Best AI tools for< Recall Information >

Unlost is a memory recall tool designed to help users effortlessly remember and retrieve information using natural language. It acts as a personal memory palace, eliminating the need for extensive note-taking or complex systems. Unlost intelligently records and organizes data, respecting user privacy by capturing content locally and offline. The tool offers quick access, powerful filtering capabilities, and familiar keyboard shortcuts for seamless user experience. With features like searching meeting transcripts, copying text from screenshots, and zero integration requirements, Unlost aims to simplify information retrieval and enhance productivity.

re:collect is an AI-powered tool that helps you enhance your memory, perception, and synthesis. It connects the information you consume and helps you quickly recall the right information when you need it. With re:collect, you can:

Essential is an open-source macOS app that acts as a co-pilot for your screen. It uses computer vision and OpenAI's LLMs to understand what's on your screen and can help you troubleshoot any error messages you run into. Essential can also remember important information from your screen, such as code snippets or website URLs, and make them easily accessible later. All of this happens entirely on your Mac, with no data ever leaving your system.

GuruPod is a mobile-native podcast AI platform that offers efficient transcription and intelligent interpretation services to help users 'smart read' podcasts. It addresses common challenges faced by podcast enthusiasts, such as low information retrieval efficiency, difficulty in accurately understanding audio content, lack of systematic organization in podcast content, and the inability to easily review and recall information. By leveraging AI technology, GuruPod aims to enhance the podcast listening experience by providing quick transcription, efficient content summarization, intelligent content structuring, and seamless integration with personal knowledge repositories. It also offers features like automatic keyword extraction, highlighting key content, recommending related materials, and providing convenient review functions.

Reflect is an AI-powered note-taking application designed to help users capture ideas, organize thoughts, and improve writing skills. The app offers features such as instant syncing across devices, networked notes with backlinks, end-to-end encryption, calendar integration, frictionless search, and AI assistance powered by GPT-4 and Whisper from OpenAI. Reflect aims to enhance users' note-taking experience by providing tools for transcribing voice notes, generating article outlines, listing key takeaways from meetings, fixing grammar and spelling errors, and more. The application focuses on creating a second brain for users to easily reference and recall information, making it a valuable tool for individuals seeking to boost productivity and creativity.

ChatPlayground AI is a versatile platform that allows users to compare multiple AI chatbots to obtain the best responses. With 14+ AI apps and features available, users can achieve better AI answers 73% of the time. The platform offers a comprehensive prompt library, real-time web search capabilities, image generation, history recall, document upload and analysis, and multilingual support. It caters to developers, data scientists, students, researchers, content creators, writers, and AI enthusiasts. Testimonials from users highlight the efficiency and creativity-enhancing benefits of using ChatPlayground AI.

Air is the world's first AI that can have full on 10-40 minute long phone calls that sound like a REAL human, with infinite memory, perfect recall, and can autonomously take actions across 5,000 plus applications. It can do the entire job of a full time agent without having to be trained, managed or motivated. It just works 24/7/365.

Gizmo is an AI-powered learning application designed to make studying easy and enjoyable for students of all levels. It offers A.I. quizzes that help users learn and retain information effectively. The app is created by Cambridge alumni and has gained popularity among students for its innovative approach to learning. With features like spaced repetition, active recall, and the ability to turn study materials into flashcards, Gizmo aims to enhance the learning experience and improve academic performance.

Recall is an AI-driven application that allows users to summarize and save any online content to their knowledge base. It automatically organizes and interlinks the saved content for easy rediscovery. Users can summarize podcasts, YouTube videos, news articles, PDFs, and more, and the application categorizes the content based on its mentions. Recall also helps users discover connections between different pieces of content by saving them in a knowledge graph. The application is praised by professionals for its AI-driven summarization and storage capabilities, boosting productivity and facilitating easy access to key details.

Recall is a web and mobile application that allows users to summarize and save any online content. It uses artificial intelligence to automatically categorize and connect saved content, making it easy to find and rediscover later. Recall also offers spaced repetition learning, data export, and offline access.

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.

Aimbly is an AI-powered meeting assistant that helps professionals quickly and accurately recall what was said in previous meetings, create summaries, action items, and ask questions about their meetings without compromising the security and privacy of their business.

NewWord is an AI-powered language learning tool designed to help users memorize and expand their vocabulary efficiently. It offers innovative features such as personalized word management solutions, AI-powered insights, and a unique traceability system. The application aims to make language learning more convenient and enjoyable by providing diversified review strategies and daily reminders. NewWord is suitable for individuals looking to enhance their linguistic skills through practical exercises and scenario-based learning modules.

Personal.ai is an AI application that offers a unique way for users to recall memories, exchange ideas, and strengthen relationships through AI messaging from their own personal AI. The platform allows users to create, publish, control, and deploy their AI, enabling them to interact with AI technology in a personalized and meaningful way. Personal.ai aims to democratize universal access to individuals and empower expertise by leveraging AI technology in various aspects of life.

Blanked is a free AI tool designed to help users find words they are struggling to recall. By providing a first letter and a casual description, users can utilize the power of AI to quickly locate the word they are blanking on. The platform aims to enhance vocabulary and assist users in never forgetting a word mid-conversation again. With an easy-to-use interface and free accessibility, Blanked is a valuable resource for anyone looking to boost their word-finding capabilities.

Song Identifier is an AI tool that helps users find a song by entering words from the lyrics. The tool utilizes AI technology to match the input lyrics with a vast database of songs, providing users with accurate results. Created with love by Pablo, Song Identifier aims to assist users in identifying songs stuck in their heads quickly and effortlessly.

Lamini is an enterprise-level LLM platform that offers precise recall with Memory Tuning, enabling teams to achieve over 95% accuracy even with large amounts of specific data. It guarantees JSON output and delivers massive throughput for inference. Lamini is designed to be deployed anywhere, including air-gapped environments, and supports training and inference on Nvidia or AMD GPUs. The platform is known for its factual LLMs and reengineered decoder that ensures 100% schema accuracy in the JSON output.

Mebot is an AI-powered application designed to help users enhance their memory and cognitive skills. By leveraging artificial intelligence technology, Mebot provides personalized memory training exercises and techniques to improve memory retention and recall. Users can track their progress, set reminders, and receive tailored recommendations to optimize their memory performance. With Mebot, users can enjoy a fun and engaging way to boost their memory capabilities and overall cognitive function.

Hana is an AI-powered Google Chat Assistant designed to enhance management efficiency by seamlessly integrating into Google Chat. It simplifies day-to-day tasks, boosts team productivity, and expands management capabilities. Hana acts as an intelligent teammate, offering step-by-step guidance, clear explanations, and actionable steps in group chat environments. It assists in tasks like code generation, concept clarification, QnA over web content, memory recall, document analysis, reminders, image intelligence, and more. Hana is a productivity machine that transforms workflows and ensures informed discussions and decisions.

Warp is a terminal reimagined with AI and collaborative tools for better productivity. It is built with Rust for speed and has an intuitive interface. Warp includes features such as modern editing, command generation, reusable workflows, and Warp Drive. Warp AI allows users to ask questions about programming and get answers, recall commands, and debug errors. Warp Drive helps users organize hard-to-remember commands and share them with their team. Warp is a private and secure application that is trusted by hundreds of thousands of professional developers.

OmniChain is a tool for building efficient self-updating visual workflows using AI language models, enabling users to automate tasks, create chatbots, agents, and integrate with existing frameworks. It allows users to create custom workflows guided by logic processes, store and recall information, and make decisions based on that information. The tool enables users to create tireless robot employees that operate 24/7, access the underlying operating system, generate and run NodeJS code snippets, and create custom agents and logic chains. OmniChain is self-hosted, open-source, and available for commercial use under the MIT license, with no coding skills required.

L3AGI is an open-source tool that enables AI Assistants to collaborate together as effectively as human teams. It provides a robust set of functionalities that empower users to design, supervise, and execute both autonomous AI Assistants and Teams of Assistants. Key features include the ability to create and manage Teams of AI Assistants, design and oversee standalone AI Assistants, equip AI Assistants with the ability to retain and recall information, connect AI Assistants to an array of data sources for efficient information retrieval and processing, and employ curated sets of tools for specific tasks. L3AGI also offers a user-friendly interface, APIs for integration with other systems, and a vibrant community for support and collaboration.

LangCorn is an API server that enables you to serve LangChain models and pipelines with ease, leveraging the power of FastAPI for a robust and efficient experience. It offers features such as easy deployment of LangChain models and pipelines, ready-to-use authentication functionality, high-performance FastAPI framework for serving requests, scalability and robustness for language processing applications, support for custom pipelines and processing, well-documented RESTful API endpoints, and asynchronous processing for faster response times.

SurfSense is a tool designed to help users save and organize content from the internet into a personal Knowledge Graph. It allows users to capture web browsing sessions and webpage content using a Chrome extension, enabling easy retrieval and recall of saved information. SurfSense offers features like powerful search capabilities, natural language interaction with saved content, self-hosting options, and integration with GraphRAG for meaningful content relations. The tool eliminates the need for web scraping by directly reading data from the DOM, making it a convenient solution for managing online information.

The enhance_llm repository contains three main parts: 1. Vector model domain fine-tuning based on llama_index and qwen fine-tuning BGE vector model. 2. Large model domain fine-tuning based on PEFT fine-tuning qwen1.5-7b-chat, with sft and dpo. 3. High-order retrieval enhanced generation (RAG) system based on the above domain work, implementing a two-stage RAG system. It includes query rewriting, recall reordering, retrieval reordering, multi-turn dialogue, and more. The repository also provides hardware and environment configurations along with star history and licensing information.

wdoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It aims to handle large volumes of diverse document types, making it ideal for researchers, students, and professionals dealing with extensive information sources. wdoc uses LangChain to process and analyze documents, supporting tens of thousands of documents simultaneously. The system includes features like high recall and specificity, support for various Language Model Models (LLMs), advanced RAG capabilities, advanced document summaries, and support for multiple tasks. It offers markdown-formatted answers and summaries, customizable embeddings, extensive documentation, scriptability, and runtime type checking. wdoc is suitable for power users seeking document querying capabilities and AI-powered document summaries.

OpenRecall is a fully open-source, privacy-first tool that captures your digital history through snapshots, making it searchable for quick access to specific information. It offers transparency, cross-platform support, privacy focus, and hardware compatibility. Features include time travel, local-first AI, semantic search, and full control over storage. The roadmap includes visual search capabilities and audio transcription. Users can easily install and run OpenRecall to enhance memory and productivity without compromising privacy.

Zep is a long-term memory service for AI Assistant apps. With Zep, you can provide AI assistants with the ability to recall past conversations, no matter how distant, while also reducing hallucinations, latency, and cost. Zep persists and recalls chat histories, and automatically generates summaries and other artifacts from these chat histories. It also embeds messages and summaries, enabling you to search Zep for relevant context from past conversations. Zep does all of this asyncronously, ensuring these operations don't impact your user's chat experience. Data is persisted to database, allowing you to scale out when growth demands. Zep also provides a simple, easy to use abstraction for document vector search called Document Collections. This is designed to complement Zep's core memory features, but is not designed to be a general purpose vector database. Zep allows you to be more intentional about constructing your prompt: 1. automatically adding a few recent messages, with the number customized for your app; 2. a summary of recent conversations prior to the messages above; 3. and/or contextually relevant summaries or messages surfaced from the entire chat session. 4. and/or relevant Business data from Zep Document Collections.

This repository provides a sample solution for building generative AI agents using Amazon Bedrock, Amazon DynamoDB, Amazon Kendra, Amazon Lex, and LangChain. The solution creates a generative AI financial services agent capable of assisting users with account information, loan applications, and answering natural language questions. It serves as a launchpad for developers to create personalized conversational agents for applications like chatbots and virtual assistants.

Awesome-LLM-RAG-Application is a repository that provides resources and information about applications based on Large Language Models (LLM) with Retrieval-Augmented Generation (RAG) pattern. It includes a survey paper, GitHub repo, and guides on advanced RAG techniques. The repository covers various aspects of RAG, including academic papers, evaluation benchmarks, downstream tasks, tools, and technologies. It also explores different frameworks, preprocessing tools, routing mechanisms, evaluation frameworks, embeddings, security guardrails, prompting tools, SQL enhancements, LLM deployment, observability tools, and more. The repository aims to offer comprehensive knowledge on RAG for readers interested in exploring and implementing LLM-based systems and products.

RAG-FiT is a library designed to improve Language Models' ability to use external information by fine-tuning models on specially created RAG-augmented datasets. The library assists in creating training data, training models using parameter-efficient finetuning (PEFT), and evaluating performance using RAG-specific metrics. It is modular, customizable via configuration files, and facilitates fast prototyping and experimentation with various RAG settings and configurations.

Sycamore is a conversational search and analytics platform for complex unstructured data, such as documents, presentations, transcripts, embedded tables, and internal knowledge repositories. It retrieves and synthesizes high-quality answers through bringing AI to data preparation, indexing, and retrieval. Sycamore makes it easy to prepare unstructured data for search and analytics, providing a toolkit for data cleaning, information extraction, enrichment, summarization, and generation of vector embeddings that encapsulate the semantics of data. Sycamore uses your choice of generative AI models to make these operations simple and effective, and it enables quick experimentation and iteration. Additionally, Sycamore uses OpenSearch for indexing, enabling hybrid (vector + keyword) search, retrieval-augmented generation (RAG) pipelining, filtering, analytical functions, conversational memory, and other features to improve information retrieval.

Auto-News is an automatic news aggregator tool that utilizes Large Language Models (LLM) to pull information from various sources such as Tweets, RSS feeds, YouTube videos, web articles, Reddit, and journal notes. The tool aims to help users efficiently read and filter content based on personal interests, providing a unified reading experience and organizing information effectively. It features feed aggregation with summarization, transcript generation for videos and articles, noise reduction, task organization, and deep dive topic exploration. The tool supports multiple LLM backends, offers weekly top-k aggregations, and can be deployed on Linux/MacOS using docker-compose or Kubernetes.

Rageval is an evaluation tool for Retrieval-augmented Generation (RAG) methods. It helps evaluate RAG systems by performing tasks such as query rewriting, document ranking, information compression, evidence verification, answer generation, and result validation. The tool provides metrics for answer correctness and answer groundedness, along with benchmark results for ASQA and ALCE datasets. Users can install and use Rageval to assess the performance of RAG models in question-answering tasks.

Benchmark various LLM Structured Output frameworks like Instructor, Mirascope, Langchain, LlamaIndex, Fructose, Marvin, Outlines, LMFormatEnforcer, etc on tasks like multi-label classification, named entity recognition, synthetic data generation. The tool provides benchmark results, methodology, instructions to run the benchmark, add new data, and add a new framework. It also includes a roadmap for framework-related tasks, contribution guidelines, citation information, and feedback request.

WDoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It supports querying tens of thousands of documents simultaneously, offers tailored summaries to efficiently manage large amounts of information, and includes features like supporting multiple file types, various LLMs, local and private LLMs, advanced RAG capabilities, advanced summaries, trust verification, markdown formatted answers, sophisticated embeddings, extensive documentation, scriptability, type checking, lazy imports, caching, fast processing, shell autocompletion, notification callbacks, and more. WDoc is ideal for researchers, students, and professionals dealing with extensive information sources.

RAGFlow is an open-source Retrieval-Augmented Generation (RAG) engine that combines deep document understanding with Large Language Models (LLMs) to provide accurate question-answering capabilities. It offers a streamlined RAG workflow for businesses of all sizes, enabling them to extract knowledge from unstructured data in various formats, including Word documents, slides, Excel files, images, and more. RAGFlow's key features include deep document understanding, template-based chunking, grounded citations with reduced hallucinations, compatibility with heterogeneous data sources, and an automated and effortless RAG workflow. It supports multiple recall paired with fused re-ranking, configurable LLMs and embedding models, and intuitive APIs for seamless integration with business applications.

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

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.

Recall data on auto, consumer, and food product recalls

Give me a link to something you read and I'll ask you good questions to help recall and retain content.

A note-taking assistant that reads and recalls from images.

Memory-enhancing games.

Informative and safety-focused guide on consumer product recalls.

Creates Active Recall questions from uploaded study materials, exported in a pdf.

Create comprehension questions based on a shared text. These questions will be designed to assess understanding at different levels of Bloom's taxonomy, from basic recall to more complex analytical and evaluative thinking skills.

Can't quite remember that thought you had? Use this GPT to help guide you back to your memory.

Aide in recalling and piecing together memories.

I assist in recalling that elusive word or name at the tip of your tongue.

Lucid dreaming expert trained on the latest techniques - learn how to dream in the age of abundance

A look back at past events.

Friendly assistant for storing/recalling personal memories.

Your Therapeutic Guide to the World of Dreams

Informs about product recalls in various industries, focusing on consumer safety.

优化笔记内容，使其更有用、易读

Coach for investment banking technical interviews