Welcome to Web3 Wednesdays on the #Crypto Daily Briefing 🚀 On the inaugural episode, @elaineyyly will host @DotNever, CEO of @SingularityDAO, a portfolio manager platform that puts together the power of #AI & DeFi. ⏰ LIVE at 12 PM ET Join us on YT 👇 rvtv.io/3pDnrVN

Happy Independence Day! Do androids dream of AIndependence? #IndependenceDay #July4th #AI

Tempus Fugit 1/1 standalone auction at @phillipsauction is currently live until June 5th 🔥 To bid on the artwork you just need to register at phillips.com/go/tempusfugit. Below a thread with more info about this release 🧵

Introducing SingularityDAO's Adaptive Multi-Strategy Agents In this tweet, we will explore @SingularityDAO's innovative Adaptive Multi-Strategy Agents (AMSAs), an advanced version of market-making agents. We'll delve into their functionality, discussing how they operate and their ability to detect specific market phases. Furthermore, we will explore the potential applications of these AMSAs in #DynaSets, unveiling the exciting possibilities they offer for optimizing trading strategies. Market makers earn alpha from the bid-ask spread by buying at the bid price and selling at the ask price. Market-making agents can buy and sell simultaneously using multiple orders and maintain different limit orders on the same market at different price levels using different spreads. In contrast, AMSAs are capable of performing experiential learning, relying on a swarm of subordinate agents executed in a virtual environment to determine optimal strategies for real trading. Additionally, the agents are equipped with the capacity to predict price movements based on e.g. social media data, which increases their financial performance. The predictive tools used for market making and the need to adjust them are similar to how DynaSets need to be adjusted based on new market dynamics. The architecture of SingularityDAO's market-making system incorporates a controller that manages two armies of single-strategy agents—one operating in the virtual environment and the other actively trading on exchanges. Before any agents engage in real-market transactions, the controller selects the most profitable ones from the virtual environment, ensuring that the bots handling real money generate positive returns. This controller also fine-tunes the agent selection policy, fund distribution, and time-based analysis of market data to continually improve efficiency. Other ways to improve the efficiency of agents include using hanging orders, predicting long and short-term market trends, and employing nested adaptive multi-strategy agents. Market volatility favors adaptive multi-strategy agents, and a strategy evolution period can help identify market phases and patterns without using the bots. In a recent paper*, the SingularityDAO team demonstrated the profitability of AMSAs relying on market price predictions. With access to predictions, these agents achieved a return on investment (ROI) of up to 25% in just two months, outperforming the same family of strategies executed without such predictive capabilities. When it comes to executing trades, centralized exchanges (CEXs) offer the best environment for these trading bots. With low trading fees and immediate trade execution, CEXs provide a favorable setting. On the other hand, decentralized exchanges present obstacles such as gas fees, price impact, slippage, and transaction speed, making the trading process more complex. While certain blockchain networks like Binance Smart Chain, Polygon, and Arbitrum allow for high-frequency trading, Ethereum is not suitable for these strategies. SingularityDAO's advanced market-making agents represent a significant leap forward in trading automation and optimization. With their ability to detect market phases, adapt to changing dynamics, and leverage predictive tools, these agents are poised to revolutionize trading strategies and enhance the financial performance of DynaSets. Sources: *arxiv.org/abs/2303.02342 arxiv.org/abs/2204.13265 youtube.com/watch?v=oedmjhef… #DeFi #AiFi #DynaVaults