Sherin Sebastian’s Post

🌊 In today’s #TokenEngineeringReads the spotlight is on Ocean Protocol’s #predictoor and Trent McConaghy’s "Data Value-Creation Loop". Ever wondered how people can make money in the open #dataeconomy? Find the answers in the article available at the link below 👇

How did Ocean Protocol's Predictoor achieve $400M+ monthly staking volume in just 6 months? Find out in today’s #TokenEngineeringReads ft. its design & impact, plus Web3 Sustainability Loop updates. READ MORE: https://buff.ly/4aln4An FYI: Major EthCC Announcement! We’re giving away 5 free tickets! Simply refer 3 friends to subscribe to #TokenEngineeringReads noting your email as the referral. Entries close May 24 at 12:00 UTC. Link: https://buff.ly/3QFmrdR 1/ In 2020, Trent McConaghy developed a framework called the "Web3 Sustainability Loop". Popular in the TE community, this loop tackles crypto’s hardest challenge: achieving sustainable value capture in non-extractive, open-source, and permissionless ecosystems. 2/ From the Web3 Sustainability Loop, the "Data Value-Creation Loop" is fleshed out as a new sub-system. It addresses the question, "How do people make money in the open data economy?" 3/ How? By following the loop's steps: 1) Create value from data, 2) Make money from it, and 3) Reinvest to fuel growth. 4/ Predictoor's Data Value-Creation Loop ensures data products generate revenue. Data fuels building models, making predictions, and creating revenues. Profits reinvest in data, sustaining the loop. $OCEAN tokens facilitate value capture. 5/ The speed and value of iterating through the Data Value-Creation Loop are crucial. Slow loops run out of funds; fast loops quickly deliver value & grow. Ocean Protocol analyzed verticals based on speed & revenue, focusing on DeFi for its fast iteration & large $ opportunity. 6/ The Data Value-Creation Loop maps the Data Supply Chain: raw data is refined into models and predictions, leading to profit. Typically, the last mile makes the most profit. Predictions are the most valuable data. 7/ In late 2023, Ocean launched Predictoor, its first end-user product, providing price predictions for the top 10 crypto tokens. It aggregates and sells predictions to traders, rewarding accuracy in price predictions. 8/ Ocean targets traders and data scientists using Python, and started with a comparably simple simple product suite. Today, Predictoor combines a Python code interface, a web app, AI/ML prediction bots, a simulator, CLI, and analytics. 9/ Ocean overcame the initial empty network issue by kick-starting transactions with own AI/ML prediction bots. Today, Predictoor Data Farming boosts predictoor earnings based on accuracy and stake. This led to >$400M in monthly staking volume in the early months! 10/ Predictoor succeeded in tackling crypto's toughest challenges by gaining user traction, creating a new value loop, and ensuring protocol success through end-user engagement. More resources are provided in the edition! This newsletter is made possible thanks to funding from Carbon DeFi by Bancor, Tokenomia.pro, and Optimism Foundation's RetroPGF! Subscribe to #TokenEngineeringReads for more: https://buff.ly/3QFmrdR #tokenengineering #ai #crypto

#Web3 native innovators Axelar Foundation and Metrika led production of an insightful MUST READ report on the importance of Institutional Interoperability in the future of #blockchain. 💡 The paper acts as a road map for financial institutions developing tokenized-asset opportunities and facing a complex array of public and private blockchains, alongside client and regulatory requirements. Georgios Vlachos, Director of Axelar Foundation and Co-Founder of Axelar Network said “Tokenized assets are by nature interoperable, bridging assets recorded on off-chain ledgers with on-chain representations. The question isn’t, how do we facilitate one such connection – it’s how do we facilitate potentially thousands of connections across on-chain and off-chain ledgers, in a way that’s secure, scalable and open." Regarding multichain interoperability, Anand Rengarajan, Global Head of Sales & Head of Securities Services APAC, Corporate Bank, Deutsche Bank, commented "Multichain asset interoperability and servicing will likely become a necessity for asset servicers as their clients adopt different chains. It will be essential that asset servicers know how to address and service interoperability with scale, while ensuring digital asset safety to enable sustainable growth that multiple chains can amplify." This excellent paper was authored by blockchain analyst Emily Parker, based on a framework laid out by the Monetary Authority of Singapore (MAS)’s Project Guardian in 2023. Key contributors to the paper include Biser Dimitrov (Global Head of DLT Center of Excellence, Citi), Altin Hoxha (Global Head of Digital Assets Platform Engineering, Citi), Caroline Lin (Digital Assets Associates, Citi), Sorcha Sullivan-Williams (Senior VP, Digital Assets Product Manager, Citi), Boon-Hiong Chan (Industry Applied Innovation Lead Head, APAC Market & Technology Advocacy, Deutsche Bank), Colin DeLarso (Crypto Product Partnerships & Commercialization Lead, Mastercard), Oskar Duris (Global Head of Blockchain Product Development, Mastercard), Rashi Goyal (Director, Product Development, Blockchain & Digital Assets, Mastercard), Soumyajit Mitra (Director, Product Management - Technical, Blockchain & Digital Assets, Mastercard), Alvin Chia (Senior VP, Head of Digital Assets Innovation, APAC, Northern Trust), Sean Mullins (Senior VP, Head of Product Execution, Digital Assets & Financial Markets, Northern Trust), Bhaji Illuminati (CMO of Centrifuge), Marianna Angelou, PhD (Director, Blockchain Analytics, Metrika), and Alexandros (Alex) Nathan (Co-Founder, VP Analytics, Metrika). 👏🏽 #AltBanking The leading aggregator, bringing the best actionable news, information and opportunities in this rapidly evolving ecosystem right to you. Follow us to stay up-to-date! #fintech #finance #tokenization #interoperability #DeFi #DLT #digitalassets #banking #innovation https://lnkd.in/gSnfXcUz

CryptoSlam Inc, backed by Mark Cuban and Reid Hoffman, is partnering with Animoca Brands to launch SlamNet, a web3 data economy aiming to fuel blockchain-based uses for intelligence, commercial and financial applications. “Data shouldn’t be centralized or controlled by any one entity or handful of entities,” Randy Wasinger, founder and CEO of CryptoSlam said. “It should belong to the industry itself and should be governed as such.” SlamNet will provide a robust source for web3 data, consolidating fragmented information under one convenient umbrella. Learn more about how SlamNet will power the flow of enriched, trusted web3 data in our latest article, now live on Decential. https://lnkd.in/eM_fuxti

Injective (INJ)integrates with The Graph to offer developers enhanced access to on-chain data, fostering the creation of sophisticated dApps. (Read More) https://lnkd.in/gEGq3m7R

🚄 Equilibrium Labs Infra Bulletin #23 comes with a fresh format ⚡️ It covers topics including verifiable inference, Sui Foundation's new consensus mechanism, NEAR Protocol's chain signatures, and more... Let's dive in! 🤿 Highlight of the week 🔍 Modulus recently announced that they'd managed to prove the inference of the GPT2-XL model (LLM with 1.5bn parameter) and verify it on Ethereum. This is the first verifiable inference for a model of this size - a significant achievement! A key part of the success was using a custom prover which yields much better results, rather than trying to prove the model in Risc0 as previous attempts have done. While Modulus proved that it's feasible to do verifiable inference for a model of this size, the performance (cost and time) still left a lot of room for optimisation (took 200+ hours start to finish with an overhead of more than 1m x compared to just simple inference). More specialized provers are likely the path forward. Why does this matter in the first place? Verifiable AI inference gives a (cryptographic) guarantee that a specific model was used for inference. This has implications for both real-world use cases (industries such as medical, legal, educational...), and crypto-specific ones (e.g. smart defi with adaptive risk management models). Research, Articles & Other Things of Interest 💡 🤓 Mysticeti - Sui Foundation's new DAG-based consensus with lower latency 📚 Overview of current state of Anoma and how it could interact with Ethereum 📚 NEAR Protocol chain signatures, which allow Near accounts (including smart contracts) to sign transactions on other chains. 🎧 Debate on cryptographic (ZKP) vs cryptoeconomic security 🎧 Whiteboard sessions about relevant (and newer) blockchain concepts, such as Blobstream, Slinky etc. News From Our Partners 🔥 ⛴️ Gevulot launched its devnet, allowing 16,000+ whitelisted users to start deploying arbitrary provers & verifiers and run workloads to generate & verify proofs. A big step forward for decentralized proving! 🚀 Membrane Finance launches EUROe Ramp - a simple API that enables seamless connectivity to banking rails. Personal Recommendations From Our Team 🤌 📚 The Dispossessed - Ursula K. Le Guin 🎧 Snarky Puppy Keyboardist Hears Dua Lipa For The First Time 💡 Smart Words From Smart People Link to newsletter in the comments - thanks for reading! 🙏

Prediction analytics can be uselful to determine a probable future outcome. Polymarket is a decentralized prediction market platform where users can bet on the outcomes of future events. It operates on blockchain technology, specifically Ethereum, to provide a transparent and secure environment for trading on various topics, such as politics, sports, finance, and more. ### Key Features of Polymarket: 1. **Decentralization**: Polymarket is built on blockchain, which means it is not controlled by any single entity. This decentralization ensures greater transparency and security. 2. **Trading Outcomes**: Users can buy and sell shares in the outcomes of events. The price of these shares reflects the probability of the event happening as perceived by the market participants. 3. **Smart Contracts**: The platform uses smart contracts to automate the settlement of bets and ensure that payouts are made accurately and promptly once the event outcome is determined. 4. **Variety of Markets**: Polymarket offers a wide range of topics for trading, including current events, scientific discoveries, and more, allowing users to speculate on almost anything. 5. **Market Resolution**: Polymarket employs oracles, which are trusted data sources, to verify the outcome of events. These oracles provide the necessary data to settle the markets and determine the winners. 6. **User-Driven**: Anyone can create a market on Polymarket, making it a highly versatile platform for crowd-sourced predictions. ### How Polymarket Works: 1. **Creating a Market**: Users can propose a new market by defining the event and possible outcomes. Once the market is created, it becomes available for trading. 2. **Trading Shares**: Participants buy shares in the outcome they believe will occur. The price of a share fluctuates based on supply and demand, representing the collective belief in the likelihood of the event. 3. **Event Resolution**: After the event occurs, Polymarket's oracle verifies the result. The smart contract then automatically settles the market, distributing payouts to the holders of the correct outcome shares. 4. **Earnings**: Users profit by buying shares at lower prices and selling them at higher prices as the perceived probability of the outcome changes, or by holding shares in the correct outcome until the market is resolved. Polymarket provides a way for people to speculate on future events, leveraging the wisdom of the crowd to predict outcomes while ensuring transparency and security through blockchain technology. https://polymarket.com Take Dominion #Predictions #bitcoin #politics #biden #CEO #trading #hedgefund #Trump2024

Definitely a must read for Asset Servicing enthusiasts who are looking at futuristic trends.

By Brad Moynes; Lead Technical Writer GoAi News. Unlock the full potential of crypto trading by combining team collaboration with cutting-edge AI algorithms optimized for short-term volatility. This approach maximizes profits, minimizes risks, and delivers a competitive edge in the high-speed world of cryptocurrency markets. 1. Harness AI for Lightning-Fast Market Execution The power of AI-generated algorithms lies in their ability to process and analyze massive amounts of market data in real-time. These algorithms use advanced machine learning models to scan historical data, spot emerging trends, and react to short-term price movements within microseconds—well beyond human capabilities. By deploying AI to monitor the market continuously, your team gains the advantage of executing trades at the exact right moment, capitalizing on rapid price swings with precision and speed. 2. Algorithmic Optimization for Short-Term Volatility The crypto market is highly volatile, offering frequent opportunities to capture profits from sudden price spikes or dips. AI-based systems are designed to thrive in this environment by using predictive analytics, pattern recognition, and high-frequency trading (HFT) techniques to identify and execute on profitable trades in fractions of a second. These algorithms are constantly learning and adapting, refining their strategies based on market shifts and emerging data, resulting in smarter, faster, and more accurate trades over time. 3. Risk Mitigation Through Automated Intelligence One of the primary benefits of algorithmic trading is removing human error and emotion from the equation. Fear and greed are two of the biggest risks in short-term trading, often leading to premature exits or mistimed entries. AI algorithms strictly follow preset risk controls, ensuring disciplined, emotion-free trading. These systems can apply advanced risk management techniques such as stop-loss orders, dynamic position sizing, and portfolio rebalancing—all in real time, ensuring your team stays on track, even during volatile market conditions. 4. Maximized Profit Potential with High-Frequency Trading By focusing on short-term price fluctuations, your AI-driven algorithm can execute hundreds, even thousands, of trades daily. This high-frequency trading approach allows your team to accumulate incremental gains rapidly, which compound over time for substantial profit. With AI optimizing trade execution—entering and exiting positions at precisely calculated moments—your team can consistently outperform slower, manual traders in the crypto market. Elevate Your Trading Strategy With the combination of AI-driven algorithms and team collaboration, your crypto trading approach becomes an unstoppable force. Leverage short-term volatility for explosive gains, manage risk with machine precision, and take your trading game to the next level.

The integration of bots in Distributed Ledger Technologies (DLTs) fostersefficiency and automation. However, their use is also associated with predatorytrading and market manipulation, and can pose threats to system integrity. Itis therefore essential to understand the extent of bot deployment in DLTs;despite this, current detection systems are predominantly rule-based and lackflexibility. In this study, we present a novel approach that utilizes machinelearning for the detection of financial bots on the Ethereum platform. First,we systematize existing scientific literature and collect anecdotal evidence toestablish a taxonomy for financial bots, comprising 7 categories and 24subcategories. Next, we create a ground-truth dataset consisting of 133 humanand 137 bot addresses. Third, we employ both unsupervised and supervisedmachine learning algorithms to detect bots deployed on Ethereum. Thehighest-performing clustering algorithm is a Gaussian Mixture Model with anaverage cluster purity of 82.6%, while the highest-performing model for binaryclassification is a Random Forest with an accuracy of 83%. Our machinelearning-based detection mechanism contributes to understanding the Ethereumecosystem dynamics by providing additional insights into the current botlandscape. #DLT #FinancialBots #MachineLearning #Ethereum #MarketManipulation