Compass Labs’ Post

We’re thrilled to see our work highlighted by Compass Labs! OpenGradient is committed to leveraging AI/ML to drive innovation in DeFi, and working with Compass Labs’ Dojo platform has been a pleasure. From boosting LP returns by 18% to enhancing market efficiency while drastically reducing infrastructure overhead, these results reflect our vision for smarter, more efficient decentralized exchanges. Check out the full story and dive into the research paper linked below!

It's been a while since I've written a technical blog, and I've missed it. So, for the past few days, I used Claude, CCXT, Firebase, and React to create an automated trading strategy that creates a long/short portfolio every 24 hours on the Hyperliquid DEX that is live in production today with $500. On the blog, I share my experience and insights into leveraging AI-assisted development, the system architecture of the bot, code and other good stuff. Blog: https://lnkd.in/e3f7RbAq

Don't miss out! Join 500+ in registering for our most anticipated learning program of the year— our Study Season! We've got a great lineup of speakers - find details for our 8 Live Tracks below 🧵 REGISTER NOW TO ATTEND: https://buff.ly/43wpCtP Live Track 1/ Token Design Thinking Framework: A Structured Approach for Crypto Founders, Protocol Designers, and Token Engineers by Shermin Voshmgir, Founder of Token Kitchen. Register to discover her token network approach starting this Friday at 17:00 UTC! Live Track 2/ The Data Value-Creation Loop: An Engineering Perspective on Data Flywheels and Supply Chains by Trent McConaghy, Founder of Ocean Protocol. How do people sustain and thrive in the data economy? It's simple: ensure that they can make money! Register now to find out how! Live Track 3/ DeFi's Concentrated Liquidity from Scratch by Mark Richardson, Project Lead at Bancor. Join us in deriving concentrated liquidity bonding curves from first principles, exploring the transformation of DeFi's AMM technology, and reconstructing key liquidity models. Live Track 4/ Reputation-based Weighted Voting - A New Primitive for DAO Governance by Octopus and Angela Kreitenweis. This track will develop a new voting system that considers voters' past decisions and expertise to determine their influence in decision-making. Register to take part! Live Track 5/ On-chain Analytics for Token Engineers 101 — Become a DYOR Maxi from SCRATCH Using ChatGPT with Roderick McKinley, CFA. This track teaches on-chain analytics fundamentals using SQL on Dune Analytics and how to turbocharge progress with ChatGPT. Live Track 6/ Modelling and Simulating Decentralized Economic Systems with the Application of AI/ML with Muhammad Idrees, Token Engineer at BlockApex, alethea.ai, and aliagents.ai. Leveraging cutting-edge AI and #MachineLearning, this track explores how to build, analyze, and refine blockchain economic models. Live Track 7/ dApp Analysis: Exploring the Complex System Oriented Approach with Giuseppe Destefanis, Associate Professor Brunel University London. Join this track to explore a novel approach to understanding and analyzing dApps through the lens of complex systems theory. Live Track 8/ Token Engineering Value Capturing Fundamentals by Vasily Sumanov, Head of Research at PowerPool. Register to learn practical methods for analyzing existing tokens' value-capturing structures and value-capturing mechanics in new tokenized systems. Curious to learn more about these tracks? After registering for our Study Season, you'll find all the details available, including track overviews, session times, prior knowledge recommended, speaker details, and more! Don't miss out, register below for the Study Season today! Link: https://buff.ly/43wpCtP #tokenengineering #education #crypto

I am very proud to be supporting the Token Engineering Academy with my Live Track "DeFi's Concentrated Liquidity From Scratch". The scope of this course includes the three preeminent descriptions of concentrated liquidity from Bancor (2020 and 2022), and Uniswap (2021), as well as three additional descriptions informed by trigonometric analysis of the same. The purpose of this contribution is to organize the seminal and derivative forms of this cornerstone DeFi technology, and algebraically and geometrically elaborate these descriptions to achieve an authoritative and near-exhaustive overview of the underlying theory powering the current state-of-the-art in decentralized exchange infrastructure.

Over the past few years, development in the blockchain domain primarily focused on resolving intrinsic infrastructure challenges such as communication, security, interoperability, and scalability. With significant advancements in these areas, the focus has now shifted towards developing real-world use cases that address the limitations of traditional centralized systems. Currently, advanced use cases in decentralized AI infrastructure, DePIN, RWA tokenization, DeFi, and decentralized governance systems are being actively developed. The role of token engineers is pivotal in development of these use cases by building robust and resilient token-based economies, to make these applications scalable, sustainable, and impactful. Given the importance of token engineering discipline in driving this decentralization revolution, consider enrolling in the learning tracks offered by the TokenEngineering Academy and develop advanced skills and expertise of this emerging interdisciplinary engineering domain

🌟 Excited to Share: Exploring the Power of LangChain! 🌟 Today, I want to dive into an incredible tool that's transforming the way we think about building applications with language models: LangChain. 🚀 LangChain is a versatile framework designed to streamline the integration of large language models into various applications, ranging from chatbots to complex data pipelines. Here are some of the standout features: 1. **Seamless Integration**: LangChain makes it effortless to connect your language model to a wide array of data sources, including APIs, databases, and more, ensuring your applications are always informed and up-to-date. 2. **Modularity and Flexibility**: With its modular architecture, LangChain allows developers to customize and extend components to suit specific needs, fostering innovation and adaptability. 3. **Robust Tooling**: It offers powerful tools for managing prompts, handling token limits, and optimizing model performance, which are crucial for building efficient and reliable AI applications. 4. **Community and Support**: LangChain boasts a vibrant community and extensive documentation, providing a wealth of resources and support for developers at all levels. Whether you're a seasoned AI developer or just starting out, LangChain opens up a world of possibilities for creating intelligent, responsive, and impactful applications. I'm thrilled to see where this journey takes us and eager to hear about the innovative projects this community will build. Let's push the boundaries of what's possible with language models together! 💡 #AI #MachineLearning #LanguageModels #LangChain #TechInnovation #AIDevelopment

In today's fast-paced, volatile markets like NASDAQ-100, the battle for alpha is fiercer than ever. Hedge funds and investors are racing to capture fleeting opportunities and navigate complex risks. 💹⚔️ 🌟 Enter the game-changer: Large Language Models (LLMs) and advanced AI architectures like Retrieval-Augmented Generation (RAG). These cutting-edge tools are reshaping the landscape of investment strategy, enabling unprecedented speed, accuracy, and insight in financial analysis. 🧠🔍 Excited to share my contribution to this revolution: a powerful financial analysis web app that harnesses the capabilities of GPT-4, Langchain, and Streamlit to deliver comprehensive, AI-driven insights. 🚀📊 By integrating GPT-4, the app can provide detailed, context-aware responses to complex questions about market trends, financial metrics, and investment strategies. 💬💡 Langchain's Conversational Retrieval Chain allows for efficient processing of vast financial documents, extracting key insights through natural language queries. 📑🔍 The intuitive Streamlit interface offers a seamless user experience across devices, with interactive visualizations and dashboards that bring financial data to life. 📱📊 Future enhancements, such as DALL-E powered visualizations and Text-to-Speech functionality, are in the works to make insights even more engaging and accessible. 🎨🔊 Whether you're a hedge fund manager seeking alpha, a financial analyst navigating volatility, or an investor looking to stay ahead of the curve, this app empowers you with the tools to thrive in today's fast-evolving markets. 💪📈 🔗 Check out the app here: https://lnkd.in/gqm9PvYT I'd love to hear your thoughts and feedback as I continue pushing the boundaries of AI-driven financial analysis. 🚀 #InvestmentStrategy  #RiskManagement #ArtificialIntelligence #MachineLearning #Streamlit #Langchain #GPT4 #FinTech #RAG

This is one of the most useful articles I have read in a while, I agree with author 100% even though I have not tried his library yet. Tools like Langchain and even CrewAI that are over-hyped in normal dev circles are actually totally useless. The over "abstraction" is a serious problem and "black box" engineering is unsettling. I dont use any of them at all, i actually build my own agents manually -- which is a LOT of work, I would love a simpler library like this one . . . so looking forward to trying it out. #AI #aiagents #AIEngineering, #AITools, #Langchain, #CrewAI, #AgentDevelopment, #ManualEngineering, #OpenSourceAI, #DeveloperInsights, #AITech, #BlackBoxProblems, #TechInnovation, #AgentLibraries, #FutureOfAI, #CustomAI, #SoftwareDevelopment https://lnkd.in/dspCwH66

Exploring LangChain’s Potential for LLM Applications. I’ve recently started delving into the LangChain framework, and I’m eager to share some insights I’ve gathered: 1. Large Language Models (LLMs), like ChatGPT's iterations, offer incredible potential but also present some key challenges—knowledge staleness, limited ability to personalize interactions over multiple sessions, struggles with long-term context, and relative difficulty in correcting real-time errors. 2. These challenges stem from the static nature of their training processes. While they ensure consistency and reliability, they limit adaptability, real-time responsiveness, and personalization. 3. LangChain offers a solution, enabling the development of applications that build on LLMs while addressing these drawbacks. 4. By integrating external data sources, memory modules, and dynamic interaction capabilities, LangChain allows LLMs to adapt to real-world contexts, deliver personalized experiences, and stay responsive to evolving information. Next steps? I’m currently working on an application that leverages LangChain’s LLM lifecycle, using its building blocks, components, and third-party integrations. Powered by OpenAI's APIs, this project is an opportunity for me to apply these tools to create a simplified, impactful solution. I’m excited to enhance my understanding of LangChain and its potential to drive more personalized, adaptive, and data-informed decision-making. #LLMs #openai #langchang #langsmith #langgraph #apis #datasolutions #techleadership #hypetrain #langchainhypetrain

"When future generations look back on the #Web3 landscape, 2024 will mark several evolutionary tipping points. As an industry insider and futurist actively engaged with various projects and events like Consensus 2024, I have a broad perspective on this evolution." ETC Group Web 3.0 UCITS #ETF $WEB3 #etfs  https://lnkd.in/eRrTPQVp ETC Group - now a part of Bitwise