Best AI tools for< Learn Efficiently >

Onri is a revolutionary online platform that provides a personalized learning path and high-quality learning materials to help users master any concept efficiently. With over 7 million concepts, 170 million paths, and 30,000 learning materials, Onri caters to students, industry analysts, and self-learners. The platform aims to address the challenges of traditional learning methods by offering expert guidance and resources for free, making learning accessible and effective in a rapidly changing world.

Opal is an AI-powered study tool designed to supercharge studying for students. It offers features such as AI-powered notes, flashcards, quizzes, and advanced performance tracking. Opal allows users to upload various document types, provides multilingual support, and ensures bank-level security for stored documents. The tool is built to help students summarize, review, and learn efficiently with the assistance of AI technology.

Candytools AI is a curated collection of AI tools that provides users with a comprehensive directory of various AI applications. Users can explore different categories such as Text&Writing, Productivity, Design&Art, Education, Life Assistant, Marketing, and more to discover and utilize cutting-edge AI technologies. The platform offers a wide range of AI tools that cater to diverse needs, from personalized learning and mental well-being support to automation solutions and creative content generation. Candytools AI aims to simplify the process of finding and utilizing AI tools for different tasks and industries, making it a valuable resource for individuals and businesses seeking to leverage AI technology.

YOURIKA is an AI-powered platform that offers personalized support for nurses and advisory services for businesses looking to leverage artificial intelligence. The platform is designed to provide immediate and tailored assistance to nurses, helping them learn, study, and perform their job more efficiently. YOURIKA Labs, the company behind the platform, is a leading AI research and development company founded by top AI experts. They focus on empowering healthcare professionals and businesses to achieve their strategic objectives through advanced AI solutions.

Video Summarizer is an AI tool designed to generate educational summaries from lengthy videos in multiple languages. It simplifies the process of summarizing video content, making it easier for users to grasp key information efficiently. The tool is user-friendly and efficient, catering to individuals seeking quick and concise video summaries for educational purposes.

YouBrief is an AI-powered platform that provides instant YouTube video summaries for efficient learning. It offers quick summaries of various YouTube videos, highlighting key ideas and insights to help users save time and stay informed. With YouBrief, users can easily absorb essential information from a wide range of content, enhancing their learning experience and knowledge acquisition.

Recall is an AI-driven application that allows users to summarize any online content and save it to a knowledge base. The tool automatically organizes and interlinks the content for easy rediscovery. Users can save time by getting key points from various sources like podcasts, YouTube videos, news articles, and PDFs. Recall uses AI for automatic categorization, spaced repetition learning, and data export. The application prioritizes security, data protection, and user control over data ownership and portability.

Structurepedia is an AI-powered platform that maps the structure of knowledge by providing structured and interactive information on various topics, including neural network architecture variants and other important concepts in machine learning and artificial intelligence. It offers a new way to learn by allowing users to explore topics through visual diagrams and detailed resources, making it easier to understand complex information. Structurepedia aims to revolutionize the way people access and comprehend knowledge in the age of AI, acting as a modern encyclopedia and search engine tailored for the AI era.

OmniSets is an ultimate flashcard tool that helps students learn efficiently. It combines advanced machine learning algorithms and incorporates them throughout the platform. OmniSets offers various modes, from spaced repetition to matching games and AI tools, to make studying easier. Users can create and organize study sets, search from over 250k+ public study sets, and take advantage of the spell tool to write terms and definitions. OmniSets is a community-driven platform that values user feedback and is constantly updating and improving its features.

BiRead is an AI-powered tool designed for instant bilingual reading. It allows users to translate any website into bilingual format with just one click, making it easy to read content in multiple languages. The tool supports over 100 languages and aims to break language barriers, enabling users to explore a world of diverse content effortlessly. BiRead offers a seamless bilingual experience, combining advanced AI translation technology with user-friendly features to enhance multilingual communication and language learning.

StudyMap.ai is an AI-powered platform designed to help users learn anything efficiently. By leveraging artificial intelligence technology, StudyMap.ai offers personalized learning experiences tailored to individual needs. The platform enables users to study various subjects, acquire new skills, and enhance their knowledge through interactive and engaging content. With StudyMap.ai, users can access a wide range of educational resources, track their progress, and receive recommendations to optimize their learning journey.

Penseum is an AI-powered study partner that helps students learn more effectively. It can instantly transform notes, PDFs, videos, and PowerPoints into custom study guides, flashcards, questions & answers, and personalized AI chat. Penseum also provides a study roadmap to help students learn one step at a time. With Penseum, students can say goodbye to endless searching for questions and answers and dive straight into practicing. They can also connect with their own AI tutor and get answers at any time, even when their professor is unavailable. Penseum is the perfect study buddy for students who want to learn more efficiently and effectively.

Roadmapped.ai is an AI-powered platform designed to help users learn various topics efficiently and quickly. By providing a structured roadmap generated in seconds, the platform eliminates the need to navigate through scattered online resources aimlessly. Users can input a topic they want to learn, and the AI will generate a personalized roadmap with curated resources. The platform also offers features like AI-powered YouTube search, saving roadmaps, priority support, and access to a private Discord community.

AlphaCode is an AI-powered programming assistant that can help you write code faster and more efficiently. It uses advanced machine learning techniques to understand your code and generate suggestions that can help you improve your code quality and performance.

ACHIV is an AI tool for ideas validation and market research. It helps businesses make informed decisions based on real market needs by providing data-driven insights. The tool streamlines the market validation process, allowing quick adaptation and refinement of product development strategies. ACHIV offers a revolutionary approach to data collection and preprocessing, along with proprietary AI models for smart analysis and predictive forecasting. It is designed to assist entrepreneurs in understanding market gaps, exploring competitors, and enhancing investment decisions with real-time data.

Migaku is a powerful Chrome extension designed to help users learn a new language efficiently by turning favorite websites into learning materials. It offers tools and concrete steps to fast-track language learning, including features like creating flashcards from content, looking up definitions and pronunciations, and generating AI explanations. Migaku caters to learners of all levels, from beginners to advanced users, and provides a comprehensive platform for immersive language learning.

TanyaPDF is an AI-powered tool that helps users to learn and understand PDF documents more efficiently. By leveraging AI technology, TanyaPDF can read and summarize research files, allowing users to interact with the content through an interactive chat interface. Users can save and review conversations, ask questions, receive accurate answers, and enhance their learning experience without losing track of their progress. TanyaPDF is suitable for students, researchers, and professionals who seek assistance in tasks such as thesis writing, research analysis, legal document comprehension, financial report review, and interactive document creation.

MiGuru is a platform designed to help you find your next job quickly and efficiently. Today it has a job search engine that consolidates the public offers of the Chilean market. Through the use of artificial intelligence, we learn from your answers and use information from your CV to complete your applications automatically. In addition, we support you in improving your CV through a complete personalized report with recommendations based on industry best practices, analyzed using artificial intelligence.

AskMore is an AI-powered platform for conducting user interviews and product research. The tool leverages artificial intelligence to streamline the interview process, enabling users to gather feedback efficiently and in multiple languages. By automating tasks such as generating reports and translating interviews, AskMore helps users access valuable insights and reach a wider audience. The platform aims to enhance the user research experience by providing a user-friendly interface and research best practices to ensure high-quality feedback.

Bash Senpai is a terminal assistant powered by ChatGPT that transforms instructions into ready-to-use commands. It provides convenience by allowing users to get answers without leaving the terminal and offers better answers by providing context with questions. The tool also incorporates self-reflection to improve the quality of its responses.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

This repository is part of the Certified Cloud Native Applied Generative AI Engineer program, focusing on Applied Generative AI Fundamentals. It covers prompt engineering, developing custom GPTs, and Multi AI Agent Systems. The course helps in building a strong understanding of generative AI, applying Large Language Models (LLMs) and diffusion models practically. It introduces principles of prompt engineering to work efficiently with AI, creating custom AI models and GPTs using OpenAI, Azure, and Google technologies. It also utilizes open source libraries like LangChain, CrewAI, and LangGraph to automate tasks and business processes.

Auto-Gmail-Creator is an open-source automation script designed for Python enthusiasts to learn automation basics and for marketers to create multiple Google accounts efficiently. The script automates the process of creating Gmail accounts using sms-activate.org API for phone verification. It handles the download of Chromedriver or Geckodriver automatically and can be customized to prevent blocking. The tool is useful for projects related to automation, scraping, and machine learning.

Cyclops is a toolkit for facilitating research and deployment of ML models for healthcare. It provides a few high-level APIs namely: data - Create datasets for training, inference and evaluation. We use the popular 🤗 datasets to efficiently load and slice different modalities of data models - Use common model implementations using scikit-learn and PyTorch tasks - Use common ML task formulations such as binary classification or multi-label classification on tabular, time-series and image data evaluate - Evaluate models on clinical prediction tasks monitor - Detect dataset shift relevant for clinical use cases report - Create model report cards for clinical ML models

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 |

Mergoo is a library for easily merging multiple LLM experts and efficiently training the merged LLM. With Mergoo, you can efficiently integrate the knowledge of different generic or domain-based LLM experts. Mergoo supports several merging methods, including Mixture-of-Experts, Mixture-of-Adapters, and Layer-wise merging. It also supports various base models, including LLaMa, Mistral, and BERT, and trainers, including Hugging Face Trainer, SFTrainer, and PEFT. Mergoo provides flexible merging for each layer and supports training choices such as only routing MoE layers or fully fine-tuning the merged LLM.

AI2Apps is a visual IDE for building LLM-based AI agent applications, enabling developers to efficiently create AI agents through drag-and-drop, with features like design-to-development for rapid prototyping, direct packaging of agents into apps, powerful debugging capabilities, enhanced user interaction, efficient team collaboration, flexible deployment, multilingual support, simplified product maintenance, and extensibility through plugins.

MyScaleDB is a SQL vector database designed for scalable AI applications, enabling developers to efficiently manage and process massive volumes of data using familiar SQL. It offers fast and efficient vector search, filtered search, and SQL-vector join queries. MyScaleDB is fully SQL-compatible and production-ready for AI applications, providing unmatched performance and scalability through cutting-edge OLAP architecture and advanced vector algorithms. Built on top of ClickHouse, it combines structured and vectorized data management for high accuracy and speed in filtered searches.

Trubrics-sdk is a software development kit designed to facilitate the integration of analytics features into applications. It provides a set of tools and functionalities that enable developers to easily incorporate analytics capabilities, such as data collection, analysis, and reporting, into their software products. The SDK streamlines the process of implementing analytics solutions, allowing developers to focus on building and enhancing their applications' functionality and user experience. By leveraging trubrics-sdk, developers can quickly and efficiently integrate robust analytics features, gaining valuable insights into user behavior and application performance.

Parrot is a distributed serving system for LLM-based Applications, designed to efficiently serve LLM-based applications by adding Semantic Variable in the OpenAI-style API. It allows for horizontal scalability with multiple Engine instances running LLM models communicating with ServeCore. The system enables AI agents to interact with LLMs via natural language prompts for collaborative tasks.

GPT4All is an ecosystem to run powerful and customized large language models that work locally on consumer grade CPUs and any GPU. Note that your CPU needs to support AVX or AVX2 instructions. Learn more in the documentation. A GPT4All model is a 3GB - 8GB file that you can download and plug into the GPT4All open-source ecosystem software. Nomic AI supports and maintains this software ecosystem to enforce quality and security alongside spearheading the effort to allow any person or enterprise to easily train and deploy their own on-edge large language models.

MyScaleDB is a SQL vector database optimized for AI applications, enabling developers to manage and process massive volumes of data efficiently. It offers fast and powerful vector search, filtered search, and SQL-vector join queries, making it fully SQL-compatible. MyScaleDB provides unmatched performance and scalability by leveraging cutting-edge OLAP database architecture and advanced vector algorithms. It is production-ready for AI applications, supporting structured data, text, vector, JSON, geospatial, and time-series data. MyScale Cloud offers fully-managed MyScaleDB with premium features on billion-scale data, making it cost-effective and simpler to use compared to specialized vector databases. Built on top of ClickHouse, MyScaleDB combines structured and vector search efficiently, ensuring high accuracy and performance in filtered search operations.

The Second Brain AI Agent Project is a tool designed to empower personal knowledge management by automatically indexing markdown files and links, providing a smart search engine powered by OpenAI, integrating seamlessly with different note-taking methods, and enhancing productivity by accessing information efficiently. The system is built on LangChain framework and ChromaDB vector store, utilizing a pipeline to process markdown files and extract text and links for indexing. It employs a Retrieval-augmented generation (RAG) process to provide context for asking questions to the large language model. The tool is beneficial for professionals, students, researchers, and creatives looking to streamline workflows, improve study sessions, delve deep into research, and organize thoughts and ideas effortlessly.

LinkedIn_AIHawk is an automated tool designed to revolutionize the job search and application process on LinkedIn. It leverages automation and artificial intelligence to efficiently apply to relevant positions, personalize responses, manage application volume, filter listings, generate dynamic resumes, and handle sensitive information securely. The tool aims to save time, increase application relevance, and enhance job search effectiveness in today's competitive landscape.

KaibanJS is a JavaScript-native framework for building multi-agent AI systems. It enables users to create specialized AI agents with distinct roles and goals, manage tasks, and coordinate teams efficiently. The framework supports role-based agent design, tool integration, multiple LLMs support, robust state management, observability and monitoring features, and a real-time agentic Kanban board for visualizing AI workflows. KaibanJS aims to empower JavaScript developers with a user-friendly AI framework tailored for the JavaScript ecosystem, bridging the gap in the AI race for non-Python developers.

HybridAGI is the first Programmable LLM-based Autonomous Agent that lets you program its behavior using a **graph-based prompt programming** approach. This state-of-the-art feature allows the AGI to efficiently use any tool while controlling the long-term behavior of the agent. Become the _first Prompt Programmers in history_ ; be a part of the AI revolution one node at a time! **Disclaimer: We are currently in the process of upgrading the codebase to integrate DSPy**

MSCCL++ is a GPU-driven communication stack for scalable AI applications. It provides a highly efficient and customizable communication stack for distributed GPU applications. MSCCL++ redefines inter-GPU communication interfaces, delivering a highly efficient and customizable communication stack for distributed GPU applications. Its design is specifically tailored to accommodate diverse performance optimization scenarios often encountered in state-of-the-art AI applications. MSCCL++ provides communication abstractions at the lowest level close to hardware and at the highest level close to application API. The lowest level of abstraction is ultra light weight which enables a user to implement logics of data movement for a collective operation such as AllReduce inside a GPU kernel extremely efficiently without worrying about memory ordering of different ops. The modularity of MSCCL++ enables a user to construct the building blocks of MSCCL++ in a high level abstraction in Python and feed them to a CUDA kernel in order to facilitate the user's productivity. MSCCL++ provides fine-grained synchronous and asynchronous 0-copy 1-sided abstracts for communication primitives such as `put()`, `get()`, `signal()`, `flush()`, and `wait()`. The 1-sided abstractions allows a user to asynchronously `put()` their data on the remote GPU as soon as it is ready without requiring the remote side to issue any receive instruction. This enables users to easily implement flexible communication logics, such as overlapping communication with computation, or implementing customized collective communication algorithms without worrying about potential deadlocks. Additionally, the 0-copy capability enables MSCCL++ to directly transfer data between user's buffers without using intermediate internal buffers which saves GPU bandwidth and memory capacity. MSCCL++ provides consistent abstractions regardless of the location of the remote GPU (either on the local node or on a remote node) or the underlying link (either NVLink/xGMI or InfiniBand). This simplifies the code for inter-GPU communication, which is often complex due to memory ordering of GPU/CPU read/writes and therefore, is error-prone.

AI Resource Navigator efficiently guides users to educational, financial, healthcare, and legal resources in the USA

A tutor for Energy Conversion Principles, providing detailed, searchable answers.

My goal is to adaptively teach you in the most efficient way possible according to how you learn best. I can teach you virtually anything.

Efficient Japanese learning Assistant 高效日语学习助手

Efficient and witty Python 3 code wizard.

Friendly web assistant for efficient code. Ask the wizard to create an application and you will get the HTML, CSS and Javascript code ready to run your web application.

Friendly bot for efficient TOEFL speaking practice, offering direct questions and detailed feedback.

Lingo Tutor is your personal language learning companion, designed to make mastering a new language engaging, efficient, and enjoyable. LingoGPT Tutor offers interactive conversations, grammar tips, cultural insights, and much more to help you become fluent in your chosen language.

A Python and programming expert, guiding users on best practices for writing clean, efficient, and well-documented Python code.

Advises on QA tests based on recent game code changes, including git history. Learn more at regression.gg

As a professional relocation assistant, I specialize in providing comprehensive support for individuals moving abroad for work, residency, or education, ensuring a smooth and efficient transition.

An AI GPT model designed to assist with Shell/Bash programming, providing real-time code suggestions, debugging tips, and script optimization for efficient command-line operations.

BigQueryGPT aids in mastering BigQuery SQL with concise, practical examples. Tailored for all skill levels, it simplifies complex queries, offering clear explanations and optimized solutions for efficient learning and query troubleshooting.

To get started, please type "menu" and select an option from the menu by typing the corresponding keyword or number. If at any time you need assistance or wish to ask a question, just type "help" for more options.

Academic assistant for SICP study, referencing solutions

Analyzes code for time and memory complexity

中国QT C++顶级程序员，提供中文解答和代码示例

严肃专业的电子工程学术专家

Unity development assistant for version-specific advice

Informative guide on fuels and energy sources.