Best AI tools for< Analyze Space Data >

Monitr is a data visualization and analytics platform that allows users to query, visualize, and share data in one place. It helps in tracking key metrics, making data-driven decisions, and breaking down data silos to provide a unified view of data from various sources. Users can create charts and dashboards, connect to different data sources like Postgresql and MySQL, and collaborate with teammates on SQL queries. Monitr's AI features are powered by Meta AI's Llama 3 LLM, enabling the development of powerful and flexible analytics tools for maximizing data utilization.

TimeComplexity.ai is an AI tool that helps users analyze the runtime complexity of their code. It works seamlessly across different programming languages without the need for headers, imports, or a main statement. Users can simply input their code and get insights into its performance. However, it is important to note that the results provided by TimeComplexity.ai may not always be accurate, so users are advised to use the tool at their own risk.

Allwork.Space is an online platform that provides resources and information on the future of work. It covers topics such as artificial intelligence, remote work, coworking, and workplace design. The website also features a marketplace where users can find office space and remote jobs.

JudgeAI is an AI tool designed to assist users in making judgments or decisions. It utilizes artificial intelligence algorithms to analyze data and provide insights. The tool helps users in evaluating information and reaching conclusions based on the input data. JudgeAI aims to streamline decision-making processes and enhance accuracy by leveraging AI technology.

Derwen is an open-source integration platform for production machine learning in enterprise, specializing in natural language processing, graph technologies, and decision support. It offers expertise in developing knowledge graph applications and domain-specific authoring. Derwen collaborates closely with Hugging Face and provides strong data privacy guarantees, low carbon footprint, and no cloud vendor involvement. The platform aims to empower AI engineers and domain experts with quality, time-to-value, and ownership since 2017.

CEBRA is a machine-learning method that compresses time series data to reveal hidden structures in the variability of the data. It excels in analyzing behavioral and neural data simultaneously, allowing for the decoding of activity from the visual cortex of the mouse brain to reconstruct viewed videos. CEBRA is a novel encoding method that leverages both behavioral and neural data to produce consistent and high-performance latent spaces, enabling the mapping of space, uncovering complex kinematic features, and providing rapid, high-accuracy decoding of natural movies from the visual cortex.

GPT Workspace is an AI tool that integrates ChatGPT and Gemini directly into Google Workspace applications such as Docs, Sheets, Slides, Drive, and Gmail. It enhances productivity by providing features like categorizing, summarizing, generating content, suggesting improvements, and crafting marketing narratives. With a focus on privacy and user control, GPT Workspace offers a seamless and efficient AI-powered experience for various tasks within Google Workspace.

BuildAI.Space is an AI application that allows users to create personalized AI tools without the need for technical skills. Users can design and customize their own AI apps, including nutrition tools like meal planners and calculators. The platform offers the ability to monetize apps, analyze user usage, and customize tools to match specific business needs. With a focus on user personalization and ease of use, BuildAI.Space empowers users to leverage the power of AI in creating unique and tailored experiences for their audience.

Open Data Science (ODS) is a community website offering a platform for data science enthusiasts to engage in tracks, competitions, hacks, tasks, events, and projects. The website serves as a hub for job opportunities and provides a space for privacy policy, service agreements, and public offers. ODS.AI, established in 2015, focuses on various data science topics such as machine learning, computer vision, natural language processing, and more. The platform hosts online and offline events, conferences, and educational courses to foster learning and networking within the data science community.

The Institute of Computer Science at the University of Würzburg is a leading research and teaching institution in the field of computer science. With 29 professors and around 200 employees, the institute offers a wide range of study programs, including bachelor's, master's, and teaching degrees. The institute's research focuses on four main areas: Computing, Systems and Networks; Artificial Intelligence and Data Science; Human-Centered Computing; and Aerospace and Robotics.

Analytics India Magazine is a leading publication covering the latest advancements in artificial intelligence, data science, and machine learning. The website provides in-depth analysis, interviews with industry experts, and insights into the impact of AI on various sectors. It also hosts events and conferences that bring together professionals and thought leaders in the field.

MindPal is an AI application that empowers users to build their AI workforce to automate tasks and workflows. It offers a wide range of features to streamline processes and enhance productivity. Users can create specialized AI agents, train them with their own data, and connect them to various tools. MindPal is recommended by professionals for its efficiency in automating tasks and generating valuable insights.

FoodIntake is an AI-powered food tracking app that helps users make healthier food choices. It features a large database of branded foods, AI food analysis, and personalized nutrition recommendations. The app is easy to use and provides users with a comprehensive view of their diet, including calorie and nutrient intake, macronutrient distribution, and food processing levels.

Oncora Medical is a healthcare technology company that provides software and data solutions to oncologists and cancer centers. Their products are designed to improve patient care, reduce clinician burnout, and accelerate clinical discoveries. Oncora's flagship product, Oncora Patient Care, is a modern, intelligent user interface for oncologists that simplifies workflow, reduces documentation burden, and optimizes treatment decision making. Oncora Analytics is an adaptive visual and backend software platform for regulatory-grade real world data analytics. Oncora Registry is a platform to capture and report quality data, treatment data, and outcomes data in the oncology space.

TradeBX is an AI-powered trading platform that provides advanced AI algorithms, an inbuilt training course, and a user-friendly interface. Its AI algorithms analyze vast amounts of data in real-time to identify profitable opportunities and execute trades with precision. The platform also offers a training course to help users leverage the bot's advanced features and strategies. With 24/7 trading and a user-friendly interface, TradeBX empowers traders of all levels to achieve their financial goals.

Artificial Intelligence + is a comprehensive platform focusing on AI, Robotics, and IoT. It covers a wide range of topics related to artificial intelligence, including the dangers, impacts, and advancements in the field. The platform also delves into robotics, space exploration, and the intersection of AI with various industries. With a mix of articles, blogs, and expert insights, Artificial Intelligence + serves as a valuable resource for individuals interested in staying updated on the latest trends and developments in the AI landscape.

Laika AI is the world's first Web3-modeled AI ecosystem, designed and optimized for Web3 and blockchain. It offers advanced on-chain AI tools, integrating artificial intelligence and blockchain data to provide users with insights into the crypto landscape. Laika AI stands out with its user-friendly browser extension that empowers users with advanced on-chain analytics without the need for complex setups. The platform continuously learns and improves, leveraging a unique foundation and proprietary algorithms dedicated to Web3. Laika AI offers features such as DeFi research, token contract analysis, wallet insights, AI alerts, and multichain swap capabilities. It is supported by strategic partnerships with leading companies in the Web3 and Web2 space, ensuring security, high performance, and accessibility for users.

Cartesia Sonic Team Blog Research Playground is an AI application that offers real-time multimodal intelligence for every device. The application aims to build the next generation of AI by providing ubiquitous, interactive intelligence that can run on any device. It features the fastest, ultra-realistic generative voice API and is backed by research on simple linear attention language models and state-space models. The founding team, who met at the Stanford AI Lab, has invented State Space Models (SSMs) and scaled it up to achieve state-of-the-art results in various modalities such as text, audio, video, images, and time-series data.

LiberalAI is a cutting-edge decentralized AI platform and network that empowers users to access advanced AI capabilities in a secure and transparent manner. By leveraging blockchain technology, LiberalAI ensures data privacy and integrity while enabling seamless collaboration and innovation in the AI space. The platform offers a wide range of AI tools and services, making it a one-stop solution for individuals and businesses looking to harness the power of artificial intelligence for various applications.

Techstrong.ai is an AI-focused website that covers a wide range of topics related to artificial intelligence, including AI at the Edge, AI Careers, Conversational AI, Cybersecurity AI, Data Engineering, Data Science, and more. The site provides the latest articles, news, videos, and related sites within the Techstrong Group. It offers insights into various industries such as Aerospace, Energy, Financial Services, Health Care, Retail, Telecommunications, and Transportation/Travel. Techstrong.ai aims to keep its audience informed about the latest developments and trends in the AI space.

A curated list of Generative AI projects, tools, artworks, and models

ChatGPT is a large language model that can generate human-like text, translate languages, write different kinds of creative content, and answer your questions in a conversational way. It is trained on a massive amount of text data, and it is able to understand and respond to a wide range of natural language prompts. Here are 5 jobs suitable for this tool, in lowercase letters: 1. content writer 2. chatbot assistant 3. language translator 4. creative writer 5. researcher

Trinity is an Explainable AI (XAI) Analysis and Visualization tool designed for Deep Learning systems or other models performing complex classification or decoding. It provides performance analysis through interactive 3D projections that are hyper-dimensional aware, allowing users to explore hyperspace, hypersurface, projections, and manifolds. Trinity primarily works with JSON data formats and supports the visualization of FeatureVector objects. Users can analyze and visualize data points, correlate inputs with classification results, and create custom color maps for better data interpretation. Trinity has been successfully applied to various use cases including Deep Learning Object detection models, COVID gene/tissue classification, Brain Computer Interface decoders, and Large Language Model (ChatGPT) Embeddings Analysis.

ExplainableAI.jl is a Julia package that implements interpretability methods for black-box classifiers, focusing on local explanations and attribution maps in input space. The package requires models to be differentiable with Zygote.jl. It is similar to Captum and Zennit for PyTorch and iNNvestigate for Keras models. Users can analyze and visualize explanations for model predictions, with support for different XAI methods and customization. The package aims to provide transparency and insights into model decision-making processes, making it a valuable tool for understanding and validating machine learning models.

EDA GPT is an open-source data analysis companion that offers a comprehensive solution for structured and unstructured data analysis. It streamlines the data analysis process, empowering users to explore, visualize, and gain insights from their data. EDA GPT supports analyzing structured data in various formats like CSV, XLSX, and SQLite, generating graphs, and conducting in-depth analysis of unstructured data such as PDFs and images. It provides a user-friendly interface, powerful features, and capabilities like comparing performance with other tools, analyzing large language models, multimodal search, data cleaning, and editing. The tool is optimized for maximal parallel processing, searching internet and documents, and creating analysis reports from structured and unstructured data.

This repository contains a collection of AI projects covering various areas of machine learning. Each project is accompanied by detailed articles on the associated blog sciblog. Projects range from introductory topics like Convolutional Neural Networks and Transfer Learning to advanced topics like Fraud Detection and Recommendation Systems. The repository also includes tutorials on data generation, distributed training, natural language processing, and time series forecasting. Additionally, it features visualization projects such as football match visualization using Datashader.

Awesome AI Tools is a curated list of popular tools and resources for artificial intelligence enthusiasts. It includes a wide range of tools such as machine learning libraries, deep learning frameworks, data visualization tools, and natural language processing resources. Whether you are a beginner or an experienced AI practitioner, this repository aims to provide you with a comprehensive collection of tools to enhance your AI projects and research. Explore the list to discover new tools, stay updated with the latest advancements in AI technology, and find the right resources to support your AI endeavors.

Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

Synmetrix is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube.js to consolidate metrics from various sources and distribute them downstream via a SQL API. Use cases include data democratization, business intelligence and reporting, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

ERAG is an advanced system that combines lexical, semantic, text, and knowledge graph searches with conversation context to provide accurate and contextually relevant responses. This tool processes various document types, creates embeddings, builds knowledge graphs, and uses this information to answer user queries intelligently. It includes modules for interacting with web content, GitHub repositories, and performing exploratory data analysis using various language models.

This repository provides a hands-on lab for learning about Neo4j and Google Cloud Vertex AI. It is intended for data scientists and data engineers to deploy Neo4j and Vertex AI in a Google Cloud account, work with real-world datasets, apply generative AI, build a chatbot over a knowledge graph, and use vector search and index functionality for semantic search. The lab focuses on analyzing quarterly filings of asset managers with $100m+ assets under management, exploring relationships using Neo4j Browser and Cypher query language, and discussing potential applications in capital markets such as algorithmic trading and securities master data management.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

Deej-A.I. is an advanced machine learning project that aims to revolutionize music recommendation systems by using artificial intelligence to analyze and recommend songs based on their content and characteristics. The project involves scraping playlists from Spotify, creating embeddings of songs, training neural networks to analyze spectrograms, and generating recommendations based on similarities in music features. Deej-A.I. offers a unique approach to music curation, focusing on the 'what' rather than the 'how' of DJing, and providing users with personalized and creative music suggestions.

PyWxDump is a Python tool designed for obtaining WeChat account information, decrypting databases, viewing WeChat chats, and exporting chats as HTML backups. It provides core features such as extracting base address offsets of various WeChat data, decrypting databases, and combining multiple database types for unified viewing. Additionally, it offers extended functions like viewing chat history through the web, exporting chat logs in different formats, and remote viewing of WeChat chat history. The tool also includes document classes for database field descriptions, base address offset methods, and decryption methods for MAC databases. PyWxDump is suitable for network security, daily backup archiving, remote chat history viewing, and more.

Lance is a modern columnar data format optimized for ML workflows and datasets. It offers high-performance random access, vector search, zero-copy automatic versioning, and ecosystem integrations with Apache Arrow, Pandas, Polars, and DuckDB. Lance is designed to address the challenges of the ML development cycle, providing a unified data format for collection, exploration, analytics, feature engineering, training, evaluation, deployment, and monitoring. It aims to reduce data silos and streamline the ML development process.

The 'awesome-AI4MolConformation-MD' repository focuses on protein conformations and molecular dynamics using generative artificial intelligence and deep learning. It provides resources, reviews, datasets, packages, and tools related to AI-driven molecular dynamics simulations. The repository covers a wide range of topics such as neural networks potentials, force fields, AI engines/frameworks, trajectory analysis, visualization tools, and various AI-based models for protein conformational sampling. It serves as a comprehensive guide for researchers and practitioners interested in leveraging AI for studying molecular structures and dynamics.

**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.

This repository is a sample chatbot using the Anthropic company's LLM Claude, one of the foundational models provided by Amazon Bedrock for generative AI. It allows users to have basic conversations with the chatbot, personalize it with their own instructions and external knowledge, and analyze usage for each user/bot on the administrator dashboard. The chatbot supports various languages, including English, Japanese, Korean, Chinese, French, German, and Spanish. Deployment is straightforward and can be done via the command line or by using AWS CDK. The architecture is built on AWS managed services, eliminating the need for infrastructure management and ensuring scalability, reliability, and security.

Algolisted is a pioneering platform dedicated to algorithmic problem-solving, offering a centralized hub for a diverse array of algorithmic challenges. It provides an immersive online environment for programmers to enhance their skills through Data Structures and Algorithms (DSA) sheets, academic progress tracking, resume refinement with OpenAI integration, adaptive testing, and job opportunity listings. The project is built on the MERN stack, Flask, Beautiful Soup, and Selenium,GEN AI, and deployed on Firebase. Algolisted aims to be a reliable companion in the pursuit of coding knowledge and proficiency.

Galactic Insights Pro: Leading the way in space exploration analysis with unmatched expertise and interactive engagement.

Knows the docs and can query official ordinal endpoints—Sat Numbers, Inscription IDs, and more.

Your personal astrophysicist, NDGPT - inspired by Neil deGrasse Tyson.

Adaptive AI for space exploration and exoplanet settlement.

Create orbital simulations with help from APIs.

A guide to the meta-crisis, the liminal web and the theoretical space of metamodernism

Multiple Environment Threat Evaluation of Resources (METEOR)™ Space Threats and Operational Risks to Mission (STORM)™ non-profit product AI co-pilot

Creates engaging social media posts with 3 AI-selected, space-themed images

Provides compliance legal advice for the financial services Ads, comparison, and marketing content space.

Healthcare futurist discussing trends, innovations, and predictions, inspired by space, resilience, and precision medicine.

精通2008版CAD的城市规划师，专注于解决规划问题

I analyze cognitive biases in scenarios and thoughts, providing neutral, educational insights.

Analyze and reverse engineer images. Receive style descriptions and image re-creation prompts.

I'll help you analyze market news and charts for trading/investing

I read and analyze annual reports of companies. Just upload the annual report PDF and start asking me questions!

As a Good Design Advisor, I provide consultation and advice on design topics and analyze designs that are provided through documents or links. I can also generate visual representations myself to illustrate design concepts.

I analyze historical events, offering insights from multiple perspectives.

For strategic knowledge distillation, upload the document you need to analyze and use !start. ENSURE the uploaded file shows DOCUMENT and NOT PDF. This workflow requires leveraging RAG to operate. Only a small amount of PDFs are supported, convert to txt or doc. For timeout, refresh & !continue

Critically analyze SLIs/SLOs with a deeper, provocative approach

Analyze any uploaded art piece, providing thoughtful insight on the history of the piece and its maker. Replicate art pieces in new styles generated by the user. Be an overall expert in art and help users navigate the art scene. Inform them of different types of art