Best AI tools for< Search Topics >

Perplexica is an AI-powered search tool designed to help users discover content within a library efficiently. The tool utilizes advanced algorithms to provide accurate and relevant search results, making it easier for users to find the information they need quickly and easily. With a user-friendly interface and powerful search capabilities, Perplexica is a valuable tool for researchers, students, and anyone looking to access information within a library or database.

JRE.AI is an AI-powered tool designed for Joe Rogan Experience podcast enthusiasts. It offers interactive timestamps and AI-generated transcripts for over 2,400 episodes, enabling users to easily navigate and explore specific topics and moments within conversations. With detailed summaries and analysis, the platform provides a comprehensive listening experience for the audience.

EduHunt is an AI-powered search engine that helps users find quality educational content on YouTube. It allows users to search for specific topics and filters the results to show only the most relevant and high-quality videos. EduHunt also offers a variety of features to help users customize their search results, such as the ability to filter by language, duration, and difficulty level.

The website is a platform that offers an AI Video Search Engine. Users can index videos, sign in, and explore topics related to the human brain, Supabase, startups, AI image generation, and the future of startups. The platform has indexed 17270 videos totaling 277741 minutes. Users can also view the code on Github or follow the creator.

Felo Search is a free AI search engine developed by Sparticle Inc. It utilizes artificial intelligence technology to provide users with accurate and relevant search results. The platform is designed to enhance the search experience by understanding user queries and delivering personalized results. Felo Search aims to revolutionize the way people search for information online by leveraging AI algorithms to improve search efficiency and effectiveness.

Farro is an innovative search engine that utilizes AI technology to generate instant videos based on user searches. It offers a unique way to explore information by creating engaging video content in under a minute. Users can browse the internet, search for relevant media, and even upload files to convert them into videos. Farro is designed to provide up-to-date answers, educational content, in-depth explanations, and the ability to transform text-based information into visually appealing video presentations. The platform offers both free and premium options for users to access advanced features and unlimited video creations.

Talpa Search is a search engine developed by LibraryThing that allows users to search for books, movies, music, and various other topics. Users can search for a wide range of queries, from specific book quotes to movie genres. The platform aims to provide a comprehensive search experience for users looking to explore different media and topics.

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.

Exa is a web API designed to provide AI applications with powerful access to the web by organizing and retrieving the best content using embeddings. It offers features like semantic search, similarity search, content scraping, and powerful filters to help developers and companies gather and process data for AI training and analysis. Exa is trusted by thousands of developers and companies for its speed, quality, and ability to provide up-to-date information from various sources on the web.

Goover is a personalized AI research agent that streamlines the process of acquiring knowledge by providing self-driving experiences. It offers users the ability to dive deeper into various topics through curated briefings, reports, and insights. Goover utilizes advanced AI technology to deliver tailored answers, identify key information, and facilitate meaningful discussions. Users can access knowledge anytime, anywhere through the mobile app, ensuring they stay informed and engaged with their passions. With Goover, users can track specific topics, receive automatic updates, and explore diverse perspectives effortlessly.

Yesber is an AI-powered search engine that utilizes advanced algorithms to provide users with relevant and up-to-date information on a wide range of topics. The platform is designed to streamline the process of finding valuable content online by leveraging machine learning and natural language processing technologies. Users can simply enter their query, and Yesber will generate comprehensive search results from reputable sources across the web. With its user-friendly interface and intelligent search capabilities, Yesber aims to revolutionize the way people discover and access information online.

Deepfind is a privacy-first AI search engine that prioritizes user data protection. It allows users to conduct searches without the use of cookies, tracking, or storing personal information. Deepfind aims to provide a secure and efficient search experience while maintaining user privacy and data security.

Explore AI is a semantic search engine that utilizes artificial intelligence technology to enhance search capabilities. The platform allows users to search for information in a more intuitive and context-aware manner, making it easier to find relevant content quickly. By leveraging AI algorithms, Explore AI provides a personalized search experience that adapts to the user's preferences and behavior. The platform aims to revolutionize the way people interact with search engines by offering advanced features and intelligent search capabilities.

Mees Ai is an advanced AI search and answer engine that allows users to explore AI with seamless search. The platform leverages cutting-edge technology, including GPT-4o, to provide accurate and relevant information on a wide range of topics. Users can search for anything from seasonal veggies to the latest iPhone show trends. Mees Ai aims to revolutionize the way people access information by offering a user-friendly interface and powerful AI capabilities.

KeyPush is an AI search tool that serves as your ultimate AI and web search companion. It utilizes advanced technologies such as Bing and ChatGPT to provide users with the most relevant search results. Users can easily find information on a wide range of topics, from the best phones in the world to the latest stock market trends and trending topics globally. KeyPush also allows users to stay updated on NASA's upcoming news and events. With its intelligent search capabilities, KeyPush aims to enhance the search experience for users seeking accurate and timely information.

MiniPerplx is a minimalistic AI-powered search engine designed to help users find information on the internet efficiently. With its intuitive interface, users can quickly search for a wide range of topics, from weather updates to sports events and even solve simple queries like counting the occurrences of specific letters in a word or understanding literary references. MiniPerplx aims to streamline the search process and provide users with accurate and relevant results in a fast and user-friendly manner.

Knowee is an AI-powered web application that provides 24/7 homework help, AI tutoring, and course notes. It offers high accuracy answers surpassing GPT-4 for various academic tasks. Users can upload images or drag and drop questions for assistance, get step-by-step solutions, and master diagrams. Knowee helps students review tough concepts, explore relevant questions, and enhance their grades across all subjects.

Open Knowledge Maps is the world's largest AI-based search engine for scientific knowledge. It aims to revolutionize discovery by increasing the visibility of research findings for science and society. The platform is open and nonprofit, based on the principles of open science, with a mission to create an inclusive, sustainable, and equitable infrastructure for all users. Users can map research topics with AI, find documents, and identify concepts to enhance their literature search experience.

The 'YouTube Comment Finder And AI Analysis' is a comprehensive web-based tool designed to simplify the process of searching, filtering, managing, and analyzing comments on YouTube videos. It empowers users to search, filter, sort, and analyze comments with ease, leveraging AI-powered comment analysis to gain insights into sentiment, trending topics, key points, and concise summaries of comments. The tool offers features such as comment search, filtering, sorting, exporting, and random comment picking, making it a valuable asset for content creators, marketers, and individuals looking to navigate the vast sea of comments on YouTube videos.

Kore.ai is an AI application that offers a wide range of conversational AI solutions for various industries such as financial services, healthcare, retail, and more. The platform provides features like automation, contact center AI, agent AI, search AI, and document segmentation. With a focus on customer, employee, and agent experiences, Kore.ai aims to optimize interactions through AI technologies. The platform also offers resources like blog posts, whitepapers, webinars, and technical documentation to support users in leveraging AI for their businesses.

The 'vector-search-class-notes' repository contains class materials for a course on Long Term Memory in AI, focusing on vector search and databases. The course covers theoretical foundations and practical implementation of vector search applications, algorithms, and systems. It explores the intersection of Artificial Intelligence and Database Management Systems, with topics including text embeddings, image embeddings, low dimensional vector search, dimensionality reduction, approximate nearest neighbor search, clustering, quantization, and graph-based indexes. The repository also includes information on the course syllabus, project details, selected literature, and contributions from industry experts in the field.

The 'awesome-ai-web-search' repository is a curated list of AI-powered web search software that focuses on the intersection of Large Language Models (LLMs) and web search capabilities. It contains a timeline of various software supporting web search with LLM summarization, chat capabilities, and agent-driven research. The repository showcases both open-source and closed-source tools, providing a comprehensive overview of AI web search solutions available in the market.

Awesome-AI-Coding is a curated list of AI coding topics, projects, datasets, LLM models, embedding models, papers, blogs, products, startups, and peer awesome lists related to artificial intelligence in coding. It includes tools for code completion, code generation, code documentation, and code search, as well as AI models and techniques for improving developer productivity. The repository also features information on various AI-powered developer tools, copilots, and related resources in the AI coding domain.

pyLLMSearch is an advanced RAG system that offers a convenient question-answering system with a simple YAML-based configuration. It enables interaction with multiple collections of local documents, with improvements in document parsing, hybrid search, chat history, deep linking, re-ranking, customizable embeddings, and more. The package is designed to work with custom Large Language Models (LLMs) from OpenAI or installed locally. It supports various document formats, incremental embedding updates, dense and sparse embeddings, multiple embedding models, 'Retrieve and Re-rank' strategy, HyDE (Hypothetical Document Embeddings), multi-querying, chat history, and interaction with embedded documents using different models. It also offers simple CLI and web interfaces, deep linking, offline response saving, and an experimental API.

This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access a GPT model (gpt-35-turbo), and Azure AI Search for data indexing and retrieval. The repo includes sample data so it's ready to try end to end. In this sample application we use a fictitious company called Contoso Electronics, and the experience allows its employees to ask questions about the benefits, internal policies, as well as job descriptions and roles.

This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access the ChatGPT model (gpt-35-turbo), and Azure AI Search for data indexing and retrieval.

The AI Workshop repository provides a comprehensive guide to utilizing OpenAI's APIs, including Chat Completion, Embedding, and Assistant APIs. It offers hands-on demonstrations and code examples to help users understand the capabilities of these APIs. The workshop covers topics such as creating interactive chatbots, performing semantic search using text embeddings, and building custom assistants with specific data and context. Users can enhance their understanding of AI applications in education, research, and other domains through practical examples and usage notes.

This repository focuses on Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs). It provides code and resources to augment LLMs with real-time data for dynamic, context-aware applications. The content covers topics such as semantic search, fine-tuning embeddings, building RAG chatbots, evaluating LLMs, and using knowledge graphs in RAG. Prerequisites include Python skills, knowledge of machine learning and LLMs, and introductory experience with NLP and AI models.

Discourse-air is a clean and modern theme for forums, featuring light and dark modes, clickable topics, loading slider, search banner, and category + group boxes. Users need to enable specific settings for the theme components to render properly. It offers customization options for color schemes, search banner placement, and category organization.

Hands-On Large Language Models is a repository containing code examples from the book 'The Illustrated LLM Book' by Jay Alammar and Maarten Grootendorst. The repository provides practical tools and concepts for using Large Language Models with over 250 custom-made figures. It covers topics such as language model introduction, tokens and embeddings, transformer LLMs, text classification, text clustering, prompt engineering, text generation techniques, semantic search, multimodal LLMs, text embedding models, fine-tuning representation models, and fine-tuning generation models. The examples are designed to be run on Google Colab with T4 GPU support, but can be adapted to other cloud platforms as well.

This repository introduces and helps organizations get started with building AI Apps and incorporating Large Language Models (LLMs) into them. The workshop covers topics such as prompt engineering, AI orchestration, and deploying AI apps. Participants will learn how to use Azure OpenAI, Langchain/ Semantic Kernel, Qdrant, and Azure AI Search to build intelligent applications.

Agently Daily News Collector is an open-source project showcasing a workflow powered by the Agent ly AI application development framework. It allows users to generate news collections on various topics by inputting the field topic. The AI agents automatically perform the necessary tasks to generate a high-quality news collection saved in a markdown file. Users can edit settings in the YAML file, install Python and required packages, input their topic idea, and wait for the news collection to be generated. The process involves tasks like outlining, searching, summarizing, and preparing column data. The project dependencies include Agently AI Development Framework, duckduckgo-search, BeautifulSoup4, and PyYAM.

A curated repository of code recipes, demos, and resources for basic and advanced Redis use cases in the AI ecosystem. It includes demos for ArxivChatGuru, Redis VSS, Vertex AI & Redis, Agentic RAG, ArXiv Search, and Product Search. Recipes cover topics like Getting started with RAG, Semantic Cache, Advanced RAG, and Recommendation systems. The repository also provides integrations/tools like RedisVL, AWS Bedrock, LangChain Python, LangChain JS, LlamaIndex, Semantic Kernel, RelevanceAI, and DocArray. Additional content includes blog posts, talks, reviews, and documentation related to Vector Similarity Search, AI-Powered Document Search, Vector Databases, Real-Time Product Recommendations, and more. Benchmarks compare Redis against other Vector Databases and ANN benchmarks. Documentation includes QuickStart guides, official literature for Vector Similarity Search, Redis-py client library docs, Redis Stack documentation, and Redis client list.

The .NET AI Workshop is a comprehensive guide designed to help developers add AI features to .NET applications. It covers various AI-based features such as classification, summarization, data extraction/cleaning, anomaly detection, translation, sentiment detection, semantic search, Q&A chatbots, and voice assistants. The workshop is tailored for developers new to AI in .NET applications, focusing on the usage of AI services without the need for prior AI technology knowledge. It provides examples using .NET and C# with a focus on AI topics, aiming to enhance productivity and automation in applications.

This repository, Awesome-LLM-RAG, aims to record advanced papers on Retrieval Augmented Generation (RAG) in Large Language Models (LLMs). It serves as a resource hub for researchers interested in promoting their work related to LLM RAG by updating paper information through pull requests. The repository covers various topics such as workshops, tutorials, papers, surveys, benchmarks, retrieval-enhanced LLMs, RAG instruction tuning, RAG in-context learning, RAG embeddings, RAG simulators, RAG search, RAG long-text and memory, RAG evaluation, RAG optimization, and RAG applications.

LLM4Opt is a collection of references and papers focusing on applying Large Language Models (LLMs) for diverse optimization tasks. The repository includes research papers, tutorials, workshops, competitions, and related collections related to LLMs in optimization. It covers a wide range of topics such as algorithm search, code generation, machine learning, science, industry, and more. The goal is to provide a comprehensive resource for researchers and practitioners interested in leveraging LLMs for optimization tasks.

LLMInterviewQuestions is a repository containing over 100+ interview questions for Large Language Models (LLM) used by top companies like Google, NVIDIA, Meta, Microsoft, and Fortune 500 companies. The questions cover various topics related to LLMs, including prompt engineering, retrieval augmented generation, chunking, embedding models, internal working of vector databases, advanced search algorithms, language models internal working, supervised fine-tuning of LLM, preference alignment, evaluation of LLM system, hallucination control techniques, deployment of LLM, agent-based system, prompt hacking, and miscellaneous topics. The questions are organized into 15 categories to facilitate learning and preparation.

Hands-On Large Language Models CN(ZH) is a Chinese version of the book 'Hands-On Large Language Models' by Jay Alammar and Maarten Grootendorst. It provides detailed code annotations and additional insights, offers Notebook versions suitable for Chinese network environments, utilizes openbayes for free GPU access, allows convenient environment setup with vscode, and includes accompanying Chinese language videos on platforms like Bilibili and YouTube. The book covers various chapters on topics like Tokens and Embeddings, Transformer LLMs, Text Classification, Text Clustering, Prompt Engineering, Text Generation, Semantic Search, Multimodal LLMs, Text Embedding Models, Fine-tuning Models, and more.

STORM is a LLM system that writes Wikipedia-like articles from scratch based on Internet search. While the system cannot produce publication-ready articles that often require a significant number of edits, experienced Wikipedia editors have found it helpful in their pre-writing stage. **Try out our [live research preview](https://storm.genie.stanford.edu/) to see how STORM can help your knowledge exploration journey and please provide feedback to help us improve the system 🙏!**

Milvus is an open-source vector database built to power embedding similarity search and AI applications. Milvus makes unstructured data search more accessible, and provides a consistent user experience regardless of the deployment environment. Milvus 2.0 is a cloud-native vector database with storage and computation separated by design. All components in this refactored version of Milvus are stateless to enhance elasticity and flexibility. For more architecture details, see Milvus Architecture Overview. Milvus was released under the open-source Apache License 2.0 in October 2019. It is currently a graduate project under LF AI & Data Foundation.

帮助用户查询头条热搜榜

Your Source for the Latest News in 24 Hours

Web search expert for news on specific topics and time ranges.

Skilled at crafting search-optimized, reader-appealing topics with meta descriptions.

I conjure advanced Google search queries.

Browse the web for the search term and summarize the results from sources

I'm Quora Search, specialized in finding Quora answers and insights.

Confident advisor for literature search, focusing on broad contexts.

Teaches you how to use the Metaphor Search API

Real-time search trends function like an app, providing live information on current trends. They display trending search terms in India in real-time and offer detailed web news information about the keywords selected by the user.

The Alien Word Search Generator 🔍🌌 🧩👽

Scientific therapist with web-search for fact-checking thoughts.

Public Domain PDF Books Finder GPT offers an expansive library of PDFs for easy search and download. It now specializes in finding public domain books from trusted sources.

Analyzes blog posts, suggests SEO topics. Link: https://goblinintheattic.com/

输入你要搜的关键词，或者丢一张图片，获取更多搜索灵感💡

中文论文指导和搜索助手

'검색엔진비서'는 Google, Youtube, Naver를 포함한 다양한 검색 엔진을 하나의 인터페이스를 통해 탐색할 수 있게 해주는 강력한 앱입니다.

Looper query strings assistant

Humorous meme finder focusing on TikTok, Instagram, and YouTube.

Summarize about the topic based on scientifically sound information