Best AI tools for< Explain Methods >

TLDR is an AI-powered IDE plugin that explains code in plain English. It helps developers understand code by providing quick summaries of what a piece of code is doing. The tool supports almost all programming languages and offers a free version for users to try before purchasing. TLDR aims to simplify the understanding of complex code structures and save developers time in comprehending codebases.

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.

The website offers a no-code AI-powered user assistance tool that helps turn knowledge bases into proactive in-app support. It features Explain This for in-app contextual mastery, Chatbot for real-time intelligent responses, Tooltips for effortless interaction, Widget for a centralized help hub, Knowledge Base for context-based empowerment, and Ticket Form for hassle-free issue reporting. The tool supports seven languages and aims to boost product adoption while reducing support tickets.

Whybug is an AI tool designed to help developers debug their code by providing explanations for errors. By utilizing a large language model trained on data from StackExchange and other sources, Whybug can predict the causes of errors and suggest fixes. Users can simply paste an error message and receive detailed explanations on how to resolve the issue. The tool aims to streamline the debugging process and improve code quality.

ExplainDev is a platform that allows users to ask and answer technical coding questions. It uses computer vision to retrieve technical context from images or videos. The platform is designed to help developers get the best answers to their technical questions and guide others to theirs.

Jam is a bug-tracking tool that helps developers reproduce and debug issues quickly and easily. It automatically captures all the information engineers need to debug, including device and browser information, console logs, network logs, repro steps, and backend tracing. Jam also integrates with popular tools like GitHub, Jira, Linear, Slack, ClickUp, Asana, Sentry, Figma, Datadog, Gitlab, Notion, and Airtable. With Jam, developers can save time and effort by eliminating the need to write repro steps and manually collect information. Jam is used by over 90,000 developers and has received over 150 positive reviews.

Kognitium is an AI assistant designed to provide users with comprehensive and accurate information across various domains. It is equipped with advanced capabilities that enable it to understand the intent behind user inquiries and deliver tailored responses. Kognitium's knowledge base spans a wide range of subjects, including current events, science, history, philosophy, and linguistics. It is designed to be user-friendly and accessible, making it a valuable tool for students, professionals, and anyone seeking to expand their knowledge. Kognitium is committed to providing reliable and actionable insights, empowering users to make informed decisions and enhance their understanding of the world around them.

SiteExplainer is an AI-powered web application that helps users understand the purpose of any website quickly and accurately. It uses advanced artificial intelligence and machine learning technology to analyze the content of a website and present a summary of the main ideas and key points. SiteExplainer simplifies the language used on landing pages and eliminates corporate jargon to help visitors better understand a website's content.

Memenome AI is an AI tool that helps users discover and understand trending sounds, hashtags, accounts, and posts on TikTok. It offers features to find top sounds, hashtags, and posts, provides AI analysis and templates for trend understanding, and allows users to iterate through content ideas with Meme0. The tool aims to save users time by efficiently identifying trends and empowering them to create engaging content.

Fiddler AI is an AI Observability platform that provides tools for monitoring, explaining, and improving the performance of AI models. It offers a range of capabilities, including explainable AI, NLP and CV model monitoring, LLMOps, and security features. Fiddler AI helps businesses to build and deploy high-performing AI solutions at scale.

Formularizer is an AI-powered assistant designed to help users with formula-related tasks in spreadsheets like Excel, Google Sheets, and Notion. It provides step-by-step guidance, formula generation, and explanations to simplify complex formula creation and problem-solving. With support for regular expressions, Excel VBA, and Google Apps Script, Formularizer aims to enhance productivity and make data manipulation more accessible.

Formularizer is an AI-powered assistant that helps users create formulas in Excel, Google Sheets, and Notion. It supports a variety of formula types, including Excel, Google Apps Script, and regular expressions. Formularizer can generate formulas from natural language instructions, explain how formulas work, and even help users debug their formulas. It is designed to be user-friendly and accessible to everyone, regardless of their level of expertise.

Tooltips.ai is an AI-powered reading extension that provides instant definitions, translations, and summaries for any word or phrase you hover over. It is designed to enhance your reading experience by making it easier and faster to understand complex or unfamiliar content. Tooltips.ai integrates seamlessly with your browser, so you can use it on any website or document.

Revealr is an AI-powered application that focuses on digitalization for business documents. It offers solutions for transforming, complying, and managing various types of documents using AI technology. Revealr helps organizations unlock knowledge from Word and PDF documents, leverage SharePoint investments, and apply AI in a trusted ecosystem to analyze and explain content. The application aims to deliver real-time access to policies and procedures, reduce costs and risks associated with managing brand portfolios, and empower remote workforces with secure information access. Revealr caters to industries such as financial services, government, insurance, and legal sectors, providing digital solutions to improve compliance, reduce risk, and enhance customer experience.

Sider.ai is an AI-powered platform that focuses on security verification for online connections. It ensures a safe browsing experience by reviewing the security of your connection before proceeding. The platform uses advanced algorithms to detect and prevent potential threats, providing users with peace of mind while browsing the internet.

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.

Formulas HQ is an AI-powered formula and script generator for Excel and Sheets. It provides users with a range of tools to simplify complex calculations, automate tasks, and enhance their spreadsheet mastery. With Formulas HQ, users can generate formulas, regular expressions, VBA code, and Apps Script, even without prior programming experience. The platform also offers a chat feature with system prompts to assist users with idea generation and troubleshooting. Formulas HQ is designed to empower users to work smarter and make better business decisions.

Flot AI is an AI-powered writing, reading, and memorization tool that seamlessly integrates into your daily workflow. It is backed by OpenAI and designed to assist users across various apps and websites. With features like AI memory, grammar correction, composing drafts, and expert prompts, Flot AI aims to enhance users' productivity and creativity. The application supports over 200 languages and offers a universal solution for writing and memory tasks at a competitive price point.

Shakespeare Toolbar is an AI-powered writing tool that helps you write better and faster. It is available as a Chrome extension and can be used on any website. With Shakespeare Toolbar, you can rephrase emails, summarize documents, write social media posts, and more. It supports over 10 languages and is available for a one-time purchase of $49.

MaxAI is a productivity tool that provides users with access to various AI models, including ChatGPT, Claude, and Gemini, through a single platform. It offers a range of AI-powered features such as AI chat, AI rewriter, AI quick reply, AI summary, AI search, AI art, and AI translator. MaxAI is designed to help users save time and improve their productivity by automating repetitive tasks and providing assistance with various tasks.

The Alignment Handbook provides robust training recipes for continuing pretraining and aligning language models with human and AI preferences. It includes techniques such as continued pretraining, supervised fine-tuning, reward modeling, rejection sampling, and direct preference optimization (DPO). The handbook aims to fill the gap in public resources on training these models, collecting data, and measuring metrics for optimal downstream performance.

Quantus is a toolkit designed for the evaluation of neural network explanations. It offers more than 30 metrics in 6 categories for eXplainable Artificial Intelligence (XAI) evaluation. The toolkit supports different data types (image, time-series, tabular, NLP) and models (PyTorch, TensorFlow). It provides built-in support for explanation methods like captum, tf-explain, and zennit. Quantus is under active development and aims to provide a comprehensive set of quantitative evaluation metrics for XAI methods.

A comprehensive repository focusing on 'Model Merging in LLMs, MLLMs, and Beyond', providing an exhaustive overview of model merging methods, theories, applications, and future research directions. The repository covers various advanced methods, applications in foundation models, different machine learning subfields, and tasks like pre-merging methods, architecture transformation, weight alignment, basic merging methods, and more.

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 |

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, ...

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.

This repository contains frontier research on explainable AI (XAI), a hot topic in the field of artificial intelligence. It includes trends, use cases, survey papers, books, open courses, papers, and Python libraries related to XAI. The repository aims to organize and categorize publications on XAI, provide evaluation methods, and list various Python libraries for explainable AI.

The ChatGPT R package provides a set of features to assist in R coding. It includes addins like Ask ChatGPT, Comment selected code, Complete selected code, Create unit tests, Create variable name, Document code, Explain selected code, Find issues in the selected code, Optimize selected code, and Refactor selected code. Users can interact with ChatGPT to get code suggestions, explanations, and optimizations. The package helps in improving coding efficiency and quality by providing AI-powered assistance within the RStudio environment.

This repository provides advanced AI explainability for PyTorch, offering state-of-the-art methods for Explainable AI in computer vision. It includes a comprehensive collection of Pixel Attribution methods for various tasks like Classification, Object Detection, Semantic Segmentation, and more. The package supports high performance with full batch image support and includes metrics for evaluating and tuning explanations. Users can visualize and interpret model predictions, making it suitable for both production and model development scenarios.

DeRTa (Refuse Whenever You Feel Unsafe) is a tool designed to improve safety in Large Language Models (LLMs) by training them to refuse compliance at any response juncture. The tool incorporates methods such as MLE with Harmful Response Prefix and Reinforced Transition Optimization (RTO) to address refusal positional bias and strengthen the model's capability to transition from potential harm to safety refusal. DeRTa provides training data, model weights, and evaluation scripts for LLMs, enabling users to enhance safety in language generation tasks.

The 'airwin2rack' repository is a collection of Airwindows audio plugins presented in various formats, including as a static library, a module for VCV Rack, and as CLAP/VST3/AU/LV2/Standalone plugins for DAWs. Users can access these plugins through different methods and interfaces, such as a uniform registry and access pattern, making it easy to integrate Airwindows plugins into their audio projects. The repository also provides instructions for updating the Airwindows sub-library and information on licensing, ensuring that users can utilize the plugins in both open and closed source environments.

Prompt4ReasoningPapers is a repository dedicated to reasoning with language model prompting. It provides a comprehensive survey of cutting-edge research on reasoning abilities with language models. The repository includes papers, methods, analysis, resources, and tools related to reasoning tasks. It aims to support various real-world applications such as medical diagnosis, negotiation, etc.

Bito CLI provides a command line interface to the Bito AI chat functionality, allowing users to interact with the AI through commands. It supports complex automation and workflows, with features like long prompts and slash commands. Users can install Bito CLI on Mac, Linux, and Windows systems using various methods. The tool also offers configuration options for AI model type, access key management, and output language customization. Bito CLI is designed to enhance user experience in querying AI models and automating tasks through the command line interface.

The 'Generative AI' repository provides a C# library for interacting with Google's Generative AI models, specifically the Gemini models. It allows users to access and integrate the Gemini API into .NET applications, supporting functionalities such as listing available models, generating content, creating tuned models, working with large files, starting chat sessions, and more. The repository also includes helper classes and enums for Gemini API aspects. Authentication methods include API key, OAuth, and various authentication modes for Google AI and Vertex AI. The package offers features for both Google AI Studio and Google Cloud Vertex AI, with detailed instructions on installation, usage, and troubleshooting.

Advanced RAG Techniques is a comprehensive collection of cutting-edge Retrieval-Augmented Generation (RAG) tutorials aimed at enhancing the accuracy, efficiency, and contextual richness of RAG systems. The repository serves as a hub for state-of-the-art RAG enhancements, comprehensive documentation, practical implementation guidelines, and regular updates with the latest advancements. It covers a wide range of techniques from foundational RAG methods to advanced retrieval methods, iterative and adaptive techniques, evaluation processes, explainability and transparency features, and advanced architectures integrating knowledge graphs and recursive processing.

tlm is a local CLI copilot tool powered by CodeLLaMa, providing efficient command line suggestions without the need for an API key or internet connection. It works on macOS, Linux, and Windows, with automatic shell detection for Powershell, Bash, and Zsh. The tool offers one-liner generation and command explanation, and can be installed via an installation script or using Go Install. Ollama is required to download necessary models, and the tool can be easily deployed and configured. Contributors are welcome to enhance the tool's functionality.

This repository contains core sources related to Robotics & AI. It serves as a submodule in integrated projects, providing a minimal Ubuntu-specific build system and development tests. The code originated around 2004 in Edinburgh and has grown over the years to encompass various functionalities for Robotics, ML, and AI. Users are advised to explore example projects using this bare code for a better understanding of its capabilities.

RTutor is an AI-based app that generates and tests R code by translating natural language into R scripts using API calls to OpenAI's ChatGPT. It executes the scripts within the Shiny platform, generating R Markdown source files and HTML reports. The tool features GPT-4 for accurate code, comprehensive EDA reports, and a chat window for code explanation, making it ideal for learning R and statistics.

The Vertex AI SDK for Python is a library that provides a convenient way to use the Vertex AI API. It offers a high-level interface for creating and managing Vertex AI resources, such as datasets, models, and endpoints. The SDK also provides support for training and deploying custom models, as well as using AutoML models. With the Vertex AI SDK for Python, you can quickly and easily build and deploy machine learning models on Vertex AI.

Probe is an AI-friendly, fully local, semantic code search tool designed to power the next generation of AI coding assistants. It combines the speed of ripgrep with the code-aware parsing of tree-sitter to deliver precise results with complete code blocks, making it perfect for large codebases and AI-driven development workflows. Probe is fully local, keeping code on the user's machine without relying on external APIs. It supports multiple languages, offers various search options, and can be used in CLI mode, MCP server mode, AI chat mode, and web interface. The tool is designed to be flexible, fast, and accurate, providing developers and AI models with full context and relevant code blocks for efficient code exploration and understanding.

Helps with course design and explains assessment methods.

I can guide your brainstorming sessions to get creative ideas. I can teach you or explain all brainstorming methods. let's practice creative thinking.

A GPT that explains research methods in a language that everyone can easily understand.

Explain scientific papers using the 3-pass method for efficient understanding. After uploading a paper, you can enter First pass/Second pass /Third pass / Q&A to get different level of response from SciPlore.

Explains like Richard Feynman using his method.

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

I simplify complex topics, like you're five!

Simplifies complex jobs into easy explanations for all.

Expert in explaining data visuals for academic publishing.

Inspired by The Office, This ChatGPT explains everything like if you were an eight year old... and if you still don't understand it, it will then explain it like you were a five year old.

跨境物流翻译专家

Helps explain medical consents

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

I create visuals to explain complex crypto concepts.

I explain surname meanings and create images that resonate with them.

Explain Like I'm Five Simplifier

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

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

⚖️ Explain Asimov's Three Laws of Robotics

Explain using math and python