Best AI tools for< Explain A Geological Process >

slAItor is an AI translation assistant powered by GPT technology. It offers advanced translation features and customization options to enhance the translation experience. Users can benefit from step-by-step translations, multiple translation alternatives, and unique translation styles. The tool supports 28 language pairs and combines recent AI advancements with traditional translation techniques to deliver accurate and efficient translations. slAItor also provides post-processing and evaluation steps to ensure translation quality and offers a user-friendly interface for seamless translation management.

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.

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.

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.

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.

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.

Whybug is an AI tool designed to help developers debug their code by explaining errors. It utilizes a large language model trained on data from StackExchange and other sources to predict the causes of errors and provide solutions. Users can input error messages and receive explanations along with example fixes in code.

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.

DB Sensei is an AI-powered SQL tool that helps developers generate, fix, explain, and format SQL queries with ease. It features a user-friendly interface, AI-driven query generation, query fixing, query explaining, and query formatting. DB Sensei is designed for developers, database administrators, and students who want to get faster results and improve their database skills.

Metabob is an AI-powered code review tool that helps developers detect, explain, and fix coding problems. It utilizes proprietary graph neural networks to detect problems and LLMs to explain and resolve them, combining the best of both worlds. Metabob's AI is trained on millions of bug fixes performed by experienced developers, enabling it to detect complex problems that span across codebases and automatically generate fixes for them. It integrates with popular code hosting platforms such as GitHub, Bitbucket, Gitlab, and VS Code, and supports various programming languages including Python, Javascript, Typescript, Java, C++, and C.

curioAI is an AI tool that offers a one-stop knowledge platform where users can sign in with Google to access a wide range of information on various topics. It leverages artificial intelligence to generate engaging Tweets and LinkedIn posts, explain complex topics in simple terms, and even create original songs. The platform aims to provide users with new insights, ideas, and opportunities while enhancing their social media presence and knowledge on different subjects.

Programming Helper is a tool that helps you code faster with the help of AI. It can generate code, test code, and explain code. It also has a wide range of other features, such as a function from description, text description to SQL command, and code to explanation. Programming Helper is a valuable tool for any programmer, regardless of their skill level.

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.

Totoy is a Document AI tool that redefines the way documents are processed. Its API allows users to explain, classify, and create knowledge bases from documents without the need for training. The tool supports 19 languages and works with plain text, images, and PDFs. Totoy is ideal for automating workflows, complying with accessibility laws, and creating custom AI assistants for employees or customers.

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.

AICodeConvert is an AI tool that simplifies coding by integrating AI Code Translator and AI Code Generator. It efficiently translates existing code into different programming languages and automatically generates high-quality code snippets and templates. This powerful combination makes AICodeConvert an indispensable tool for developers, providing a convenient and intelligent coding experience.

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.

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.

PicNotes is a web-based image-to-text converter that can convert messy images into summaries, text, or explanations. It supports handwritten papers, medical reports, and other types of images. The tool is easy to use: simply upload an image and choose the desired output format. PicNotes will then process the image and return the results within seconds.

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.

imodelsX is a Scikit-learn friendly library that provides tools for explaining, predicting, and steering text models/data. It also includes a collection of utilities for getting started with text data. **Explainable modeling/steering** | Model | Reference | Output | Description | |---|---|---|---| | Tree-Prompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/tree_prompt) | Explanation + Steering | Generates a tree of prompts to steer an LLM (_Official_) | | iPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/iprompt) | Explanation + Steering | Generates a prompt that explains patterns in data (_Official_) | | AutoPrompt | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/autoprompt) | Explanation + Steering | Find a natural-language prompt using input-gradients (⌛ In progress)| | D3 | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/d3) | Explanation | Explain the difference between two distributions | | SASC | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/sasc) | Explanation | Explain a black-box text module using an LLM (_Official_) | | Aug-Linear | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_linear) | Linear model | Fit better linear model using an LLM to extract embeddings (_Official_) | | Aug-Tree | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/aug_tree) | Decision tree | Fit better decision tree using an LLM to expand features (_Official_) | **General utilities** | Model | Reference | |---|---| | LLM wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/llm) | Easily call different LLMs | | | Dataset wrapper| [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/data) | Download minimially processed huggingface datasets | | | Bag of Ngrams | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/bag_of_ngrams) | Learn a linear model of ngrams | | | Linear Finetune | [Reference](https://github.com/microsoft/AugML/tree/main/imodelsX/linear_finetune) | Finetune a single linear layer on top of LLM embeddings | | **Related work** * [imodels package](https://github.com/microsoft/interpretml/tree/main/imodels) (JOSS 2021) - interpretable ML package for concise, transparent, and accurate predictive modeling (sklearn-compatible). * [Adaptive wavelet distillation](https://arxiv.org/abs/2111.06185) (NeurIPS 2021) - distilling a neural network into a concise wavelet model * [Transformation importance](https://arxiv.org/abs/1912.04938) (ICLR 2020 workshop) - using simple reparameterizations, allows for calculating disentangled importances to transformations of the input (e.g. assigning importances to different frequencies) * [Hierarchical interpretations](https://arxiv.org/abs/1807.03343) (ICLR 2019) - extends CD to CNNs / arbitrary DNNs, and aggregates explanations into a hierarchy * [Interpretation regularization](https://arxiv.org/abs/2006.14340) (ICML 2020) - penalizes CD / ACD scores during training to make models generalize better * [PDR interpretability framework](https://www.pnas.org/doi/10.1073/pnas.1814225116) (PNAS 2019) - an overarching framewwork for guiding and framing interpretable machine learning

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.

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 |

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.

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.

Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. _For interpretability in NLP, check out our new package:imodelsX _

Savvy is a CLI tool that simplifies the creation, sharing, and running of runbooks directly from the terminal. It can generate runbooks using AI or commands provided by the user. The tool allows users to easily create runbooks for various tasks, share them, and run them automatically. Savvy also provides features like explaining commands and troubleshooting errors in a user-friendly manner. It supports creating runbooks from shell history, sharing runbooks, and running runbooks seamlessly from the terminal.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.

fish-ai is a tool that adds AI functionality to Fish shell. It can be integrated with various AI providers like OpenAI, Azure OpenAI, Google, Hugging Face, Mistral, or a self-hosted LLM. Users can transform comments into commands, autocomplete commands, and suggest fixes. The tool allows customization through configuration files and supports switching between contexts. Data privacy is maintained by redacting sensitive information before submission to the AI models. Development features include debug logging, testing, and creating releases.

rwkv.cpp is a port of BlinkDL/RWKV-LM to ggerganov/ggml, supporting FP32, FP16, and quantized INT4, INT5, and INT8 inference. It focuses on CPU but also supports cuBLAS. The project provides a C library rwkv.h and a Python wrapper. RWKV is a large language model architecture with models like RWKV v5 and v6. It requires only state from the previous step for calculations, making it CPU-friendly on large context lengths. Users are advised to test all available formats for perplexity and latency on a representative dataset before serious use.

AIKit is a one-stop shop to quickly get started to host, deploy, build and fine-tune large language models (LLMs). AIKit offers two main capabilities: Inference: AIKit uses LocalAI, which supports a wide range of inference capabilities and formats. LocalAI provides a drop-in replacement REST API that is OpenAI API compatible, so you can use any OpenAI API compatible client, such as Kubectl AI, Chatbot-UI and many more, to send requests to open-source LLMs! Fine Tuning: AIKit offers an extensible fine tuning interface. It supports Unsloth for fast, memory efficient, and easy fine-tuning experience.

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.

Gp.nvim (GPT prompt) Neovim AI plugin provides a seamless integration of GPT models into Neovim, offering features like streaming responses, extensibility via hook functions, minimal dependencies, ChatGPT-like sessions, instructable text/code operations, speech-to-text support, and image generation directly within Neovim. The plugin aims to enhance the Neovim experience by leveraging the power of AI models in a user-friendly and native way.

Neural is a Vim and Neovim plugin that integrates various machine learning tools to assist users in writing code, generating text, and explaining code or paragraphs. It supports multiple machine learning models, focuses on privacy, and is compatible with Vim 8.0+ and Neovim 0.8+. Users can easily configure Neural to interact with third-party machine learning tools, such as OpenAI, to enhance code generation and completion. The plugin also provides commands like `:NeuralExplain` to explain code or text and `:NeuralStop` to stop Neural from working. Neural is maintained by the Dense Analysis team and comes with a disclaimer about sending input data to third-party servers for machine learning queries.

Streamer-Sales is a large model for live streamers that can explain products based on their characteristics and inspire users to make purchases. It is designed to enhance sales efficiency and user experience, whether for online live sales or offline store promotions. The model can deeply understand product features and create tailored explanations in vivid and precise language, sparking user's desire to purchase. It aims to revolutionize the shopping experience by providing detailed and unique product descriptions to engage users effectively.

Devoxx Genie is a Java-based IntelliJ IDEA plugin that integrates with local and cloud-based LLM providers to aid in reviewing, testing, and explaining project code. It supports features like code highlighting, chat conversations, and adding files/code snippets to context. Users can modify REST endpoints and LLM parameters in settings, including support for cloud-based LLMs. The plugin requires IntelliJ version 2023.3.4 and JDK 17. Building and publishing the plugin is done using Gradle tasks. Users can select an LLM provider, choose code, and use commands like review, explain, or generate unit tests for code analysis.

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.

Narrative expert on English Premier League and related English history, culture, and geology.

Simplifies complex jobs into easy explanations for all.

Explains a science topic with analogies, principles, models and context

A witty, sarcastic teacher who makes learning fun with clever humor.

I generate wild, yet believable conspiracies using historical events in a twisted context.

Explains like Richard Feynman using his method.

Executes tasks, explains only when asked.

Structured explanations without hallucinations.

Your personal mythic story teller

Multilingual, novelistic Tango storyteller.

Explores 'The Beginning of Infinity' by David Deutsch, offering insights and discussions.

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

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.

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.

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

I will explain any concept in calculus in a fun way!

Cornered by a taunt? Just explain your situation and I'll provide you with a comeback that'll decimate your adversary. I deliver knock-out punches. With my mouth.

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

A Global dictionary that requires only a word to explain it in both english and its original language.

Expert in product ingredient analysis. Wanna know if a product is good or bad? I rate and explain the ingredients in simple terms.