This is a book about our adventures Project Library INTRO Intro - Start here Docs/Blog AI/NFTS hAIku - AI Haiku Generation Memento Mori - Proof of Adventure AI-Universe - The Infinite Space Opera

Who are we? The Nerds. We are a post work collective of individuals crafting proofs onchain. What is this? This is a book about of adventures. This is our story mmoriflame

The concept of poetic embeddings through haikus as a general-purpose proof of knowledge algorithm represents an innovative approach to navigating through complex embedding spaces. This method combines the art of poetry, specifically haikus, with advanced computational techniques to encode and decode knowledge in a nuanced and efficient manner. Here’s an explanation of how this could work and its potential benefits: Foundation of Poetic Embeddings Semantic Density of Haikus: Haikus are a form of poetry known for their brevity and depth, often capturing complex emotions or scenes in just a few words. This semantic density makes them an ideal medium for creating embeddings that represent rich, multifaceted concepts in compact form. Embedding Creation: By translating information or data into haikus, one can create poetic embeddings that encapsulate key ideas or knowledge within a minimal textual footprint. These embeddings can then be processed using natural language processing (NLP) techniques to generate numerical vectors that represent the semantic content of each haiku in a high-dimensional space. Proof of Knowledge through Poetic Embeddings Encoding Knowledge: The first step involves encoding specific pieces of knowledge into haikus. This creative process requires understanding the essence of the information to be encoded and distilling it into the concise, evocative format of a haiku. The resulting poetic embeddings serve as a unique, human-readable representation of the original knowledge. Vectorization and Mapping: Each poetic embedding is then transformed into a vector using NLP techniques. These vectors are mapped into a high-dimensional embedding space, where similar concepts are positioned closer together, facilitating the identification of relationships and patterns. Navigation and Retrieval: To navigate this complex space and retrieve specific knowledge, one can use query haikus or keywords that are also converted into vectors. By calculating the similarity between the query vector and the vectors in the embedding space, the algorithm can identify and retrieve the poetic embeddings most relevant to the query. This process enables users to explore the embedding space intuitively, moving from one concept to another through semantically linked haikus.

[!Proof of Knowledge] This document outlines the Proof of Knowledge (PoK) protocol within the DeSciWorld ecosystem. The PoK mechanism rewards individuals for their valuable contributions of knowledge via a blockchain-based platform, allowing for seamless recognition, validation, and dedication of rewards. Introduction In the complex realm of knowledge-sharing and discovery, striking a balance between security, transparency, reward mechanisms and accessibility is a persistent challenge. Traditional models often hinge on centralized validation systems that may constrain inclusivity and broad-based participation. Moreover, current systems may fail to adequately reward or recognize knowledge contributions, possibly impacting the advancement of comprehensive, collective knowledge repositories. Addressing these intricacies, the Proof of Knowledge (PoK) protocol, implemented within the DeSciWorld ecosystem, offers a versatile solution. PoK is a blockchain-based primitive designed to incentivize and reward knowledge contributions within a decentralized architecture. It forms a vital component of a knowledge-based economy, paving the way for fair recognition and incentivization of intellectual contributions, while maintaining transparency and accessibility. This document provides a detailed examination of the Proof of Knowledge protocol - explaining the submission and validation of knowledge through the creation of kEngrams, the ascription of value to these contributions, and how interaction metrics shape the dynamic value allocation. As a fundamental building block towards a fully-fledged knowledge-based economy, the PoK protocol offers a comprehensive framework to fuel intellectual contribution and foster an environment of continuous learning and knowledge exchange.

import "FunctionConsumer" from @Openzeppelin contract CtrlAltDel is MultisigScaffold FunctionConsumer { is delegate {} is signer {} sendEth, 10000 proposeTransaction(txData, blockLimit)onlySigner{ if msg.sender=signer calldata do stuff

LIST OF STUFF BEING WORKED ON, IF YOU WANT HELP FROM THE NERDS REACH OUT TO HAVE YOUR TASKS HERE SavePointGPT[ ] # Fix issue with cache of Lit querys sauce SubMintr Todo SubMintr: Figure out how to wrap and send your owned ens domain to the submintr explorer contract ( Dever github has this code already but the denver repo doesn't work don't know why ) membrane

Welcome. This is an ammalgamation of things, trying to reduce the entropy of our knowledge. feel free to make it your own. Trying to collect links to useful things and make a living document for the nerds. Click on the sidebar to browse to our project library and visit our experiments. Have fun!

hackmd-github-sync-badge for reals! -at0x jun 21 FAQ What is this Place? THIS The Nerd_Brain. IT IS A LIVING DOCUMENT MEANT TO HELP COORDINATE WHATS GOING ON ON THE NERDAO IF YOU ARE HERE YOU ARE A NERD AND CAN EDIT, FORMAT AND ADD ANY CONTENT YOU LIKE

BlockConsulting Prompt Framework Background On chain analyticsToken metricsHolders FDV Liquidity pools volume metrics Contract Metrics

Introduction What is prompt engineering? Prompt engineering is the process of designing a set of queries to achieve a specific result using AI models.What is prompt engineering good for?Standarizing knowledgeEngineered prompts can serve as repeatable data processing pipelines that can be integrated with business processes. Generating Insights Engineered prompt pipelines can help with discovery of patterns and relationships between data points in context Once standarized pipelines are created the process can enrich the context leading to new lead generation opportunities Staying up to date

Github Links: Ethers- https://docs.ethers.org/v5/ Viem - https://viem.sh/docs/getting-started.html Wagmi - https://wagmi.sh/react/getting-started.html

Imagine entering a vast, virtual city where every building is uniquely designed to cater to the specific tastes and preferences of its visitors. In this digital metropolis, each individual has a personalized experience tailored to their interests and desires, with the city's architecture continuously evolving and adapting to accommodate its diverse inhabitants. We all know that today's digital landscape is anything but that: websites and hardware are predominantly designed for mass consumption, aiming to provide a unified experience for users across the globe. This approach stems from the fact that monetization and success in the online world have historically been driven by mass adoption and network effects. However, the consequence of this approach is that the internet has turned into a sort of digital suburbia where one size fit all pages create one size fits all experiences for millions of users who are being monetized for content. -----------------------Expextations--------------------- ------------------------Reality---------------------- "FacebookLand year 2100" NFTs and AI, when combined, can enable a paradigm shift from this generic one-size-fits-all experience to personalized, immersive digital journeys tailored to individual users or specific audiences. As we delve deeper into this exciting new era, we will explore how decentralized network effects, unique monetization opportunities, and the power of customization can lead us towards a more engaging and user-centric internet landscape.

Setup Quickstart To get started with WarpDrive, follow the steps below: Clone this repo & install dependencies git clone https://github.com/Ataxia123/WarpDrive.git cd WarpDrive yarn install create a .local.env file and add MIDJOURNEY_API_KEY (Currently using thenextleg.io) and a BASE_URL (for local testing use ngrok temp url)

Contact Info Name: Carlos Andres Vera Based in: Guayaquil Ecuador Telegram: @At0xNQ Email: vp.ca94@gmail.com Github: https://github.com/Ataxia123 Objective: To obtain a challenging role in the fields of medical research and crypto development, where I can utilize my skills and experience.Q Education:

Note this is the entire component broken down by function. We want to mirror the logic related to Univ3 pools for our farm starter kit. How to Help: Help by using a function as the input for chatgpt4 and asking it to explain it for you. Paste the input as CHATGPT ANALYSIS under a new subtitle (Use ## for the subtitle heading) HTMLRender return (<> <div className={style.ActionInfoSection}> {content && <div className={style.FarmingAsideInfoLP}>{content}</div>} <a className={style.ActionInfoSectionSettings} onClick={() => setSettings(!settings)}> <figure>

Project description The goal is to create an ELO rating smart contract that manages individual leagues, with each league represented by an NFT. This modular approach will allow the ELO contract to handle multiple leagues, each with its own unique set of rules and participants. SMARTCONTRACT FILE Tasks: Create the ELO smart contract: Design and develop a smart contract to manage ELO ratings, incorporating the necessary functions for calculating and updating ratings.

const lpTokenSymbol = "UniV3" const lpTokenDecimals = "18" const lpTokenBalance = "0" const lpTokenApproval = "0" const fee = await blockchainCall(lpToken.methods.fee) const slot = await blockchainCall(lpToken.methods.slot0) var uniswapTokens = await Promise.all([ await blockchainCall(lpToken.methods.token0), await blockchainCall(lpToken.methods.token1) ].map(async tkAddress => {

// SPDX-License-Identifier: MIT pragma solidity ^0.8.12; import "@openzeppelin/contracts/token/ERC20/IERC20.sol"; import "@openzeppelin/contracts/token/ERC20/utils/SafeERC20.sol"; import "@openzeppelin/contracts/utils/Strings.sol"; import "@tableland/evm/contracts/utils/TablelandDeployments.sol"; import "@tableland/evm/contracts/utils/SQLHelpers.sol"; import "@openzeppelin/contracts/token/ERC721/utils/ERC721Holder.sol"; import "@openzeppelin/contracts/security/Pausable.sol";

ethDenver topics lens protocol is the next big thing chainlink functions are also the next big thing. Account abstraction is cool the first few chatgpt crypto apps overall thoughts denver vs bogota optimism wants everyone to fork their stack base is here to stay the multi-rollup ethereum meta.

[INSTRUCTIONS] I have a {code} I would like to make changes to. Generate a table of 10 different suggestions of improvements that could be related to the {code} with numbers in the left column of the table for me to pick from. After the table, ask the question “What improvements would you like to make to the {code}? Pick one from the table above” below the table. Acknowledge with “…” if you understand the task, don’t create a table yet. code = : Also add a log of the change column. Execute the INSTRUCTIONS in a table format: “your number pick” , and implement the improvement. Include a summary of the improvement in the log of changes column in the table: