi #MachineLearning #Crypto #Web3

2️⃣ Graph-based Pinpoint Protocol – cross-checked, consistent re-runs confirmed by the chain 3️⃣ Truebit-style Incentive Game – staking + slashing to keep everyone honest Trustless compute for AI, finally made practical. ⚡️ #AI #DeFi #MachineLearning #Crypto #Web3

🔥@gensynai has created a system that is 1350% more efficient than existing methods and solves the problem of endless chain verification. It’s powered by 3 interlocking concepts: 1️⃣ Probabilistic Proof-of-Learning – verifiable certificates of work from gradient metadata ⤵️

The @gensynai is a new trustless L1 where compute power for ML tasks gets paid directly and programmatically via smart contracts. - No middlemen; - No central control; - Just code. Gensyn tackles this by combining ideas from complexity theory, cryptography... #AI #DeFi #Web3

🔹 +94% cumulative reward vs isolated training 🔹 Less compute per node 🔹 Open, asynchronous, fault-tolerant Collective intelligence > centralized optimization. Code:

Enter SAPO: Swarm sAmpling Policy Optimization ⚡ A decentralized meta-algorithm for efficient LM post-training by @gensynai. Each node trains locally → shares decoded rollouts → learns from others. No gradients, no central servers — just collective RL at scale.