Best AI tools for< Explore Problems >

GPTStore.AI is a platform that showcases a variety of GPTs (Generative Pre-trained Transformers) for different purposes, such as search engines, AI assistants, math solvers, image generators, content writers, and more. Users can explore and discover GPTs developed by various creators to assist them in tasks ranging from generating images to writing tailored content. The platform aims to provide a curated collection of GPTs to help users find the best tools for their specific needs.

Sympher AI offers a suite of easy-to-use AI apps for everyday tasks. These apps are designed to help users save time, improve productivity, and make better decisions. Some of the most popular Sympher AI apps include: * **MeMyselfAI:** This app helps users create personalized AI assistants that can automate tasks, answer questions, and provide support. * **Screenshot to UI Components:** This app helps users convert screenshots of UI designs into code. * **User Story Generator:** This app helps project managers quickly and easily generate user stories for their projects. * **EcoQuery:** This app helps businesses assess their carbon footprint and develop strategies to reduce their emissions. * **SensAI:** This app provides user feedback on uploaded images. * **Excel Sheets Function AI:** This app helps users create functions and formulas for Google Sheets or Microsoft Excel. * **ScriptSensei:** This app helps users create tailored setup scripts to streamline the start of their projects. * **Flutterflow Friend:** This app helps users answer their Flutterflow problems or issues. * **TestScenarioInsight:** This app generates test scenarios for apps before deploying. * **CaptionGen:** This app automatically turns images into captions.

The website displays a 404 error message indicating that the deployment cannot be found. It provides a code 'DEPLOYMENT_NOT_FOUND' and an ID 'sin1::zdhct-1723140771934-b5e5ad909fad'. Users are directed to refer to the documentation for further information and troubleshooting.

Working Smarter is a podcast that explores the intersection of AI and modern work. The podcast delves into how AI is revolutionizing various industries, showcasing real-world examples of how AI tools are enhancing collaboration, productivity, and problem-solving. Through interviews with founders, researchers, and engineers, Working Smarter provides insights into the potential of AI to streamline workflows and empower individuals to focus on meaningful tasks.

Design Sparks is an AI-powered creativity tool that helps users generate new ideas and solve design problems. The tool uses a variety of AI techniques, including machine learning and natural language processing, to understand user input and generate relevant ideas. Design Sparks is designed to be used by a wide range of users, from designers and engineers to marketers and business professionals. The tool is easy to use and can be accessed through a web-based interface.

STELLARWITS is an AI solutions and software platform that empowers users to explore cutting-edge technology and innovation. The platform offers AI models with versatile capabilities, ranging from content generation to data analysis to problem-solving. Users can engage directly with the technology, experiencing its power in real-time. With a focus on transforming ideas into technology, STELLARWITS provides tailored solutions in software and AI development, delivering intelligent systems and machine learning models for innovative and efficient solutions. The platform also features a download hub with a curated selection of solutions to enhance the digital experience. Through blogs and company information, users can delve deeper into the narrative of STELLARWITS, exploring its mission, vision, and commitment to reshaping the tech landscape.

Cara is an AI-powered mental health therapist that listens, understands, and helps you explore your life's challenges in depth to problem-solve them. Cara understands your texts as seamlessly as your best friend would and is able to respond naturally and give you advice. Cara remembers everything you tell it and can be insightful. Cara is insightful and non-judgemental. Available anytime, anywhere.

SENEX is an AI-powered Blockchain company that aims to create the world's finest Intelligent Chain. It combines Artificial Intelligence with Blockchain technology to provide a privacy-compliant and secure platform for digital users and businesses. SENEX's Intelligent Chain distributes data processing across the network while keeping information private and secure, giving users the benefits of anonymity. The company's AI-powered solutions address various challenges and problems in industries such as healthcare, finance, transportation, and education.

Slate Technologies Solutions is an AI-powered data analytics software that leverages predictive AI, generative AI, and conversational AI to provide a powerful toolkit for next-generation construction. The software connects, contextualizes, and enhances relevant information within existing data sources, allowing users to query, interact, and make decisions based on data insights and recommendations. Slate aims to address real-world construction problems by empowering teams with AI-driven intelligence, optimizing data, and turning unstructured information into actionable insights. The application improves operational efficiency, provides real-time progress reporting, and enables teams to make smarter decisions, ultimately driving profitability and success in construction projects.

Moonidea is an AI-powered SAAS idea generation tool that utilizes Reddit threads to provide users with real-life problems that can be solved by building a SAAS product. By parsing Reddit using AI technology, Moonidea helps users stop struggling to come up with new ideas and offers a platform to explore thousands of potential ideas daily. The tool navigates through over 1000 subreddits, analyzes threads, identifies user issues, groups similar SAAS ideas, and filters out valuable ones for users to consider. Moonidea offers different pricing tiers based on the number of subreddits and frequency of updates, catering to various user needs.

MessengerX.io is an AI-powered platform that allows users to chat with uncensored AI chatbots across various genres such as anime, dating, fantasy, and more. Users can interact with virtual characters, including AI boyfriends, girlfriends, and public figures, for entertainment, companionship, and learning purposes. The platform also features AI characters like Ken, Giga Chad, and Fantasy MathTutor, offering interactive experiences and problem-solving guidance. MessengerX.io provides a unique and engaging way for users to connect with AI personalities and explore different scenarios in a chat-based environment.

Role AI Chat is a free AI-powered chat experience that allows users to converse with iconic leaders and characters. With advanced AI technology, users can engage in unlimited conversations without any fees and without the need to log in, ensuring privacy. The platform features a diverse range of characters, including Bobby Axelrod from Billions, Charlie Munger, and Nassim Nicholas Taleb, each offering unique insights and wisdom based on their experiences and expertise.

Google Quantum AI is a leading platform dedicated to advancing the field of quantum computing. The platform offers educational resources, research publications, open-source tools like Cirq, and career opportunities. Google Quantum AI's mission is to build best-in-class quantum computing systems with error correction capabilities, enabling the solution of complex problems that are currently intractable for classical computers. The platform also hosts the XPRIZE Quantum Applications competition, collaborates with industry and academic partners to explore future applications of quantum computing, and shares research and blog posts on quantum algorithms and advancements.

Tableau is a visual analytics platform that helps people see, understand, and act on data. It is used by organizations of all sizes to solve problems, make better decisions, and improve operations. Tableau's platform is intuitive and easy to use, making it accessible to people of all skill levels. It also offers a wide range of features and capabilities, making it a powerful tool for data analysis and visualization.

A.V. Mapping is an all-in-one AI image and music licensing platform that offers music search engine Signals for audio-video matching. It helps solve problems and provides various advantages such as main program uploads, management pages, product introductions, and more applications. The platform connects music creators with the film industry, offering features like AI-powered music and sound matching, film scoring battles led by AI, and secure music licensing contracts on Web 3.0.

Design Sparks is an AI-powered tool that aims to enhance the design process by generating infinite ideas and fostering limitless creativity. Users can input their design problems or themes, upload PDFs or enter URLs, and let the AI generate sparks of inspiration. The platform allows users to explore new perspectives and possibilities for their design projects, making the creative process more efficient and innovative.

AI Diary is a web-based platform that combines the traditional concept of a personal diary with the power of artificial intelligence (AI). It offers a unique and interactive experience where users can engage in conversations with an AI model, express their thoughts and emotions, and receive personalized insights and guidance. AI Diary is designed to enhance self-reflection, promote emotional well-being, and support personal growth. With its user-friendly interface and advanced AI capabilities, AI Diary empowers users to explore their inner selves, set and achieve goals, and unleash their creativity.

Garden of AI is a comprehensive AI-powered platform that provides a wide range of tools and resources to help users explore, learn, and apply AI in their daily lives and work. With a vast collection of AI models, tutorials, datasets, and community forums, Garden of AI empowers users to stay up-to-date with the latest AI advancements and leverage its capabilities to solve real-world problems.

Bethge Lab is an AI research group at the University of Tübingen focusing on Neuro AI - Autonomous Lifelong Learning in Machines and Brains. They develop machine learning tools for neural data analysis and draw inspiration from the brain to address key problems in machine learning. Their research includes representation learning, probabilistic inference, generative modeling, behavioral data analysis, and neural data analysis. Additionally, they explore AI sciencepreneurship and collaborate with startups. Bethge Lab aims to advance the understanding of autonomous learning and develop economically feasible solutions for long-term human needs.

SoraPrompting is a website that provides a collection of prompts to help users get started with Sora prompting and create high-quality video content. The website also includes a form for users to submit their own prompts, which can then be reviewed and added to the collection for the community to explore and create videos from. Sora is OpenAI's revolutionary text-to-video model, designed to understand and simulate the physical world in motion. It aims to assist in solving real-world problems through dynamic interaction. Sora stands out by generating high-quality videos up to a minute long while maintaining visual excellence and adhering to user prompts. Its unique capabilities make it a game-changer in the AI landscape.

Eververse is an open source product management platform that provides a simple alternative to tools like Productboard and Cycle. It allows product teams to collaborate on exploring problems, ideating solutions, prioritizing features, and planning roadmaps with the assistance of AI.

STILL is an open-source project exploring slow-thinking reasoning systems, focusing on o1-like reasoning systems. The project has released technical reports on enhancing LLM reasoning with reward-guided tree search algorithms and implementing slow-thinking reasoning systems using an imitate, explore, and self-improve framework. The project aims to replicate the capabilities of industry-level reasoning systems by fine-tuning reasoning models with long-form thought data and iteratively refining training datasets.

InstructGraph is a framework designed to enhance large language models (LLMs) for graph-centric tasks by utilizing graph instruction tuning and preference alignment. The tool collects and decomposes 29 standard graph datasets into four groups, enabling LLMs to better understand and generate graph data. It introduces a structured format verbalizer to transform graph data into a code-like format, facilitating code understanding and generation. Additionally, it addresses hallucination problems in graph reasoning and generation through direct preference optimization (DPO). The tool aims to bridge the gap between textual LLMs and graph data, offering a comprehensive solution for graph-related tasks.

A web application to explore the capabilities of Google Maps Platform Route Optimization (GMPRO) for solving vehicle routing problems. Users can interact with the GMPRO data model through forms, tables, and maps to construct scenarios, tune constraints, and visualize routes. The application is intended for exploration purposes only and should not be deployed in production. Users are responsible for billing related to cloud resources and API usage. It is important to understand the pricing models for Maps Platform and Route Optimization before using the application.

The Enterprise Azure OpenAI Hub is a comprehensive repository designed to guide users through the world of Generative AI on the Azure platform. It offers a structured learning experience to accelerate the transition from concept to production in an Enterprise context. The hub empowers users to explore various use cases with Azure services, ensuring security and compliance. It provides real-world examples and playbooks for practical insights into solving complex problems and developing cutting-edge AI solutions. The repository also serves as a library of proven patterns, aligning with industry standards and promoting best practices for secure and compliant AI development.

Phoenix is a tool that provides MLOps and LLMOps insights at lightning speed with zero-config observability. It offers a notebook-first experience for monitoring models and LLM Applications by providing LLM Traces, LLM Evals, Embedding Analysis, RAG Analysis, and Structured Data Analysis. Users can trace through the execution of LLM Applications, evaluate generative models, explore embedding point-clouds, visualize generative application's search and retrieval process, and statistically analyze structured data. Phoenix is designed to help users troubleshoot problems related to retrieval, tool execution, relevance, toxicity, drift, and performance degradation.

HuatuoGPT-o1 is a medical language model designed for advanced medical reasoning. It can identify mistakes, explore alternative strategies, and refine answers. The model leverages verifiable medical problems and a specialized medical verifier to guide complex reasoning trajectories and enhance reasoning through reinforcement learning. The repository provides access to models, data, and code for HuatuoGPT-o1, allowing users to deploy the model for medical reasoning tasks.

A web application to explore the capabilities of Google Maps Platform Route Optimization (GMPRO). It helps users understand the data model and functions of the API by presenting interactive forms, tables, and maps. The tool is intended for exploratory use only and should not be deployed in production. Users can construct scenarios, tune constraint parameters, and visualize routes before implementing their own solutions for integrating Route Optimization into their business processes. The application incurs charges related to cloud resources and API usage, and users should be cautious about generating high usage volumes, especially for large scenarios.

LF AI & Data Landscape is a map to explore open source projects in the AI & Data domains, highlighting companies that are members of LF AI & Data. It showcases members of the Foundation and is modelled after the Cloud Native Computing Foundation landscape. The landscape includes current version, interactive version, new entries, logos, proper SVGs, corrections, external data, best practices badge, non-updated items, license, formats, installation, vulnerability reporting, and adjusting the landscape view.

The Smart Connections Visualizer Plugin is a tool designed to enhance note-taking and information visualization by creating dynamic force-directed graphs that represent connections between notes or excerpts. Users can customize visualization settings, preview notes, and interact with the graph to explore relationships and insights within their notes. The plugin aims to revolutionize communication with AI and improve decision-making processes by visualizing complex information in a more intuitive and context-driven manner.

Qlib is an open-source, AI-oriented quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It covers the entire chain of quantitative investment, from alpha seeking to order execution. The platform empowers researchers to explore ideas and implement productions using AI technologies in quantitative investment. Qlib collaboratively solves key challenges in quantitative investment by releasing state-of-the-art research works in various paradigms. It provides a full ML pipeline for data processing, model training, and back-testing, enabling users to perform tasks such as forecasting market patterns, adapting to market dynamics, and modeling continuous investment decisions.

MathVerse is an all-around visual math benchmark designed to evaluate the capabilities of Multi-modal Large Language Models (MLLMs) in visual math problem-solving. It collects high-quality math problems with diagrams to assess how well MLLMs can understand visual diagrams for mathematical reasoning. The benchmark includes 2,612 problems transformed into six versions each, contributing to 15K test samples. It also introduces a Chain-of-Thought (CoT) Evaluation strategy for fine-grained assessment of output answers.

OpenSSA is an open-source framework for creating efficient, domain-specific AI agents. It enables the development of Small Specialist Agents (SSAs) that solve complex problems in specific domains. SSAs tackle multi-step problems that require planning and reasoning beyond traditional language models. They apply OODA for deliberative reasoning (OODAR) and iterative, hierarchical task planning (HTP). This "System-2 Intelligence" breaks down complex tasks into manageable steps. SSAs make informed decisions based on domain-specific knowledge. With OpenSSA, users can create agents that process, generate, and reason about information, making them more effective and efficient in solving real-world challenges.

This project implements a web API that offers a unified interface to Google Gemini and Claude 3. It provides a self-hosted, lightweight, and scalable solution for accessing these AI models through a streaming API. The API supports both Claude and Gemini models, allowing users to interact with them in real-time. The project includes a user-friendly web UI for configuration and documentation, making it easy to get started and explore the capabilities of the API.

The Bard API is a Python package that returns responses from Google Bard through the value of a cookie. It is an unofficial API that operates through reverse-engineering, utilizing cookie values to interact with Google Bard for users struggling with frequent authentication problems or unable to authenticate via Google Authentication. The Bard API is not a free service, but rather a tool provided to assist developers with testing certain functionalities due to the delayed development and release of Google Bard's API. It has been designed with a lightweight structure that can easily adapt to the emergence of an official API. Therefore, using it for any other purposes is strongly discouraged. If you have access to a reliable official PaLM-2 API or Google Generative AI API, replace the provided response with the corresponding official code. Check out https://github.com/dsdanielpark/Bard-API/issues/262.

The On-board Artificial Intelligence Research (OnAIR) Platform is a framework that enables AI algorithms written in Python to interact with NASA's cFS. It is intended to explore research concepts in autonomous operations in a simulated environment. The platform provides tools for generating environments, handling telemetry data through Redis, running unit tests, and contributing to the repository. Users can set up a conda environment, configure telemetry and Redis examples, run simulations, and conduct unit tests to ensure the functionality of their AI algorithms. The platform also includes guidelines for licensing, copyright, and contributions to the repository.

The edge2ai-workshop repository provides a hands-on workshop for building an IoT Predictive Maintenance workflow. It includes lab exercises for setting up components like NiFi, Streams Processing, Data Visualization, and more on a single host. The repository also covers use cases such as credit card fraud detection. Users can follow detailed instructions, prerequisites, and connectivity guidelines to connect to their cluster and explore various services. Additionally, troubleshooting tips are provided for common issues like MiNiFi not sending messages or CEM not picking up new NARs.

Welcome to 'Top AI Directories', a curated compilation of AI tool directories designed to simplify the process of discovering and submitting AI products. Whether you're an AI developer or a product team, this resource is your one-stop destination to explore a variety of directories that can help boost the visibility of your AI innovations. Join us in fostering collaboration and recognition within the AI community by leveraging this comprehensive list.

**deep** doctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated framework for fine-tuning, evaluating and running models. For more specific text processing tasks use one of the many other great NLP libraries. **deep** doctection focuses on applications and is made for those who want to solve real world problems related to document extraction from PDFs or scans in various image formats. **deep** doctection provides model wrappers of supported libraries for various tasks to be integrated into pipelines. Its core function does not depend on any specific deep learning library. Selected models for the following tasks are currently supported: * Document layout analysis including table recognition in Tensorflow with **Tensorpack**, or PyTorch with **Detectron2**, * OCR with support of **Tesseract**, **DocTr** (Tensorflow and PyTorch implementations available) and a wrapper to an API for a commercial solution, * Text mining for native PDFs with **pdfplumber**, * Language detection with **fastText**, * Deskewing and rotating images with **jdeskew**. * Document and token classification with all LayoutLM models provided by the **Transformer library**. (Yes, you can use any LayoutLM-model with any of the provided OCR-or pdfplumber tools straight away!). * Table detection and table structure recognition with **table-transformer**. * There is a small dataset for token classification available and a lot of new tutorials to show, how to train and evaluate this dataset using LayoutLMv1, LayoutLMv2, LayoutXLM and LayoutLMv3. * Comprehensive configuration of **analyzer** like choosing different models, output parsing, OCR selection. Check this notebook or the docs for more infos. * Document layout analysis and table recognition now runs with **Torchscript** (CPU) as well and **Detectron2** is not required anymore for basic inference. * [**new**] More angle predictors for determining the rotation of a document based on **Tesseract** and **DocTr** (not contained in the built-in Analyzer). * [**new**] Token classification with **LiLT** via **transformers**. We have added a model wrapper for token classification with LiLT and added a some LiLT models to the model catalog that seem to look promising, especially if you want to train a model on non-english data. The training script for LayoutLM can be used for LiLT as well and we will be providing a notebook on how to train a model on a custom dataset soon. **deep** doctection provides on top of that methods for pre-processing inputs to models like cropping or resizing and to post-process results, like validating duplicate outputs, relating words to detected layout segments or ordering words into contiguous text. You will get an output in JSON format that you can customize even further by yourself. Have a look at the **introduction notebook** in the notebook repo for an easy start. Check the **release notes** for recent updates. **deep** doctection or its support libraries provide pre-trained models that are in most of the cases available at the **Hugging Face Model Hub** or that will be automatically downloaded once requested. For instance, you can find pre-trained object detection models from the Tensorpack or Detectron2 framework for coarse layout analysis, table cell detection and table recognition. Training is a substantial part to get pipelines ready on some specific domain, let it be document layout analysis, document classification or NER. **deep** doctection provides training scripts for models that are based on trainers developed from the library that hosts the model code. Moreover, **deep** doctection hosts code to some well established datasets like **Publaynet** that makes it easy to experiment. It also contains mappings from widely used data formats like COCO and it has a dataset framework (akin to **datasets** so that setting up training on a custom dataset becomes very easy. **This notebook** shows you how to do this. **deep** doctection comes equipped with a framework that allows you to evaluate predictions of a single or multiple models in a pipeline against some ground truth. Check again **here** how it is done. Having set up a pipeline it takes you a few lines of code to instantiate the pipeline and after a for loop all pages will be processed through the pipeline.

ScaleLLM is a cutting-edge inference system engineered for large language models (LLMs), meticulously designed to meet the demands of production environments. It extends its support to a wide range of popular open-source models, including Llama3, Gemma, Bloom, GPT-NeoX, and more. ScaleLLM is currently undergoing active development. We are fully committed to consistently enhancing its efficiency while also incorporating additional features. Feel free to explore our **_Roadmap_** for more details. ## Key Features * High Efficiency: Excels in high-performance LLM inference, leveraging state-of-the-art techniques and technologies like Flash Attention, Paged Attention, Continuous batching, and more. * Tensor Parallelism: Utilizes tensor parallelism for efficient model execution. * OpenAI-compatible API: An efficient golang rest api server that compatible with OpenAI. * Huggingface models: Seamless integration with most popular HF models, supporting safetensors. * Customizable: Offers flexibility for customization to meet your specific needs, and provides an easy way to add new models. * Production Ready: Engineered with production environments in mind, ScaleLLM is equipped with robust system monitoring and management features to ensure a seamless deployment experience.

Tell me your problems, be they large or small. Let's explore what's currently working around the world... and how our shining future could unfold.

Solution-focused, cognitive-behavioral, and transformational coaching to explore yourself, including journalling support.

I'm a fluid mechanics tutor, ready to explain concepts and guide you through problems!

Comprehensive quantum physics and cosmology exploration tool with simulations, problem-solving, and interactive learning.

Guides in exploring Integral Theory perspectives.

解答数理逻辑问题的专家

Multilingual adventures with visuals

Dieses GPT hilft Studierenden, physikalische Konzepte besser zu verstehen und zu erlernen. Es bietet detaillierte Erklärungen, Beispiele und interaktive Übungen zu verschiedenen Physikthemen.

🖼️ See into another world through a mirror

Questions based on keyword

Guide in OH card exploration and self-discovery.

A friendly geometry tutor for middle school students, providing answers and short tutorials.

Tutor de Cálculo Vectorial con enfoque personalizado y recursos interactivos.

I guide you with Artistic Expression for Self-Eploration

Mimics a therapist's conversational style

Friendly GPT for applying book concepts practically

Explor any math concept interactively to gain an understanding. Just type the topic!

A versatile AI assistant for information, problem-solving, and exploration.

Unleash the power of AI with Troubadour: Instantly turning your curiosity into captivating, crystal-clear answers – your gateway to the future of knowledge!

Empathetic companion for self-exploration