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OMO NAIJA, automation Dev. Tweeting smarter with a bit of code ⚡, #SocialTech. Bullish on @aztecnetwork
Joined February 2016
GM CT, The way @_technotainment is bringing Hollywood on-chain with community raises is a novel approach, which could bypass traditional gatekeepers and foster direct fan funding.
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GM ⛅️ The best audiences don’t just watch, they co-create. Every single action has value here. @_technotainment
GM ⛅️ The best audiences don’t just watch, they co-create. Every single action has value here. @_technotainment
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For the creators. For the viewers. For the culture. 🦋 @_technotainment
The industry needs something new. The old model is broken, and ready for reinventing. That's why we're building Technotainment. For the creators. For the viewers. For the culture. 🦋
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Every step you take in our airdrop program brings you closer to a share of the $1M rewards pool! join @_technotainment now
Don’t forget to stack your Techno Points 🎬 Every step you take in our airdrop program brings you closer to a share of the $1M rewards pool! Engage, earn, repeat. Join us here: https://t.co/ARUhqx4VgE
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What's at the core of @ChimpxAI? 1. MOJO AI Agent Your intelligent DeFi co-pilot. Execute complex, multi-step Defi operations with simple language commands — all within one unified superapp. 2. Effortless Token Swaps Cross-chain and same-chain swaps without gas fees. Liquidity
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Nobody talks about the computational overhead of converting ONNX models to proof circuits, but it's crucial. JSTprove tackling ONNX in → Proof out shows promise, but the R1CS constraint generation from complex ONNX ops can be a bottleneck. Why? Because the resulting circuits
ONNX in → Proof out. That’s the experience JSTprove delivers. Paired with DSperse slicing, zkML finally escapes the lab.
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Why are zkML projects still trying to prove an entire model at once? @inference_labs is rethinking this. Building circuits for entire models becomes unwieldy because of the computational overhead. Their modular approach to proofs makes decentralized AI practical for enterprise
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Technotainment was born from a shared vision, to bring Hollywood on-chain. Mission is simple yet bold, to build a world where creators own their work, audiences shape every moment, and brands engage on a transparent, decentralized stage. @_technotainment
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ChimpX AI (@ChimpxAI) is an all-in-one decentralized finance (DeFi) platform that allows users to control 100% of their DeFi activities through a single interface using an AI agent. With ChimpX AI, users can perform actions such as swapping tokens, bridging assets, trading,
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wake up - gm - read about verifiable autonomy, how @ChimpxAI is building on BNB - send 10 tweets about @inference_labs & @ChimpxAI #MissionStarbound repeat.
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Welcome to the last month of 2025 CT @inference_labs's approach to decentralized AI via their Inference Network is interesting. The way they reward correct proofs & slash dishonesty using economic incentives and cryptography moves beyond simple trust assumptions. This matters
Gm CT @inference_labs Starboard campaign highlights a key challenge: verifiable AI in Web3. Bridging decentralized AI with enterprise needs requires trust, why traditional AI lacks because it’s opaque. Inference Labs focuses on "proof," enabling secure commercial applications.
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zkML's bottleneck is proving the entire model. The circuit-witness-proof process becomes computationally intensive. @inference_labs tackles this by slicing and distributing with DSperse, then compiling and proving each slice with JSTprove. @inference_labs's focus on
ONNX in → Proof out. That’s the experience JSTprove delivers. Paired with DSperse slicing, zkML finally escapes the lab.
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Nobody talks about @ChimpxAI's early DeFi Dawn stats on Katana, but it's crucial because those 17,744 transactions show real on-chain activity, not just hype. Compare that to meme coins with inflated volume via wash trading. This active user base of 2,421 indicates stickiness.
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GM ⛅️ The best audiences don’t just watch, they co-create. Every single action has value here. @_technotainment
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zkML's challenge: proving entire models at once creates massive circuits. This limits applications because of compute costs. How @inference_labs tackles this with slicing and distribution: Why aren't more decentralized AI projects focusing on verifiable inference like
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X vs Y: Why most miss the real difference. @ChimpxAI launching on BSC, Solana + 8 chains contrasts with single-chain DEXs. Their layer-2 tech for "lightning-fast transactions" matters because it tackles cross-chain gas fees, a pain point others ignore. Tradeoff? L2 adds
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AI auditability is crucial in high-stakes sectors like finance. Because regulatory compliance demands proof of model integrity. What @inference_labs enterprise focus teaches us about decentralized AI: Enterprises need to know which model acted, what it computed, and if the
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