AI tools for study
Related Tools:
Study Plannr
Study Plannr is an AI-powered application that generates personalized and smart study plans using ChatGPT. It optimizes revision by considering subjects, topics, and assessment dates. The tool is designed to help parents, educators, K12 students, and learners studying for certifications in creating customized study plans to improve learning efficiency and goal setting.
Study Fetch
StudyFetch is a revolutionary new platform that allows you to upload your course materials and create interactive study sets. You can study with an AI tutor, create flashcards, generate notes, take practice tests, and more. StudyFetch's AI, Spark.e, utilizes advanced machine learning algorithms to offer a tailored, interactive tutoring experience. Once you upload your study materials, Spark.e scans and indexes them, making the content searchable and accessible for real-time queries.
Studygenie
Studygenie is an AI-powered learning platform that helps students study for tests 10x faster. It uses AI to generate personalized quizzes, track retention, and provide insightful explanations. Studygenie is simple to use and trusted by students at top universities.
Client-side Exception Error Handler
The website appears to be encountering an application error, specifically a client-side exception. This error message indicates that there is an issue with the code running on the user's browser, prompting them to check the browser console for more detailed information. The website may be experiencing technical difficulties that need to be addressed by the developers to ensure proper functionality and user experience.
StudyCards App
StudyCards App is an AI-powered flashcards maker that allows users to create custom flashcard decks with the assistance of Artificial Intelligence. The app features a paper-and-sticky-note interface and an embedded text-to-speech engine for easy memorization and study. It is designed to help users with various learning styles and reading disorders by providing a convenient and accessible platform for creating and organizing study materials.
StudyNinja
StudyNinja is an AI-enhanced study buddy designed to revolutionize the academic journey of students. It offers a holistic productivity solution by blending smart task management, interactive study tools, and a unique AI Tutor. StudyNinja fosters active learning, efficient organization, and effective time management to enhance academic performance. The application provides features such as personalized study goals, assignment management, task management, study notes, and collaborative assignments. It is a cloud-based productivity software that works seamlessly on PC, tablet, or mobile devices, offering ultimate flexibility and hassle-free learning experience.
StudyRaga
StudyRaga is an AI-integrated productivity software designed to help students manage their academic responsibilities. It offers a centralized platform for managing tasks, schedules, and resources, enabling students to stay organized and focused. With features such as smart task management, progress tracking, group assignments, study notes, and interactive study tools, StudyRaga aims to enhance student productivity and collaboration.
StudyShift
StudyShift is a revolutionary collaborative productivity tool specifically designed for students. It is made to make students more efficient and productive. It works everywhere, whether on a PC, tablet, or mobile device. With StudyShift, students can set their study goals and track their progress efficiently. They can also manage their assignments, create documents, collaborate with others, and manage their tasks. StudyShift also includes an AI tutor that can answer questions on any subject. It is a revolutionary suite of productivity tools and apps for learners that works everywhere, whether on a PC, tablet, or mobile device.
Studyable
Studyable is an AI-powered platform designed to assist students with homework help and flashcards. The application leverages artificial intelligence technology to provide personalized learning experiences for users. With Studyable, students can access a wide range of study materials, practice questions, and interactive flashcards to enhance their understanding of various subjects. The platform aims to make studying more efficient and engaging by offering tailored recommendations and adaptive learning features. Studyable is a valuable tool for students seeking academic support and looking to improve their study habits.
Studyquick
Studyquick is an AI-powered tool designed for students to streamline their learning process. By uploading university scripts, lectures, videos, and audio recordings, users can benefit from AI-generated study notes, practice exams, podcasts, and a virtual AI tutor. Studyquick aims to revolutionize the way students prepare for exams by providing personalized and efficient study materials tailored to individual needs. With features like KI-generated study notes, personalized study assistance, and quick access to study materials, Studyquick offers a comprehensive solution for students looking to enhance their learning experience.
StudyPro
StudyPro is a premier online learning platform designed for students to enhance their academic performance. It offers a wide range of services, including grammar checking, paraphrasing, homework planning, and AI writing tools. StudyPro leverages advanced AI technologies to provide personalized learning experiences and support students in achieving their educational goals. The platform aims to simplify the learning process by offering innovative features and top-notch support to help students succeed in their academic journey.
StudyMap.ai
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.
Tomo Cafe
Tomo Cafe is an RPG-ish AI companion application designed to boost productivity by providing users with accountable AI buddies for study, work, and more. Users can engage with unique virtual characters, set study targets, interact in 3D, and unlock character backstories to stay motivated and focused. The application offers a gamified experience with rewards, Pomodoro timer, and immersive storytelling to enhance the learning process.
StudyX
StudyX is an all-in-one AI learning assistant that provides students with a variety of tools to help them learn more effectively. These tools include a chat-based AI assistant, homework help, research paper help, and writing assistance. StudyX is available as a web app, mobile app, and browser extension, making it easy to use anywhere you learn.
StudyWithGpt
StudyWithGpt.com is a GPT-powered full-stack learning hub that provides personalized AI tutorials for various tech stacks including Java, PHP, Golang, Python, front-end, back-end, DevOps, and microservices. The AI Full-Stack Mentor offers tailored tutorials based on the user's learning objectives, breaking down knowledge points and providing 24/7 assistance. Users can ask questions, receive tutorial outlines, and get help with tough problems from the AI tutor.
StudyRaid
StudyRaid is an AI-powered platform that enables users to learn anything 10X faster through personalized courses generated by AI. The platform offers a wide range of features such as AI-crafted lessons, audio lessons, real-time chat with AI, certification programs, quizzes, flashcards, exams, and key points. Users can create their own complete courses with tailored content to suit their learning style. StudyRaid aims to revolutionize the learning experience by providing efficient and focused learning opportunities for students and professionals alike.
StudyQ
StudyQ is a free AI-powered Q&A homework helper and tutor that provides accurate answers for assignments, quizzes, exams, and other learning questions. Users can access advanced models like GPT-4o for free and unlimited usage. StudyQ aims to assist students in their academic endeavors by offering AI-generated solutions to their queries.
Interview.study
Interview.study is an AI-powered interview preparation platform that helps candidates practice real interview questions asked by top companies. The platform provides users with instant feedback on their responses, helping them identify areas for improvement and develop stronger answers. Interview.study also offers a variety of features to help candidates prepare for their interviews, including a database of interview questions, a mock interview tool, and a resume builder.
Sara
Sara is an AI-powered platform that serves as a virtual tutor and exam planner. It leverages artificial intelligence to provide personalized learning experiences and help students prepare for exams efficiently. With Sara, users can access study materials, receive customized study plans, track their progress, and get feedback on their performance. The platform aims to enhance learning outcomes by offering adaptive learning solutions tailored to individual needs.
KardsAI Flashcard Maker
KardsAI is an AI-powered flashcard maker application that aims to make learning easier and more efficient. It allows users to transform any PDF, text, note, or prompt into flashcards in a snap. With features like converting PDFs to flashcards, generating flashcards from prompts, and cross-platform access, KardsAI caters to students, language learners, knowledge seekers, and trivia enthusiasts. The application saves valuable time through AI-powered flashcard creation and helps users remember information longer with a spaced repetition algorithm. KardsAI offers a freemium model, allowing users to use the app for free or upgrade for additional features at an affordable price.
Study Abroad Advisor
Committed to guiding students through the thrilling and transformative journey of studying abroad
Cyber Test & CareerPrep
Helping you study for cybersecurity certifications and get the job you want!
PE Coach
A PE exam coach offering study strategies, practice questions, and motivational support.
Anatomy Ace
Your Anatomy Tutor: Assisting with key concepts, study plans and practice questions!
Taupin
Meet Taupin, your study coach ! Tailored specifically for students in preparatory class , Taupin provides personalized guidance and smart tips to help you study smarter and achieve your goals !
Real Estate Exam Helper
Helps with real estate exam prep, offering study tips and clarifying concepts.
Azure AI Study help
A study assistant for Azure certification, explaining concepts and offering exam tips.
Pro Bible Enhanced
A comprehensive, enhanced tool for Bible study, sermons, and church management.
Step 1 Med Mentor
USMLE Step 1 study tutor using Duke Pathoma Anki deck, evaluates and guides answers. Powered by SlaySchool.com
Study GPT (Mechanics & Dynamics)
Mechanical Engineering GPT to help study Mechanics & Dynamics topics
Algo Final Exam Tutor
I assist in studying for an algorithms exam, guiding through concepts and problems.
Where Should I Study Abroad Test?
Where Should I Study Abroad Test - Find your ideal abroad study location with our free test!
kantv
KanTV is an open-source project that focuses on studying and practicing state-of-the-art AI technology in real applications and scenarios, such as online TV playback, transcription, translation, and video/audio recording. It is derived from the original ijkplayer project and includes many enhancements and new features, including: * Watching online TV and local media using a customized FFmpeg 6.1. * Recording online TV to automatically generate videos. * Studying ASR (Automatic Speech Recognition) using whisper.cpp. * Studying LLM (Large Language Model) using llama.cpp. * Studying SD (Text to Image by Stable Diffusion) using stablediffusion.cpp. * Generating real-time English subtitles for English online TV using whisper.cpp. * Running/experiencing LLM on Xiaomi 14 using llama.cpp. * Setting up a customized playlist and using the software to watch the content for R&D activity. * Refactoring the UI to be closer to a real commercial Android application (currently only supports English). Some goals of this project are: * To provide a well-maintained "workbench" for ASR researchers interested in practicing state-of-the-art AI technology in real scenarios on mobile devices (currently focusing on Android). * To provide a well-maintained "workbench" for LLM researchers interested in practicing state-of-the-art AI technology in real scenarios on mobile devices (currently focusing on Android). * To create an Android "turn-key project" for AI experts/researchers (who may not be familiar with regular Android software development) to focus on device-side AI R&D activity, where part of the AI R&D activity (algorithm improvement, model training, model generation, algorithm validation, model validation, performance benchmark, etc.) can be done very easily using Android Studio IDE and a powerful Android phone.
AIStudyAssistant
AI Study Assistant is an app designed to enhance learning experience and boost academic performance. It serves as a personal tutor, lecture summarizer, writer, and question generator powered by Google PaLM 2. Features include interacting with an AI chatbot, summarizing lectures, generating essays, and creating practice questions. The app is built using 100% Kotlin, Jetpack Compose, Clean Architecture, and MVVM design pattern, with technologies like Ktor, Room DB, Hilt, and Kotlin coroutines. AI Study Assistant aims to provide comprehensive AI-powered assistance for students in various academic tasks.
TrustLLM
TrustLLM is a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions. Specifically, we first propose a set of principles for trustworthy LLMs that span eight different dimensions. Based on these principles, we further establish a benchmark across six dimensions including truthfulness, safety, fairness, robustness, privacy, and machine ethics. We then present a study evaluating 16 mainstream LLMs in TrustLLM, consisting of over 30 datasets. The document explains how to use the trustllm python package to help you assess the performance of your LLM in trustworthiness more quickly. For more details about TrustLLM, please refer to project website.
LLaVA-MORE
LLaVA-MORE is a new family of Multimodal Language Models (MLLMs) that integrates recent language models with diverse visual backbones. The repository provides a unified training protocol for fair comparisons across all architectures and releases training code and scripts for distributed training. It aims to enhance Multimodal LLM performance and offers various models for different tasks. Users can explore different visual backbones like SigLIP and methods for managing image resolutions (S2) to improve the connection between images and language. The repository is a starting point for expanding the study of Multimodal LLMs and enhancing new features in the field.
camel
CAMEL is an open-source library designed for the study of autonomous and communicative agents. We believe that studying these agents on a large scale offers valuable insights into their behaviors, capabilities, and potential risks. To facilitate research in this field, we implement and support various types of agents, tasks, prompts, models, and simulated environments.
machine-learning-research
The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.
COLD-Attack
COLD-Attack is a framework designed for controllable jailbreaks on large language models (LLMs). It formulates the controllable attack generation problem and utilizes the Energy-based Constrained Decoding with Langevin Dynamics (COLD) algorithm to automate the search of adversarial LLM attacks with control over fluency, stealthiness, sentiment, and left-right-coherence. The framework includes steps for energy function formulation, Langevin dynamics sampling, and decoding process to generate discrete text attacks. It offers diverse jailbreak scenarios such as fluent suffix attacks, paraphrase attacks, and attacks with left-right-coherence.
LLM-PLSE-paper
LLM-PLSE-paper is a repository focused on the applications of Large Language Models (LLMs) in Programming Language and Software Engineering (PL/SE) domains. It covers a wide range of topics including bug detection, specification inference and verification, code generation, fuzzing and testing, code model and reasoning, code understanding, IDE technologies, prompting for reasoning tasks, and agent/tool usage and planning. The repository provides a comprehensive collection of research papers, benchmarks, empirical studies, and frameworks related to the capabilities of LLMs in various PL/SE tasks.
AI_Hospital
AI Hospital is a research repository focusing on the interactive evaluation and collaboration of Large Language Models (LLMs) as intern doctors for clinical diagnosis. The repository includes a simulation module tailored for various medical roles, introduces the Multi-View Medical Evaluation (MVME) Benchmark, provides dialog history documents of LLMs, replication instructions, performance evaluation, and guidance for creating intern doctor agents. The collaborative diagnosis with LLMs emphasizes dispute resolution. The study was authored by Zhihao Fan, Jialong Tang, Wei Chen, Siyuan Wang, Zhongyu Wei, Jun Xie, Fei Huang, and Jingren Zhou.
PINNACLE
PINNACLE is a flexible geometric deep learning approach that trains on contextualized protein interaction networks to generate context-aware protein representations. It provides protein representations split across various cell-type contexts from different tissues and organs. The tool can be fine-tuned to study the genomic effects of drugs and nominate promising protein targets and cell-type contexts for further investigation. PINNACLE exemplifies the paradigm of incorporating context-specific effects for studying biological systems, especially the impact of disease and therapeutics.
oasis
OASIS is a scalable, open-source social media simulator that integrates large language models with rule-based agents to realistically mimic the behavior of up to one million users on platforms like Twitter and Reddit. It facilitates the study of complex social phenomena such as information spread, group polarization, and herd behavior, offering a versatile tool for exploring diverse social dynamics and user interactions in digital environments. With features like scalability, dynamic environments, diverse action spaces, and integrated recommendation systems, OASIS provides a comprehensive platform for simulating social media interactions at a large scale.
Youtube-playlist-to-formatted-text
This Python application, 'Youtube-playlist-to-formatted-text', utilizes the Google Gemini API to extract and refine transcripts from YouTube playlists. It offers various refinement styles such as Balanced and Detailed, Summary, Educational, Narrative Rewriting, and Q&A Generation. Users can control the chunk size for API calls, select Gemini models, and output the refined transcript as a formatted markdown file. The tool is designed to convert lengthy YouTube playlists into organized text files for easy readability and further processing, suitable for tasks like summarizing videos, creating study guides, and enhancing content comprehension.
examples
This repository contains a collection of sample applications and Jupyter Notebooks for hands-on experience with Pinecone vector databases and common AI patterns, tools, and algorithms. It includes production-ready examples for review and support, as well as learning-optimized examples for exploring AI techniques and building applications. Users can contribute, provide feedback, and collaborate to improve the resource.
FigStep
FigStep is a black-box jailbreaking algorithm against large vision-language models (VLMs). It feeds harmful instructions through the image channel and uses benign text prompts to induce VLMs to output contents that violate common AI safety policies. The tool highlights the vulnerability of VLMs to jailbreaking attacks, emphasizing the need for safety alignments between visual and textual modalities.
jailbreak_llms
This is the official repository for the ACM CCS 2024 paper 'Do Anything Now': Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models. The project employs a new framework called JailbreakHub to conduct the first measurement study on jailbreak prompts in the wild, collecting 15,140 prompts from December 2022 to December 2023, including 1,405 jailbreak prompts. The dataset serves as the largest collection of in-the-wild jailbreak prompts. The repository contains examples of harmful language and is intended for research purposes only.
awesome-llm-understanding-mechanism
This repository is a collection of papers focused on understanding the internal mechanism of large language models (LLM). It includes research on topics such as how LLMs handle multilingualism, learn in-context, and handle factual associations. The repository aims to provide insights into the inner workings of transformer-based language models through a curated list of papers and surveys.
UglyFeed
UglyFeed is a simple Python application designed to retrieve, aggregate, filter, rewrite, evaluate, and serve content (RSS feeds) written by a large language model. It provides features such as retrieving RSS feeds, aggregating feed items by similarity, rewriting content using various APIs, saving rewritten feeds to JSON files, converting JSON to valid RSS feed, serving XML feed via an HTTP server, deploying XML feed to GitHub or GitLab, and evaluating generated content. The tool can be used for smart content curation, dynamic blog generation, interactive educational tools, personalized reading experiences, brand monitoring, multilingual content delivery, enhanced RSS feeds, creative writing assistance, content repurposing, and fake news detection datasets. It is modular, extensible, and aims to empower users in content manipulation and delivery.
vidur
Vidur is a high-fidelity and extensible LLM inference simulator designed for capacity planning, deployment configuration optimization, testing new research ideas, and studying system performance of models under different workloads and configurations. It supports various models and devices, offers chrome trace exports, and can be set up using mamba, venv, or conda. Users can run the simulator with various parameters and monitor metrics using wandb. Contributions are welcome, subject to a Contributor License Agreement and adherence to the Microsoft Open Source Code of Conduct.
Awesome-Attention-Heads
Awesome-Attention-Heads is a platform providing the latest research on Attention Heads, focusing on enhancing understanding of Transformer structure for model interpretability. It explores attention mechanisms for behavior, inference, and analysis, alongside feed-forward networks for knowledge storage. The repository aims to support researchers studying LLM interpretability and hallucination by offering cutting-edge information on Attention Head Mining.
LLM-Tuning
LLM-Tuning is a collection of tools and resources for fine-tuning large language models (LLMs). It includes a library of pre-trained LoRA models, a set of tutorials and examples, and a community forum for discussion and support. LLM-Tuning makes it easy to fine-tune LLMs for a variety of tasks, including text classification, question answering, and dialogue generation. With LLM-Tuning, you can quickly and easily improve the performance of your LLMs on downstream tasks.