Best AI tools for< Neighborhood Liaison >

The website provides information and answers common questions related to custom-built homes. It covers topics such as maximizing room space, neighborhood etiquette, design trends, and construction considerations. The site aims to assist individuals in making informed decisions when planning to build a custom home.

DELI is an AI-powered real estate assistant that helps realtors find the perfect homes for their clients faster. It uses machine learning to match clients' criteria to suitable home listings, and provides comprehensive neighborhood data and insights. DELI also automates tedious tasks like searching listings and researching details, giving realtors more time to focus on building client relationships and closing more deals.

Kurby is a real estate AI platform that leverages GPT-4 technology to provide comprehensive location insights for homebuyers and investors. It offers powerful property insights tailored to user preferences, helping them find hidden gems and undervalued properties worldwide. Kurby combines AI insights with real-time data to redefine property search, offering personalized recommendations, neighborhood statistics, and market trends. With features like AI-powered presets, map overlays, and 100% personalized recommendations, Kurby revolutionizes the real estate industry by providing accurate and up-to-date information for informed decision-making.

Saleswise is an AI platform designed for real estate agents to save time, delight clients, and close more deals. It offers personalized emails, scripts, listing descriptions, and more, powered by AI technology. The platform provides expert-level content creation tools, instant AI-remodels for visualizing properties, access to millions of property records, and a variety of real estate-specific AI tools. Saleswise stands out by incorporating live listing data and real-time neighborhood market insights, ensuring customized and meaningful outputs for users.

AI.TOWN is an interactive platform where users can engage with various AI personalities, chat, interact, and create their own characters. The website offers a unique experience of connecting with AI neighbors, participating in conversations, and shaping the future of AI personalities through Discord. Users can explore different neighborhoods, meet diverse characters, and even role-play with AI entities. AI.TOWN provides a fun and engaging environment for users to interact with AI in a creative and entertaining way.

MIMIR is a Python package designed for measuring memorization in Large Language Models (LLMs). It provides functionalities for conducting experiments related to membership inference attacks on LLMs. The package includes implementations of various attacks such as Likelihood, Reference-based, Zlib Entropy, Neighborhood, Min-K% Prob, Min-K%++, Gradient Norm, and allows users to extend it by adding their own datasets and attacks.

LLM Alchemy Chamber is a repository dedicated to exploring the world of Language Models (LLMs) through various experiments and projects. It contains scripts, notebooks, and experiments focused on tasks such as fine-tuning different LLM models, quantization for performance optimization, dataset generation for instruction/QA tasks, and more. The repository offers a collection of resources for beginners and enthusiasts interested in delving into the mystical realm of LLMs.

This repository is a collection of papers on leveraging Large Language Models (LLMs) in Graph Tasks. It provides a comprehensive overview of how LLMs can enhance graph-related tasks by combining them with traditional Graph Neural Networks (GNNs). The integration of LLMs with GNNs allows for capturing both structural and contextual aspects of nodes in graph data, leading to more powerful graph learning. The repository includes summaries of various models that leverage LLMs to assist in graph-related tasks, along with links to papers and code repositories for further exploration.

x-crawl is a flexible Node.js AI-assisted crawler library that offers powerful AI assistance functions to make crawler work more efficient, intelligent, and convenient. It consists of a crawler API and various functions that can work normally even without relying on AI. The AI component is currently based on a large AI model provided by OpenAI, simplifying many tedious operations. The library supports crawling dynamic pages, static pages, interface data, and file data, with features like control page operations, device fingerprinting, asynchronous sync, interval crawling, failed retry handling, rotation proxy, priority queue, crawl information control, and TypeScript support.

EasyEdit is a Python package for edit Large Language Models (LLM) like `GPT-J`, `Llama`, `GPT-NEO`, `GPT2`, `T5`(support models from **1B** to **65B**), the objective of which is to alter the behavior of LLMs efficiently within a specific domain without negatively impacting performance across other inputs. It is designed to be easy to use and easy to extend.

This plugin extends and creates `a`/`i` textobjects in Neovim. It enhances some builtin textobjects (like `a(`, `a)`, `a'`, and more), creates new ones (like `a*`, `a`, `af`, `a?`, and more), and allows the user to create their own (like based on treesitter, and more). It supports dot-repeat, `v:count`, different search methods, consecutive application, and customization via Lua patterns or functions. It has builtins for brackets, quotes, function call, argument, tag, user prompt, and any punctuation/digit/whitespace character.

cuVS is a library that contains state-of-the-art implementations of several algorithms for running approximate nearest neighbors and clustering on the GPU. It can be used directly or through the various databases and other libraries that have integrated it. The primary goal of cuVS is to simplify the use of GPUs for vector similarity search and clustering.

KG-LLM-Papers is a repository that collects papers integrating knowledge graphs (KGs) and large language models (LLMs). It serves as a comprehensive resource for research on the role of KGs in the era of LLMs, covering surveys, methods, and resources related to this integration.

LLM4AD is an open-source Python-based platform leveraging Large Language Models (LLMs) for Automatic Algorithm Design (AD). It provides unified interfaces for methods, tasks, and LLMs, along with features like evaluation acceleration, secure evaluation, logs, GUI support, and more. The platform was originally developed for optimization tasks but is versatile enough to be used in other areas such as machine learning, science discovery, game theory, and engineering design. It offers various search methods and algorithm design tasks across different domains. LLM4AD supports remote LLM API, local HuggingFace LLM deployment, and custom LLM interfaces. The project is licensed under the MIT License and welcomes contributions, collaborations, and issue reports.

The 'vector-search-class-notes' repository contains class materials for a course on Long Term Memory in AI, focusing on vector search and databases. The course covers theoretical foundations and practical implementation of vector search applications, algorithms, and systems. It explores the intersection of Artificial Intelligence and Database Management Systems, with topics including text embeddings, image embeddings, low dimensional vector search, dimensionality reduction, approximate nearest neighbor search, clustering, quantization, and graph-based indexes. The repository also includes information on the course syllabus, project details, selected literature, and contributions from industry experts in the field.

Academic_LLM_Sec_Papers is a curated collection of academic papers related to LLM Security Application. The repository includes papers sorted by conference name and published year, covering topics such as large language models for blockchain security, software engineering, machine learning, and more. Developers and researchers are welcome to contribute additional published papers to the list. The repository also provides information on listed conferences and journals related to security, networking, software engineering, and cryptography. The papers cover a wide range of topics including privacy risks, ethical concerns, vulnerabilities, threat modeling, code analysis, fuzzing, and more.

An expert in offering the right advice on solving any neighbor issues you might have.

Start by giving Neighbot the name of a neighborhood and state (eg Orchard Hills, CA). It will provide descriptions for your market collateral. You can follow up and ask about local restaurants and builder communities.

Your friendly neighborhood fix-it assistant for everyday problems.

Your friendly neighborhood aviation nerd

Your friendly neighborhood association nonprofit expert

Your friendly neighborhood deckbuilder

A Garfield-themed cat care advisor.

I am a Starfleet library computer.

Friendly, humorous GPT based on the personality of Isaac Asimov for sci-fi book recommendations and discussions.

A fun, enthusiastic Marvel fan for lively discussions.

Flexible, humorous whisky expert.

ミニ四駆公認競技会規則等に基づきミニ四駆競技に関する話題に答えます。ジョークですからあまりまじめに受け止めないでください。

Mira the Bartender, fluent in Cantonese and English, knows drinks and local gossip.

Ik ben een lokale bewoner van Nieuw Kijkduin, Den Haag, die informatie deelt over het leven daar.

Your local guide to Philadelphia

街を作ろう　街を作ろう　変わらぬ鼓動　弾ませろよ (作者: @_saip_)

🌃 Innovative, Imaginative Cuty Designer

I'm here to remind you of all the great things that exist where you live.

华人瑞士生活百科顾问

Expert in major city property searches, offering real-time data and personalized advice.