Fiks(❖,❖)

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Fiks(❖,❖)

Fiks(❖,❖)

@Fixa404

Building connections in Web3 || Jpeg lover irys-verify-0x3b533e-Fixa404

Web3.0 انضم Haziran 2024
580 يتبع596 المتابعون
Fiks(❖,❖) أُعيد تغريده
Fiks(❖,❖)
Fiks(❖,❖)@Fixa404·
DAY 49 art on SEISMIC Holding energy, Shaping the future. That’s the idea I had in mind with this, and it reminds me a lot of what @SeismicSys represents quiet, strength, but capable of real impact. @xealistt @NoxxW3 @snow_blis @mzain2292
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Fiks(❖,❖)@Fixa404

DAY48 art on SEISMIC In a world full of noise, @SeismicSys helps teams say the right thing, at the right moment. And that’s powerful. @xealistt @NoxxW3 @snow_blis @mzain2292

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Ser David
Ser David@serdavi7_·
𝗦𝗲𝗶𝘀𝗺𝗶𝗰 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 𝗙𝗮𝗰𝘁𝘀, 𝗗𝗮𝘆 11 According to the docs, Seismic is designed to support encryption natively within its execution environment. 𝙷𝚎𝚛𝚎'𝚜 𝚠𝚑𝚊𝚝 𝙸 𝚖𝚎𝚊𝚗... By supporting encryption natively, and withing it's execution env, developers don’t need to rely on external privacy tools or separate systems to make their applications confidential. "𝘌𝘯𝘤𝘳𝘺𝘱𝘵𝘪𝘯𝘨 𝘢𝘳𝘣𝘪𝘵𝘳𝘢𝘳𝘺 𝘴𝘮𝘢𝘳𝘵 𝘤𝘰𝘯𝘵𝘳𝘢𝘤𝘵𝘴?" This means you can take a normal Solidity contract and, with Seismic’s added syntax and features, you (as a Dev) can make its logic, state, and data private... all within the same VM. The contract still runs like any other, but sensitive values (balances, inputs, internal logic) are encrypted during execution and storage. Simply put, instead of stitching together multiple tools for privacy, developers can build a fully encrypted DeFi protocol directly from a single contract, with privacy handled at the protocol level. For more details, check out @SeismicSys docs. gMic CT! Special seismic greetings to @xplanettt , @NoxxW3 , and @lyronctk in particular 🌚
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Ser David@serdavi7_

𝗦𝗲𝗶𝘀𝗺𝗶𝗰 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 𝗙𝗮𝗰𝘁𝘀, 𝗗𝗮𝘆 10 According to the docs, Trusted Execution Environments (TEEs) is used by Seismic to securely run encrypted computations. 𝐁𝐮𝐭 𝐰𝐡𝐚𝐭'𝐬 𝐓𝐄𝐄? TEEs are more like a protected area in a processor where codes and data can be executed safely, and in isolation from the rest of the system. 𝐀𝐩𝐩𝐥𝐲𝐢𝐧𝐠 𝐭𝐡𝐢𝐬 𝐭𝐨 𝐒𝐞𝐢𝐬𝐦𝐢𝐜'𝐬 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞: In Seismic’s architecture, this allows encrypted smart contract logic to be processed inside the secure enclave in isolation, without exposing the underlying data to validators, nodes, or the public blockchain. Yes, the network can still verify that the computation was done correctly, and yes... sensitive inputs and outputs remain private. Simply put, TEEs are one of the core mechanisms that help Seismic achieve protocol level privacy, enabling confidential fintech applications and Defi to run securely on-chain. For more details, check out @SeismicSys docs. gMic CT!

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Mouse | ❤️‍🩹 🏕️
GMIC EVERYONE 🥰 @SeismicSys Even the strongest foundations need a little love Rocky the unbreakable mascot of seismic showing us that true strength includes being soft enough to bring flowers to his gf stable foundation zero red flags maximum vibes 🌹
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Fiks(❖,❖)
Fiks(❖,❖)@Fixa404·
Everyone is talking about AI. Everyone is building on-chain. @ritualnet is doing both but with a real use case. Imagine smart contracts that don’t just execute but think, adapt, and respond using AI models directly on-chain That’s the direction Ritual is heading @Jez_Cryptoz
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Fiks(❖,❖)@Fixa404

A lot of people are focused on AI tools, not enough people are thinking about AI trust. @ritualnet is building around that exact problem. And honestly, that’s where the real value might be long term. @Jez_Cryptoz @cryptooflashh @dunken9718

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Alola (∇, ∇) ♦️(real-time oracle)
OpenGradient Model Highlight: SUI/USDT Short-Term Spot Forecasting Model In the evolving intersection of AI and decentralized finance (DeFi), @OpenGradient continues to push boundaries with practical, on-chain intelligence. One of its latest highlights the SUI/USDT Short-Term Spot Forecasting Model offers a glimpse into how machine learning can be applied to real-time crypto trading decisions. The Core Idea: Predicting the Next Move At its foundation, the model focuses on short-horizon price forecasting for the SUI/Tether (USDT) trading pair. The goal is simple but powerful: Can an AI model learn short-term market behavior without overfitting noise? This question is central to modern crypto trading. Markets are highly volatile, and short-term price movements are often driven by micro patterns that are difficult for humans to detect but potentially learnable by models trained on high-frequency data. How the Model Work The forecasting model builds on OpenGradient’s broader spot forecasting framework, which uses structured market data and statistical learning techniques. 1. Data Input (OHLC Candles) The model consumes recent OHLC (Open, High, Low, Close) price data standard inputs in financial modeling. These are arranged as time-series sequences representing recent market behavior. 2. Feature Engineering Before training, the raw data undergoes: ‌• Log transformations •‌ Feature extraction • ‌Dimensionality reduction 3. Model Training The system uses: •‌ Lasso regression for feature selection • ‌Least-squares optimization for weight tuning Short-Term Forecasting Capabilities OpenGradient’s framework supports multiple short-term horizons, including: • ‌30-minute forecasts • ‌Multi-hour forecasts (e.g., 6-hour windows) These models output expected returns, not just price direction making them useful for: • ‌Trade execution strategies • ‌Risk management systems • ‌Automated AI agents Why This Matters 1. From Data to Action This model is not just analytical it’s actionable. It can be embedded into: • ‌Trading bots • ‌On-chain agents • ‌DeFi protocols 2. Enabling Autonomous AI in DeFi Short-term forecasting is a key building block for: • ‌Autonomous trading agents • ‌Adaptive liquidity strategies • ‌Yield optimization systems These agents can analyze → decide → execute, all without human intervention. 3. Moving Beyond Historical Analysis Traditional trading relies heavily on past performance. In contrast, forecasting models: ‌• Incorporate current market conditions • ‌Provide forward-looking signals • ‌Adapt dynamically to new data This aligns with the broader shift toward predictive, AI-driven finance. Limitations to Keep in Mind While promising, the model is not perfect: • ‌Crypto markets remain highly noisy and unpredictable • ‌Backtested performance does not guarantee future results • ‌Short-term signals can degrade quickly in volatile conditions OpenGradient itself emphasizes that these models should be used as components within larger systems, not standalone “magic predictors.” The Bigger Picture The SUI/USDT Short-Term Forecasting Model represents more than just a trading tool it’s part of a larger movement toward verifiable, decentralized AI infrastructure. By making models: • ‌Deployable on-chain • ‌Composable with other protocols • ‌Accessible via SDKs and APIs OpenGradient is turning AI from a black-box service into a programmable financial primitive. Final Thoughts The highlight of this model isn’t just its predictive capabilityit’s what it enables: • ‌Smarter trading systems • ‌Autonomous financial agents • ‌A new layer of intelligence in DeFi As AI continues to merge with blockchain infrastructure, models like this will likely become core building blocks of the next-generation financial stack where decisions are no longer manual, but learned, optimized, and executed in real time. Gai @josephweb3 @SheTalksCrypto @0xChainWiz @0x_Nate1
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Fiks(❖,❖)
Fiks(❖,❖)@Fixa404·
Everyone wants to use AI, but not everyone understands how it learns. @OpenGradient change that. When the process is transparent the wins, the errors, the iterations people don’t just consume tech, they grow with it. That’s the kind of future worth building.
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Fiks(❖,❖)@Fixa404

Big move for verifiable AI @OpenGradient teaming up with Cysic is exactly the kind of collaboration the space needs right now. Zero-knowledge proofs verifying model execution That’s how we start building real trust in AI systems, not just hype.

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cryptic Ream (❖,❖)
cryptic Ream (❖,❖)@Faizan626371·
Gmic @SeismicSys fam Seismic is building what web3 has been missing real on-chain privacy Not add-ons not workarounds Encryption built into the network itself → private smart contracts → confidential transactions → encrypted data by default Most blockchains are fully transparent Seismic flips that If web3 wants real-world adoption, privacy isn’t optional Seismic gets that @NoxxW3 @xealistt @heathcliff_eth @mzain2292 @k2sbhai
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cryptic Ream (❖,❖)@Faizan626371

Gmic @SeismicSys fam Another poker night is here ♠️ Make sure you get registered on time and don’t miss out It’s all about good vibes, smart plays and a bit of luck Let’s see who takes the win this time @NoxxW3 @xealistt @heathcliff_eth @mzain2292 @k2sbhai

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Fiks(❖,❖) أُعيد تغريده
OpenGradient (∇, ∇)
OpenGradient (∇, ∇)@OpenGradient·
🙌 OG COMMUNITY SPOTLIGHT We’re highlighting standout work from the OpenGradient community Developers, educator’s, artists and contributors are actively creating, shipping, and contributing across the network From dapps built on the model hub to original artwork and hands-on improvements through testing and feedback. Featuring: @santotheplug1_ @LolaSt1400 @trungkts29 @0xNormal_ @kingop0007 @Shahzaib0x @DioeconmeXBT @kant_lll @amathxbt @kurlyk27 @K_Gass @gemspecialist01 Appreciation to everyone contributing and pushing the network forward. 👏
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