Best AI tools for< Location Researcher >

PropHunt.ai is an AI-powered platform designed for real estate professionals and property investors. It utilizes advanced machine learning algorithms to analyze property data and provide valuable insights for property hunting and investment decisions. The platform offers features such as property price prediction, neighborhood analysis, investment risk assessment, property comparison, and market trend forecasting. With PropHunt.ai, users can make informed decisions, optimize their property investments, and stay ahead in the competitive real estate market.

Bedrock Analytics is an AI-powered Location Intelligence and AI Platform that helps organizations maximize the value of place for strategic investments, operational performance, and everyday decisions. The platform offers scalable analysis and enrichment solutions embedded in web & mobile apps, with a wide range of data layers across categories such as human mobility, points of interest, and economic data. Bedrock Analytics turns locations into assets by providing the fastest, easiest, and most effective way to utilize location data for solving organizational tasks and challenges.

Hella Jobs is a leading platform for AI, Machine Learning, and Data Science jobs. It connects job seekers with top employers in the field of AI/ML, allowing employers to post open jobs and hire top talent. Job seekers can create profiles, submit resumes, and find new job opportunities. The platform offers features such as job filtering by keywords and location, job category selection, salary range selection, and job type filtering. Hella Jobs aims to streamline the job search process for both employers and job seekers in the AI/ML industry.

QPNOTES is an AI tool designed to help users save and manage their AI prompts in one convenient location. By enabling JavaScript, users can access the app's features to streamline their AI prompt management process. With QPNOTES, users can easily organize, store, and retrieve their AI prompts efficiently, enhancing their workflow and productivity.

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, neighborhood statistics, and personalized recommendations based on millions of real estate data points. Kurby revolutionizes the real estate industry by combining AI insights with real-time market data to help users make informed decisions and find hidden gems in the property market.

GrantWizard is an AI-powered tool designed to assist students in finding the best grants for college education. By leveraging magical AI powers, the tool considers various factors such as the user's location, high school details, GPA, extracurricular activities, colleges of interest, and preferred majors. GrantWizard aims to simplify the grant search process and help students elevate their grant game with wizardly expertise.

Roic AI is an AI tool designed to provide users with essential financial data for analyzing companies. It offers comprehensive company summaries, 30+ years of financial statements, and earnings call transcripts in a single location. Users can access crucial information about popular companies like Apple Inc. and Microsoft Corporation through this platform.

Global Plastic Watch (GPW) is a digital platform that maps the world's plastic pollution in near real-time using a unique combination of satellite imagery and artificial intelligence. It provides a comprehensive view of the global plastic waste crisis, including the location and size of plastic waste sites, the types of plastic waste, and the impact of plastic pollution on the environment and human health.

Personalized.energy is an AI-powered online platform that offers personalized electricity plans tailored to individual needs and lifestyles. The platform simplifies the process of finding the best energy solution by utilizing an AI-powered search engine to compare and match plans based on users' location and usage profiles. By eliminating the need for manual research and comparison, Personalized.energy provides a stress-free experience for users looking to navigate the complexities of the energy market.

Phind AI is a cost-effective alternative to other AI search engines, making AI search accessible to everyone, regardless of location. It offers a comprehensive search experience with a user-friendly interface and advanced features.

iNCSAI List is a comprehensive database of AI startups and companies. It provides information on the latest AI trends, news, and resources. The website also offers a directory of AI companies, sorted by industry and location. iNCSAI List is a valuable resource for anyone interested in learning more about AI or finding AI-related products and services.

Factori is a data intelligence platform designed for an AI-first world, offering a wide range of products and datasets to empower businesses with advanced data insights. It enables users to uncover movement trends, reach customers effectively, drive data-driven insights, personalize experiences, and target the right consumers with unique segments. Factori is trusted by global businesses for all their data requirements, providing high-quality data to improve predictive and causal models.

MaskMyPrompt is an AI tool designed to anonymize prompts before sending them to ChatGPT. It ensures that your prompt data remains private by masking names and sensitive information. The tool is programmed by Mike Ushakov and ChatGPT, utilizing the powerful Transformers.js. Users can reach out for support or feature requests via email or Twitter.

ScaDS.AI (Center for Scalable Data Analytics and Artificial Intelligence) is a research center focusing on Data Science, Artificial Intelligence, and Big Data with locations in Dresden and Leipzig. It is one of the five new AI centers in Germany funded under the federal government's AI strategy by the Federal Ministry of Education and Research and the Free State of Saxony. The center collaborates closely with TUD Dresden University of Technology and Leipzig University, aiming to bridge the gap between mass data utilization, knowledge management, and advanced AI methods.

GetOData is a powerful web scraping API and Chrome extension that offers AI-based data extraction tools for small-scale scraping projects. It allows users to extract large amounts of data without getting blocked by anti-bot mechanisms like Captchas, Cloudflare, or Akamai. The API is built by data extraction experts and provides features such as choosing the output format (HTML or JSON), setting proxy locations, executing JavaScript, taking screenshots, and more. GetOData offers simplified pricing options for freelancers, startups, and businesses, with competitive rates and high success rates compared to other services in the market.

Picarta AI is an image geolocalization solution that uses artificial intelligence to find where a photo has been taken in the world. By uploading a photo, users can get the GPS location, latitude, longitude, time stamp, and camera details of the image. Picarta AI also offers a map view of the image location and allows users to download the map. The company's vision is to empower individuals and businesses with the most accurate and reliable image geolocalization solution, unlocking new possibilities for exploration, research, and decision-making.

Orbital Insight is a leading geospatial data analytics platform that provides users with the ability to query the world with three basic parameters: WHAT type of activity? WHERE on earth? WHEN? The platform automates the most difficult steps of deriving insights, allowing you to answer many challenging geospatial questions. Orbital Insight's GO platform is designed for enterprise collaboration and transforms multiple geospatial data sources to accelerate and streamline team member's research, reporting, due diligence, and more.

DagsHub is an open source data science collaboration platform that helps AI teams build better models and manage data projects. It provides a central location for data, code, experiments, and models, making it easy for teams to collaborate and track their progress. DagsHub also integrates with a variety of popular data science tools and frameworks, making it a powerful tool for data scientists and machine learning engineers.

Casc is an AI-powered knowledge management tool that helps teams access and share information quickly and easily. It integrates with popular collaboration tools like Slack, Google Drive, and Confluence, allowing users to search and access documents, images, and other content from a central location. Casc also uses natural language processing to understand user queries and deliver precise answers, making it easy for teams to find the information they need without having to spend hours searching through multiple sources.

Stops.com is a location-based platform that allows users to find, create, and share location-based content and products. The platform boasts over 130 million locations and features AI capabilities to enhance user experience. Stops.com partners with businesses for location-based marketing opportunities, offering free business listings and premium services. Users can access a variety of content, including videos, blogs, and apps, to discover new locations and products. The platform aims to connect customers with brands and products nearby, making it a valuable tool for both businesses and consumers.

SimAI is the industry's first full-stack, high-precision simulator for AI large-scale training. It provides detailed modeling and simulation of the entire LLM training process, encompassing framework, collective communication, network layers, and more. This comprehensive approach offers end-to-end performance data, enabling researchers to analyze training process details, evaluate time consumption of AI tasks under specific conditions, and assess performance gains from various algorithmic optimizations.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

Slideflow is a deep learning library for digital pathology, offering a user-friendly interface for model development. It is designed for medical researchers and AI enthusiasts, providing an accessible platform for developing state-of-the-art pathology models. Slideflow offers customizable training pipelines, robust slide processing and stain normalization toolkit, support for weakly-supervised or strongly-supervised labels, built-in foundation models, multiple-instance learning, self-supervised learning, generative adversarial networks, explainability tools, layer activation analysis tools, uncertainty quantification, interactive user interface for model deployment, and more. It supports both PyTorch and Tensorflow, with optional support for Libvips for slide reading. Slideflow can be installed via pip, Docker container, or from source, and includes non-commercial add-ons for additional tools and pretrained models. It allows users to create projects, extract tiles from slides, train models, and provides evaluation tools like heatmaps and mosaic maps.

Windows Agent Arena (WAA) is a scalable Windows AI agent platform designed for testing and benchmarking multi-modal, desktop AI agents. It provides researchers and developers with a reproducible and realistic Windows OS environment for AI research, enabling testing of agentic AI workflows across various tasks. WAA supports deploying agents at scale using Azure ML cloud infrastructure, allowing parallel running of multiple agents and delivering quick benchmark results for hundreds of tasks in minutes.

Notate is a powerful desktop research assistant that combines AI-driven analysis with advanced vector search technology. It streamlines research workflow by processing, organizing, and retrieving information from documents, audio, and text. Notate offers flexible AI capabilities with support for various LLM providers and local models, ensuring data privacy. Built for researchers, academics, and knowledge workers, it features real-time collaboration, accessible UI, and cross-platform compatibility.

TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

Awesome-Attention-Heads is a platform providing the latest research on Attention Heads, focusing on enhancing understanding of Transformer structure for model interpretability. It explores attention mechanisms for behavior, inference, and analysis, alongside feed-forward networks for knowledge storage. The repository aims to support researchers studying LLM interpretability and hallucination by offering cutting-edge information on Attention Head Mining.

xFinder is a model specifically designed for key answer extraction from large language models (LLMs). It addresses the challenges of unreliable evaluation methods by optimizing the key answer extraction module. The model achieves high accuracy and robustness compared to existing frameworks, enhancing the reliability of LLM evaluation. It includes a specialized dataset, the Key Answer Finder (KAF) dataset, for effective training and evaluation. xFinder is suitable for researchers and developers working with LLMs to improve answer extraction accuracy.

wdoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It aims to handle large volumes of diverse document types, making it ideal for researchers, students, and professionals dealing with extensive information sources. wdoc uses LangChain to process and analyze documents, supporting tens of thousands of documents simultaneously. The system includes features like high recall and specificity, support for various Language Model Models (LLMs), advanced RAG capabilities, advanced document summaries, and support for multiple tasks. It offers markdown-formatted answers and summaries, customizable embeddings, extensive documentation, scriptability, and runtime type checking. wdoc is suitable for power users seeking document querying capabilities and AI-powered document summaries.

YGO Agent is a project focused on using deep learning to master the Yu-Gi-Oh! trading card game. It utilizes reinforcement learning and large language models to develop advanced AI agents that aim to surpass human expert play. The project provides a platform for researchers and players to explore AI in complex, strategic game environments.

This repository contains course materials for T81 559: Applications of Generative Artificial Intelligence at Washington University in St. Louis. The course covers practical applications of Large Language Models (LLMs) and text-to-image networks using Python. Students learn about generative AI principles, LangChain, Retrieval-Augmented Generation (RAG) model, image generation techniques, fine-tuning neural networks, and prompt engineering. Ideal for students, researchers, and professionals in computer science, the course offers a transformative learning experience in the realm of Generative AI.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

ShortcutsBench is a project focused on collecting and analyzing workflows created in the Shortcuts app, providing a dataset of shortcut metadata, source files, and API information. It aims to study the integration of large language models with Apple devices, particularly focusing on the role of shortcuts in enhancing user experience. The project offers insights for Shortcuts users, enthusiasts, and researchers to explore, customize workflows, and study automated workflows, low-code programming, and API-based agents.

Scira is a powerful open-source tool for analyzing and visualizing data. It provides a user-friendly interface for data exploration, cleaning, and modeling. With Scira, users can easily import datasets, perform statistical analysis, create insightful visualizations, and generate reports. The tool supports various data formats and offers a wide range of statistical functions and visualization options. Whether you are a data scientist, researcher, or student, Scira can help you uncover valuable insights from your data and communicate your findings effectively.

This repository focuses on test-time computing, exploring various strategies such as test-time adaptation, modifying the input, editing the representation, calibrating the output, test-time reasoning, and search strategies. It covers topics like self-supervised test-time training, in-context learning, activation steering, nearest neighbor models, reward modeling, and multimodal reasoning. The repository provides resources including papers and code for researchers and practitioners interested in enhancing the reasoning capabilities of large language models.

AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.

Swarms provides simple, reliable, and agile tools to create your own Swarm tailored to your specific needs. Currently, Swarms is being used in production by RBC, John Deere, and many AI startups.

BIG-Bench Mistake is a dataset of chain-of-thought (CoT) outputs annotated with the location of the first logical mistake. It was released as part of a research paper focusing on benchmarking LLMs in terms of their mistake-finding ability. The dataset includes CoT traces for tasks like Word Sorting, Tracking Shuffled Objects, Logical Deduction, Multistep Arithmetic, and Dyck Languages. Human annotators were recruited to identify mistake steps in these tasks, with automated annotation for Dyck Languages. Each JSONL file contains input questions, steps in the chain of thoughts, model's answer, correct answer, and the index of the first logical mistake.

LLMClient is a JavaScript/TypeScript library that simplifies working with large language models (LLMs) by providing an easy-to-use interface for building and composing efficient prompts using prompt signatures. These signatures enable the automatic generation of typed prompts, allowing developers to leverage advanced capabilities like reasoning, function calling, RAG, ReAcT, and Chain of Thought. The library supports various LLMs and vector databases, making it a versatile tool for a wide range of applications.

Instructor is a Typescript library for structured extraction in Typescript, powered by llms, designed for simplicity, transparency, and control. It stands out for its simplicity, transparency, and user-centric design. Whether you're a seasoned developer or just starting out, you'll find Instructor's approach intuitive and steerable.

A visual analysis expert who guesses image locations.

Get the latest Crime Rate of any location in the UK

Compares prices, ensures privacy, and asks for location

Analyzes images, providing facts, history, and location details.

Free Guides on Google Maps data scraping

Virtual assistant for NYC 311 services, providing info and guidance on city programs.

Helps locate stores and businesses informatively

Finds top 10 UFO sightings in a given area with links and media.

A comprehensive Nationwide database of law firms and lawyers, including specialties, locations, and contact information with live URLs.

국가, 도시 별 주요 정보 검색

I analyze Street View images to guess countries and cities.

Cartographic Creator from the 1600's

Atlas Eye analyzes images to guess their location

Begin by providing a location or situation. Commands: /l /i /m /s

A game of location guessing with photorealistic images.

Explore any location with a visual street view perspective.

Redirector to New GPT Location for Information Law Course

Offers workout snacks based on lifestyle and location

An assistant for accurate tide timings based on location.

Guides in AR game development & location-based features