Best AI tools for< Explain Concept >

ExplainThis is an AI-powered assistant that helps you understand the web. It can explain key concepts, summarize content, and provide context without leaving the webpage. With ExplainThis, you can learn and grow while you browse, making your daily browsing more informative and efficient.

BlogImagery is an AI-powered tool that helps you generate unique and visually appealing images for your blog posts. With just a single click, you can create images that are perfectly tailored to your content and style. BlogImagery offers a variety of art styles to choose from, so you can find the perfect look for your blog. You can also use BlogImagery to transform boring walls of text into beautiful articles. Original images have been shown to perform 40% better than stock photos, so using BlogImagery can help you improve your blog's engagement and traffic.

analogenie is an AI-powered analogy generator tool designed to help users create creative analogies and metaphors to enhance their writing. It enables users to explain complex concepts, engage their audience, and improve the impact of their content by providing contextual analogies. The tool generates analogies quickly and easily with just a click, saving time and elevating the quality of writing.

ELI5 is an AI-powered website that simplifies complex topics into easy-to-understand explanations. It uses natural language processing to break down concepts into clear and concise language, making them accessible to people of all ages and backgrounds. ELI5 covers a wide range of subjects, from science and technology to history and culture. It also offers a variety of tools for educators, including lesson plans, discussion questions, and quizzes.

AiVANTA is a scalable AI SaaS solution that offers Integrated Content Automation and Delivery (ICAD) for enterprises, enabling seamless AI video adoption. The platform provides a single-window solution to simplify all AI video needs, reducing video production costs by 80%. AiVANTA features a rich virtual avatar library, managed services for refining AI output, and tailored AI videos for various business needs. Its advantages include cost reduction, multi-lingual content, customization, quick turnaround, and trusted by brands. However, the disadvantages include the need for oversight in managed services, limited customization options, and potential language barriers. The application is suitable for BFSI, Healthcare, E-Commerce, and corporate training. Users can utilize AiVANTA for tasks like creating product information videos, training content, engaging with customers, and producing podcasts and explainer videos.

AI Homework Helper is an innovative platform powered by artificial intelligence technology, designed to assist students with their homework assignments across various subjects. Our AI Homework Helper analyzes students’ homework requirements and generates customized solutions, including step-by-step explanations, relevant examples, and problem-solving strategies. Our platform features a user-friendly interface that makes it easy for students to navigate and access the assistance they need, without any technical hassles.

TheBookSum is an AI-powered tool that provides instant book summaries. It helps users to quickly grasp the core of literature across genres efficiently and deeply. With just a click, users can input the title and author of the book they wish to summarize, and TheBookSum's AI will generate a detailed summary that captures the essence of the book. The summaries are divided into clear segments for easy understanding, and they extract and explain the main concepts and keywords from books, aiding in grasping central themes and terms. TheBookSum is free to use and can summarize a broad spectrum of books, ranging from fiction and non-fiction to technical guides and more.

Squid & Fish Digitals is a platform offering various AI applications and tools for tech-savvy individuals. Among its products are Machine Learning study plans, Frontend Development study plans, Study Curator for generating learning paths, and more. The platform aims to simplify complex concepts and tasks through AI-powered solutions, catering to different educational and professional needs.

ChatDOC is an AI-powered tool that allows users to chat with PDF documents and get instant answers with cited sources. It can summarize long documents, explain complex concepts, and find key information in seconds. ChatDOC is built for professionals and is used by over 500,000 global users.

Chat-docs AI is an innovative AI application that allows users to interact with PDF documents through natural language conversations. The tool leverages advanced artificial intelligence algorithms to summarize long documents, explain complex concepts, and find key information with cited sources in seconds. It transforms PDFs into intelligent entities capable of dialogue, making learning, research, and analysis more interactive and personalized. Chat-docs AI is designed to be intuitive, secure, and accessible to users from various backgrounds, revolutionizing the way individuals engage with textual content.

AI Does Your Homework is an innovative AI tool designed to assist students with their homework assignments. The tool utilizes advanced artificial intelligence algorithms to provide accurate solutions to a wide range of academic questions and problems. Students can simply input their questions into the tool, and it will generate step-by-step solutions, explanations, and answers in real-time. AI Does Your Homework aims to streamline the learning process, enhance understanding of complex topics, and improve academic performance.

Domyhomework.online is an AI-powered homework help website that offers instant solutions to students' questions in over 30 subjects. With its advanced AI technology, students can simply upload a photo of their homework or type in their question, and the website will provide a detailed step-by-step solution within 2 minutes. Domyhomework.online also offers personalized learning support, adapting to each student's individual needs and learning style. The website is available in over 20 languages, making it accessible to students from all over the world.

The website offers online tutoring services with the help of artificial intelligence in various languages such as German, English, Croatian, Polish, Turkish, Ukrainian, and Arabic. It provides personalized tutoring sessions, homework assistance, and explanations for a wide range of school subjects. The AI tool supports self-directed learning by adapting to the user's school level and learning progress. Users can receive help in over 30 school subjects, including math, geography, history, biology, chemistry, and more. The platform allows users to upload homework assignments, receive detailed explanations, and interact with AI tutors through chat sessions.

Question AI is a free AI homework helper designed to assist students with their homework assignments. The tool utilizes artificial intelligence to provide accurate and reliable answers to a wide range of academic questions. Students can simply input their homework questions into the tool, and it will generate step-by-step solutions to help them understand the concepts better. With Question AI, students can improve their learning outcomes and enhance their academic performance.

SciSpace is an AI-powered tool that helps researchers understand research papers better. It can explain and elaborate most academic texts in simple words. It is a great tool for students, researchers, and anyone who wants to learn more about a particular topic. SciSpace has a user-friendly interface and is easy to use. Simply upload a research paper or enter a URL, and SciSpace will do the rest. It will highlight key concepts, provide definitions, and generate a summary of the paper. SciSpace can also be used to generate citations and find related papers.

Explainpaper is an AI-powered tool designed to simplify and explain complex research papers. Users can upload a paper, highlight confusing text, and receive explanations to make the content easier to understand. The tool leverages AI and machine learning models to break down dense sections and clarify intricate concepts, ultimately making research papers more accessible to a wider audience. It is a valuable resource for researchers, students, and anyone looking to delve into complex topics with confidence.

AskDocs is an AI-powered document assistant designed to help users read faster and create better work content. It offers cross-document analysis, quick answers linked to documents, one-click summaries of key concepts, and the ability to understand confusing information. With a focus on enhancing productivity, AskDocs is trusted by students, knowledge workers, and small businesses to streamline research, meeting notes, emails, and more. The tool supports various document types and provides instant answers directly linked to sources within the uploaded documents.

BLUF is an AI-powered web page assistant that provides concise answers, summaries, and explanations of web pages. It helps users to quickly and easily get the information they need from any web page, without having to read through irrelevant or unnecessary content. BLUF is available as a browser extension for Chrome and Firefox, and it can be used to summarize or explain any web page with a single click.

Lingolette is an AI language teaching machine that helps users master a language faster through personalized neural network chat-based tools. It speaks with users like a real teacher, motivates them on their learning journey, adapts to their learning style, and explains concepts clearly. Lingolette aims to enhance users' talking skills, pronunciation, and overall language learning experience.

This tool uses AI to explain any piece of code you don't understand. Simply paste the code in the code editor and press "Explain Code" and AI will output a paragraph explaining what the code is doing.

AlwaysReddy is a simple LLM assistant with no UI that you interact with entirely using hotkeys. It can easily read from or write to your clipboard, and voice chat with you via TTS and STT. Here are some of the things you can use AlwaysReddy for: - Explain a new concept to AlwaysReddy and have it save the concept (in roughly your words) into a note. - Ask AlwaysReddy "What is X called?" when you know how to roughly describe something but can't remember what it is called. - Have AlwaysReddy proofread the text in your clipboard before you send it. - Ask AlwaysReddy "From the comments in my clipboard, what do the r/LocalLLaMA users think of X?" - Quickly list what you have done today and get AlwaysReddy to write a journal entry to your clipboard before you shutdown the computer for the day.

A sleek and powerful macOS client for Amazon Bedrock, bringing AI models to your desktop. It provides seamless interaction with multiple Amazon Bedrock models, real-time chat interface, easy model switching, support for various AI tasks, and native Dark Mode support. Built with SwiftUI for optimal performance and modern UI.

This course has 18 lessons. Each lesson covers its own topic so start wherever you like! Lessons are labeled either "Learn" lessons explaining a Generative AI concept or "Build" lessons that explain a concept and code examples in both **Python** and **TypeScript** when possible. Each lesson also includes a "Keep Learning" section with additional learning tools. **What You Need** * Access to the Azure OpenAI Service **OR** OpenAI API - _Only required to complete coding lessons_ * Basic knowledge of Python or Typescript is helpful - *For absolute beginners check out these Python and TypeScript courses. * A Github account to fork this entire repo to your own GitHub account We have created a **Course Setup** lesson to help you with setting up your development environment. Don't forget to star (🌟) this repo to find it easier later. ## 🧠 Ready to Deploy? If you are looking for more advanced code samples, check out our collection of Generative AI Code Samples in both **Python** and **TypeScript**. ## 🗣️ Meet Other Learners, Get Support Join our official AI Discord server to meet and network with other learners taking this course and get support. ## 🚀 Building a Startup? Sign up for Microsoft for Startups Founders Hub to receive **free OpenAI credits** and up to **$150k towards Azure credits to access OpenAI models through Azure OpenAI Services**. ## 🙏 Want to help? Do you have suggestions or found spelling or code errors? Raise an issue or Create a pull request ## 📂 Each lesson includes: * A short video introduction to the topic * A written lesson located in the README * Python and TypeScript code samples supporting Azure OpenAI and OpenAI API * Links to extra resources to continue your learning ## 🗃️ Lessons | | Lesson Link | Description | Additional Learning | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 00 | Course Setup | **Learn:** How to Setup Your Development Environment | Learn More | | 01 | Introduction to Generative AI and LLMs | **Learn:** Understanding what Generative AI is and how Large Language Models (LLMs) work. | Learn More | | 02 | Exploring and comparing different LLMs | **Learn:** How to select the right model for your use case | Learn More | | 03 | Using Generative AI Responsibly | **Learn:** How to build Generative AI Applications responsibly | Learn More | | 04 | Understanding Prompt Engineering Fundamentals | **Learn:** Hands-on Prompt Engineering Best Practices | Learn More | | 05 | Creating Advanced Prompts | **Learn:** How to apply prompt engineering techniques that improve the outcome of your prompts. | Learn More | | 06 | Building Text Generation Applications | **Build:** A text generation app using Azure OpenAI | Learn More | | 07 | Building Chat Applications | **Build:** Techniques for efficiently building and integrating chat applications. | Learn More | | 08 | Building Search Apps Vector Databases | **Build:** A search application that uses Embeddings to search for data. | Learn More | | 09 | Building Image Generation Applications | **Build:** A image generation application | Learn More | | 10 | Building Low Code AI Applications | **Build:** A Generative AI application using Low Code tools | Learn More | | 11 | Integrating External Applications with Function Calling | **Build:** What is function calling and its use cases for applications | Learn More | | 12 | Designing UX for AI Applications | **Learn:** How to apply UX design principles when developing Generative AI Applications | Learn More | | 13 | Securing Your Generative AI Applications | **Learn:** The threats and risks to AI systems and methods to secure these systems. | Learn More | | 14 | The Generative AI Application Lifecycle | **Learn:** The tools and metrics to manage the LLM Lifecycle and LLMOps | Learn More | | 15 | Retrieval Augmented Generation (RAG) and Vector Databases | **Build:** An application using a RAG Framework to retrieve embeddings from a Vector Databases | Learn More | | 16 | Open Source Models and Hugging Face | **Build:** An application using open source models available on Hugging Face | Learn More | | 17 | AI Agents | **Build:** An application using an AI Agent Framework | Learn More | | 18 | Fine-Tuning LLMs | **Learn:** The what, why and how of fine-tuning LLMs | Learn More |

This repository provides a deployment guide for utilizing Google Cloud's Generative AI tools in marketing scenarios. It includes step-by-step instructions, examples of crafting marketing materials, and supplementary Jupyter notebooks. The demos cover marketing insights, audience analysis, trendspotting, content search, content generation, and workspace integration. Users can access and visualize marketing data, analyze trends, improve search experience, and generate compelling content. The repository structure includes backend APIs, frontend code, sample notebooks, templates, and installation scripts.

Vespa documentation is served using GitHub Project pages with Jekyll. To edit documentation, check out and work off the master branch in this repository. Documentation is written in HTML or Markdown. Use a single Jekyll template _layouts/default.html to add header, footer and layout. Install bundler, then $ bundle install $ bundle exec jekyll serve --incremental --drafts --trace to set up a local server at localhost:4000 to see the pages as they will look when served. If you get strange errors on bundle install try $ export PATH=“/usr/local/opt/[email protected]/bin:$PATH” $ export LDFLAGS=“-L/usr/local/opt/[email protected]/lib” $ export CPPFLAGS=“-I/usr/local/opt/[email protected]/include” $ export PKG_CONFIG_PATH=“/usr/local/opt/[email protected]/lib/pkgconfig” The output will highlight rendering/other problems when starting serving. Alternatively, use the docker image `jekyll/jekyll` to run the local server on Mac $ docker run -ti --rm --name doc \ --publish 4000:4000 -e JEKYLL_UID=$UID -v $(pwd):/srv/jekyll \ jekyll/jekyll jekyll serve or RHEL 8 $ podman run -it --rm --name doc -p 4000:4000 -e JEKYLL_ROOTLESS=true \ -v "$PWD":/srv/jekyll:Z docker.io/jekyll/jekyll jekyll serve The layout is written in denali.design, see _layouts/default.html for usage. Please do not add custom style sheets, as it is harder to maintain.

Nerority's Advanced GPT Suite is a collection of 33 GPTs that can be controlled with natural language prompts. The suite includes tools for various tasks such as strategic consulting, business analysis, career profile building, content creation, educational purposes, image-based tasks, knowledge engineering, marketing, persona creation, programming, prompt engineering, role-playing, simulations, and task management. Users can access links, usage instructions, and guides for each GPT on their respective pages. The suite is designed for public demonstration and usage, offering features like meta-sequence optimization, AI priming, prompt classification, and optimization. It also provides tools for generating articles, analyzing contracts, visualizing data, distilling knowledge, creating educational content, exploring topics, generating marketing copy, simulating scenarios, managing tasks, and more.

Lightning Lab is a public template for artificial intelligence and machine learning research projects using Lightning AI's PyTorch Lightning. It provides a structured project layout with modules for command line interface, experiment utilities, Lightning Module and Trainer, data acquisition and preprocessing, model serving APIs, project configurations, training checkpoints, technical documentation, logs, notebooks for data analysis, requirements management, testing, and packaging. The template simplifies the setup of deep learning projects and offers extras for different domains like vision, text, audio, reinforcement learning, and forecasting.

The Aleph Alpha Intelligence Layer️ offers a comprehensive suite of development tools for crafting solutions that harness the capabilities of large language models (LLMs). With a unified framework for LLM-based workflows, it facilitates seamless AI product development, from prototyping and prompt experimentation to result evaluation and deployment. The Intelligence Layer SDK provides features such as Composability, Evaluability, and Traceability, along with examples to get started. It supports local installation using poetry, integration with Docker, and access to LLM endpoints for tutorials and tasks like Summarization, Question Answering, Classification, Evaluation, and Parameter Optimization. The tool also offers pre-configured tasks for tasks like Classify, QA, Search, and Summarize, serving as a foundation for custom development.

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.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

WritingAIPaper is a comprehensive guide for beginners on crafting AI conference papers. It covers topics like paper structure, core ideas, framework construction, result analysis, and introduction writing. The guide aims to help novices navigate the complexities of academic writing and contribute to the field with clarity and confidence. It also provides tips on readability improvement, logical strength, defensibility, confusion time reduction, and information density increase. The appendix includes sections on AI paper production, a checklist for final hours, common negative review comments, and advice on dealing with paper rejection.

gollm is a Go package designed to simplify interactions with Large Language Models (LLMs) for AI engineers and developers. It offers a unified API for multiple LLM providers, easy provider and model switching, flexible configuration options, advanced prompt engineering, prompt optimization, memory retention, structured output and validation, provider comparison tools, high-level AI functions, robust error handling and retries, and extensible architecture. The package enables users to create AI-powered golems for tasks like content creation workflows, complex reasoning tasks, structured data generation, model performance analysis, prompt optimization, and creating a mixture of agents.

InterpretML is an open-source package that incorporates state-of-the-art machine learning interpretability techniques under one roof. With this package, you can train interpretable glassbox models and explain blackbox systems. InterpretML helps you understand your model's global behavior, or understand the reasons behind individual predictions. Interpretability is essential for: - Model debugging - Why did my model make this mistake? - Feature Engineering - How can I improve my model? - Detecting fairness issues - Does my model discriminate? - Human-AI cooperation - How can I understand and trust the model's decisions? - Regulatory compliance - Does my model satisfy legal requirements? - High-risk applications - Healthcare, finance, judicial, ...

The UvA Deep Learning Tutorials repository contains a series of Jupyter notebooks designed to help understand theoretical concepts from lectures by providing corresponding implementations. The notebooks cover topics such as optimization techniques, transformers, graph neural networks, and more. They aim to teach details of the PyTorch framework, including PyTorch Lightning, with alternative translations to JAX+Flax. The tutorials are integrated as official tutorials of PyTorch Lightning and are relevant for graded assignments and exams.

TruLens provides a set of tools for developing and monitoring neural nets, including large language models. This includes both tools for evaluation of LLMs and LLM-based applications with _TruLens-Eval_ and deep learning explainability with _TruLens-Explain_. _TruLens-Eval_ and _TruLens-Explain_ are housed in separate packages and can be used independently.

LLMOps Duke AIPI is a course focused on operationalizing Large Language Models, teaching methodologies for developing applications using software development best practices with large language models. The course covers various topics such as generative AI concepts, setting up development environments, interacting with large language models, using local large language models, applied solutions with LLMs, extensibility using plugins and functions, retrieval augmented generation, introduction to Python web frameworks for APIs, DevOps principles, deploying machine learning APIs, LLM platforms, and final presentations. Students will learn to build, share, and present portfolios using Github, YouTube, and Linkedin, as well as develop non-linear life-long learning skills. Prerequisites include basic Linux and programming skills, with coursework available in Python or Rust. Additional resources and references are provided for further learning and exploration.

This repository contains slides, notebooks, and data for the Machine Learning University (MLU) Responsible AI class. The mission is to make Machine Learning accessible to everyone, covering widely used ML techniques and applying them to real-world problems. The class includes lectures, final projects, and interactive visuals to help users learn about Responsible AI and core ML concepts.

This repository contains a collection of interview questions related to various topics such as statistics, machine learning, deep learning, Python, networking, operating systems, data structures, and algorithms. The questions cover a wide range of concepts and are suitable for individuals preparing for technical interviews in the field of artificial intelligence and data science.

Mentals AI is a tool designed for creating and operating agents that feature loops, memory, and various tools, all through straightforward markdown syntax. This tool enables you to concentrate solely on the agent’s logic, eliminating the necessity to compose underlying code in Python or any other language. It redefines the foundational frameworks for future AI applications by allowing the creation of agents with recursive decision-making processes, integration of reasoning frameworks, and control flow expressed in natural language. Key concepts include instructions with prompts and references, working memory for context, short-term memory for storing intermediate results, and control flow from strings to algorithms. The tool provides a set of native tools for message output, user input, file handling, Python interpreter, Bash commands, and short-term memory. The roadmap includes features like a web UI, vector database tools, agent's experience, and tools for image generation and browsing. The idea behind Mentals AI originated from studies on psychoanalysis executive functions and aims to integrate 'System 1' (cognitive executor) with 'System 2' (central executive) to create more sophisticated agents.

I'm a BSc tutor, here to explain complex concepts and guide you in science subjects.

I explain basic concepts and analyze code in distributed systems.

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

A facilitator for understanding concepts using a simplified Concept Attainment Method.

I explain complex topics in simple, fun ways, like you're 5!

I explain topics with a structured approach and lots of emojis!

Explain using math and python

Explains ML and data science concepts clearly, catering to various expertise levels.

I'm a Kazakhtelecom sales manager, simplifying telecom concepts in Russian.

A coding expert who interprets and writes code, explains concepts, and debugs.

Expert in Micro Economics, interprets graphs, explains concepts, avoids direct exam answers.

ELI5 ChatGPT: Explica conceitos complexos de forma simples, incentivando aprendizado e curiosidade em diversos tópicos de maneira acessível.

Produces Streamlit code first, then explains briefly in a casual, supportive tone.

这是李继刚（即刻同名）创作的讲解概念的 Bot。请直接输入你想要了解的概念名称即可。

I refine explanations.

I generate Manim animations for CS education.

Academic guide in BCom subjects, focusing on clear, detailed explanations.

Explains ideas & Solve problems intuitively and comprehensibly in great detail.

A creative interpreter for explaining and simplifying complex topics as parables and fables.

Ein deutscher Biologietutor, geduldig und sachkundig, der Schülern beim Lernen hilft.