Best AI tools for< Recommendation Generation >

Pinecone is a vector database designed to help power AI applications for various companies. It offers a serverless platform that enables users to build knowledgeable AI applications quickly and cost-effectively. With Pinecone, users can perform low-latency vector searches for tasks such as search, recommendation, detection, and more. The platform is scalable, secure, and cloud-native, making it suitable for a wide range of AI projects.

Bibit AI is a real estate marketing AI designed to enhance the efficiency and effectiveness of real estate marketing and sales. It can help create listings, descriptions, and property content, and offers a host of other features. Bibit AI is the world's first AI for Real Estate. We are transforming the real estate industry by boosting efficiency and simplifying tasks like listing creation and content generation.

Telescope is an AI-driven lead generation platform that helps businesses find potential customers quickly and efficiently. By utilizing natural language search and next-gen search and recommendation features, Telescope allows users to generate targeted lead lists in seconds. With access to a vast global data network and advanced prospect-search capabilities, Telescope streamlines the prospecting process and provides valuable insights for sales and business development teams. The platform is designed to enhance productivity and effectiveness in lead generation activities, offering a user-friendly experience for companies of all sizes.

Chat Blackbox is an AI tool that specializes in AI code generation, code chat, and code search. It provides a platform where users can interact with AI to generate code, discuss code-related topics, and search for specific code snippets. The tool leverages artificial intelligence algorithms to enhance the coding experience and streamline the development process. With Chat Blackbox, users can access a wide range of features to improve their coding skills and efficiency.

Blackbox is an AI-powered code generation, code chat, and code search tool that helps developers write better code faster. With Blackbox, you can generate code snippets, chat with an AI assistant about code, and search for code examples from a massive database.

Pinecone is a vector database that helps power AI for the world's best companies. It is a serverless database that lets you deliver remarkable GenAI applications faster, at up to 50x lower cost. Pinecone is easy to use and can be integrated with your favorite cloud provider, data sources, models, frameworks, and more.

Brisk Teaching is a free AI tool designed for teachers to streamline their workflow and enhance their teaching practices. It offers a wide range of AI-powered features to provide personalized feedback, create engaging presentations and quizzes, analyze student writing, and generate various educational resources. Brisk Teaching aims to save teachers time and effort by automating tasks such as feedback generation, curriculum creation, and assessment. Trusted by over 400,000 educators, Brisk Teaching is actively used in 20,000 school districts worldwide.

Minduck is an AI-powered generating platform that helps users unleash their creativity and productivity. It offers features such as automatic analysis of words, recommendation of creation types, visualizations of ideas, and deepening of concepts with AI. Trusted by users from various backgrounds, Minduck simplifies tasks like image generation, content creation, and idea expansion. With its intuitive human creativity and AI efficiency, Minduck aims to assist users in taking the first step beyond ideas and turning them into reality.

Askimo is a premier AI services platform that offers a wide range of AI tools and recommendations to users. It provides services such as AI Recommendations, AI Recommendation Wizard, AI Consultation, and more. Users can access various AI services for tasks like Presentation, Web Design, Text-to-Speech, Image Generation, Search Engine Optimization, Music Composing, Image Editing, and Logo Design. Askimo aims to simplify the process of finding and utilizing AI services, connecting users with AI professionals for tailored solutions.

GPTMyDay is an AI-powered application that helps users plan their day efficiently. By leveraging ChatGPT's AI technology, users can input their preferences and receive personalized daily plans, saving time and effort. The application offers features like activity recommendations, plan generation, plan review, and personalized history tracking. With GPTMyDay, users can explore new activities, restaurants, and hotels hassle-free, making their daily experiences more enjoyable and organized.

Generative.ai is an AI tool designed for Salesforce consultants to enhance productivity and efficiency in creating solutions, estimates, and proposals. The tool leverages AI technology to generate detailed proposals in minutes, provide commercial insights, and recommend product features based on extensive data processing. It aims to streamline the proposal creation process and improve accuracy through AI-assisted enhancement.

Plantrips is an AI-powered travel planner that helps users create custom travel itineraries in minutes. With Plantrips, users can generate itineraries for specific destinations, budgets, and travel styles. Plantrips also provides users with recommendations for activities, restaurants, and accommodations. The platform is free to use and is available online and as a mobile app.

LeadShark is an AI-powered B2B sales automation tool that helps businesses automate lead generation processes. By using a Browser Extension powered by AI, LeadShark enables users to sit back and watch high-quality leads roll into their sales funnel. The tool offers features such as automated lead generation, opportunity dashboard for sales metrics, integrations with favorite browsers, and a Go-to-Market Strategy Template for enhancing marketing strategies. LeadShark aims to address the continuous need for finding high-quality leads in outbound sales by providing automated lead generation solutions based on the user's Ideal Customer Profile criteria.

novita.ai is an AI-assisted tool designed to aid developers in code generation tasks. It offers a state-of-the-art large language model, Code Llama, which provides intelligent recommendations and transforms the coding experience. The platform leverages advancements in machine learning to enhance developers' productivity and accuracy in writing error-free code.

Yep AI is an AI-powered platform that offers digital human solutions to businesses, allowing them to enhance customer engagement, optimize product recommendations, and provide personalized shopping experiences. The platform enables users to create their own personalized AI avatars to provide real-time assistance to customers. With seamless implementation and advanced artificial intelligence capabilities, Yep AI aims to revolutionize customer service and boost conversions for businesses across various industries.

Obviyo is a product-led growth platform that helps e-commerce businesses increase revenue by matching products to shoppers based on real-time behavior. It uses AI to identify buying signals from individual shoppers and link them with products of interest. Obviyo's suite of AI-powered Growth Bots, cross-platform data, and real-time AI algorithms enable businesses to personalize the shopping experience, upsell and cross-sell products, optimize product merchandising, and acquire new customers. Obviyo integrates with Shopify and Amazon, and has a track record of delivering strong customer results for global brands.

Quiz Makito is an innovative AI quiz generation platform that leverages AI technology to streamline the quiz creation process. It offers a range of features, from gamified quizzes to personalized recommendations, to enhance the learning experience. With regular updates and high-quality design, Quiz Makito aims to provide users with engaging and interactive quizzes on various topics, powered by cutting-edge AI algorithms.

AI Hairstyle is an AI-powered online platform that offers a virtual hairstyle transformation experience. Users can explore various hairstyles and hair colors using the AI hairstyle generator and color changer. The platform provides personalized hairstyle suggestions and allows users to try on different looks virtually. With features like free storage, users can save their generated images in the cloud for easy access. AI Hairstyle aims to make experimenting with new hairstyles effortless and fun.

Clevis is a platform that allows users to build and sell AI-powered applications without the need for coding. With a variety of pre-built processing steps, users can create apps with features like text generation, image generation, and web scraping. Clevis provides an easy-to-use editor, templates, sharing options, and API integration to help users launch their AI-powered apps quickly. The platform also offers customization options, data upload capabilities, and the ability to schedule app runs. Clevis offers a free trial period and flexible pricing plans to cater to different user needs.

VirtualFantasy.ai is an AI-powered virtual companion platform that utilizes advanced artificial intelligence algorithms to provide users with personalized assistance and companionship. The platform offers a wide range of features such as virtual conversations, emotional support, task reminders, entertainment recommendations, and personalized insights. VirtualFantasy.ai aims to enhance users' daily lives by offering a virtual companion that can engage in meaningful interactions and provide support whenever needed.

chromem-go is an embeddable vector database for Go with a Chroma-like interface and zero third-party dependencies. It enables retrieval augmented generation (RAG) and similar embeddings-based features in Go apps without the need for a separate database. The focus is on simplicity and performance for common use cases, allowing querying of documents with minimal memory allocations. The project is in beta and may introduce breaking changes before v1.0.0.

The Next-Generation LLM-based Recommender Systems Survey is a comprehensive overview of the latest advancements in recommender systems leveraging Large Language Models (LLMs). The survey covers various paradigms, approaches, and applications of LLMs in recommendation tasks, including generative and non-generative models, multimodal recommendations, personalized explanations, and industrial deployment. It discusses the comparison with existing surveys, different paradigms, and specific works in the field. The survey also addresses challenges and future directions in the domain of LLM-based recommender systems.

A collection of papers related to knowledge distillation of large language models (LLMs). The repository focuses on techniques to transfer advanced capabilities from proprietary LLMs to smaller models, compress open-source LLMs, and refine their performance. It covers various aspects of knowledge distillation, including algorithms, skill distillation, verticalization distillation in fields like law, medical & healthcare, finance, science, and miscellaneous domains. The repository provides a comprehensive overview of the research in the area of knowledge distillation of LLMs.

This repository is a collection of papers and resources related to recommendation systems, focusing on foundation models, transferable recommender systems, large language models, and multimodal recommender systems. It explores questions such as the necessity of ID embeddings, the shift from matching to generating paradigms, and the future of multimodal recommender systems. The papers cover various aspects of recommendation systems, including pretraining, user representation, dataset benchmarks, and evaluation methods. The repository aims to provide insights and advancements in the field of recommendation systems through literature reviews, surveys, and empirical studies.

This paper list is about Large Language Model-enhanced Recommender System. It also contains some related works. Keywords: recommendation system, large language models

This repository contains a curated list of resources on generative information retrieval, including research papers, datasets, tools, and applications. Generative information retrieval is a subfield of information retrieval that uses generative models to generate new documents or passages of text that are relevant to a given query. This can be useful for a variety of tasks, such as question answering, summarization, and document generation. The resources in this repository are intended to help researchers and practitioners stay up-to-date on the latest advances in generative information retrieval.

TheCodersGig is an AI-powered open-source social network platform for developers, facilitating seamless connection and collaboration. It features an integrated utility marketplace for creating plugins easily, automating backend development with scalable code. The user-friendly interface supports API integration, data models, databases, authentication, and authorization. The platform's architecture includes frontend, backend, AI services, database, marketplace, security, and DevOps layers, enabling customization and diverse integrations. Key components encompass technologies like React.js, Node.js, Python-based AI frameworks, SQL/NoSQL databases, payment gateways, security protocols, and DevOps tools for automation and scalability.

Studio B3 (B-3 Bomber) is a sophisticated editor designed for content creation, catering to various formats such as blogs, articles, user stories, and more. It provides an immersive content generation experience with local AI capabilities for intelligent search and recommendation functions. Users can define custom actions and variables for flexible content generation. The editor includes interactive tools like Bubble Menu, Slash Command, and Quick Insert for enhanced user experience in editing, searching, and navigation. The design principles focus on intelligent embedding of AI, local optimization for efficient writing experience, and context flexibility for better control over AI-generated content.

This repository contains a collection of AI projects covering various areas of machine learning. Each project is accompanied by detailed articles on the associated blog sciblog. Projects range from introductory topics like Convolutional Neural Networks and Transfer Learning to advanced topics like Fraud Detection and Recommendation Systems. The repository also includes tutorials on data generation, distributed training, natural language processing, and time series forecasting. Additionally, it features visualization projects such as football match visualization using Datashader.

The LLMEvaluation repository is a comprehensive compendium of evaluation methods for Large Language Models (LLMs) and LLM-based systems. It aims to assist academics and industry professionals in creating effective evaluation suites tailored to their specific needs by reviewing industry practices for assessing LLMs and their applications. The repository covers a wide range of evaluation techniques, benchmarks, and studies related to LLMs, including areas such as embeddings, question answering, multi-turn dialogues, reasoning, multi-lingual tasks, ethical AI, biases, safe AI, code generation, summarization, software performance, agent LLM architectures, long text generation, graph understanding, and various unclassified tasks. It also includes evaluations for LLM systems in conversational systems, copilots, search and recommendation engines, task utility, and verticals like healthcare, law, science, financial, and others. The repository provides a wealth of resources for evaluating and understanding the capabilities of LLMs in different domains.

MicroLens is a content-driven micro-video recommendation dataset at scale. It provides a large dataset with multimodal data, including raw text, images, audio, video, and video comments, for tasks such as multi-modal recommendation, foundation model building, and fairness recommendation. The dataset is available in two versions: MicroLens-50K and MicroLens-100K, with extracted features for multimodal recommendation tasks. Researchers can access the dataset through provided links and reach out to the corresponding author for the complete dataset. The repository also includes codes for various algorithms like VideoRec, IDRec, and VIDRec, each implementing different video models and baselines.

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.

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.

KDB.AI is a time-based vector database that allows developers to build scalable, reliable, and real-time applications by providing advanced search, recommendation, and personalization for Generative AI applications. It supports multiple index types, distance metrics, top-N and metadata filtered retrieval, as well as Python and REST interfaces. The repository contains samples demonstrating various use-cases such as temporal similarity search, document search, image search, recommendation systems, sentiment analysis, and more. KDB.AI integrates with platforms like ChatGPT, Langchain, and LlamaIndex. The setup steps require Unix terminal, Python 3.8+, and pip installed. Users can install necessary Python packages and run Jupyter notebooks to interact with the samples.

SuperSonic is a next-generation BI platform that integrates Chat BI (powered by LLM) and Headless BI (powered by semantic layer) paradigms. This integration ensures that Chat BI has access to the same curated and governed semantic data models as traditional BI. Furthermore, the implementation of both paradigms benefits from the integration: * Chat BI's Text2SQL gets augmented with context-retrieval from semantic models. * Headless BI's query interface gets extended with natural language API. SuperSonic provides a Chat BI interface that empowers users to query data using natural language and visualize the results with suitable charts. To enable such experience, the only thing necessary is to build logical semantic models (definition of metric/dimension/tag, along with their meaning and relationships) through a Headless BI interface. Meanwhile, SuperSonic is designed to be extensible and composable, allowing custom implementations to be added and configured with Java SPI. The integration of Chat BI and Headless BI has the potential to enhance the Text2SQL generation in two dimensions: 1. Incorporate data semantics (such as business terms, column values, etc.) into the prompt, enabling LLM to better understand the semantics and reduce hallucination. 2. Offload the generation of advanced SQL syntax (such as join, formula, etc.) from LLM to the semantic layer to reduce complexity. With these ideas in mind, we develop SuperSonic as a practical reference implementation and use it to power our real-world products. Additionally, to facilitate further development we decide to open source SuperSonic as an extensible framework.

Deej-A.I. is an advanced machine learning project that aims to revolutionize music recommendation systems by using artificial intelligence to analyze and recommend songs based on their content and characteristics. The project involves scraping playlists from Spotify, creating embeddings of songs, training neural networks to analyze spectrograms, and generating recommendations based on similarities in music features. Deej-A.I. offers a unique approach to music curation, focusing on the 'what' rather than the 'how' of DJing, and providing users with personalized and creative music suggestions.

This repository is dedicated to collecting and categorizing papers related to Retrieval-Augmented Generation (RAG) for AI-generated content. It serves as a survey repository based on the paper 'Retrieval-Augmented Generation for AI-Generated Content: A Survey'. The repository is continuously updated to keep up with the rapid growth in the field of RAG.

Godot LLM is a plugin that enables the utilization of large language models (LLM) for generating content in games. It provides functionality for text generation, text embedding, multimodal text generation, and vector database management within the Godot game engine. The plugin supports features like Retrieval Augmented Generation (RAG) and integrates llama.cpp-based functionalities for text generation, embedding, and multimodal capabilities. It offers support for various platforms and allows users to experiment with LLM models in their game development projects.

CoLLM is a novel method that integrates collaborative information into Large Language Models (LLMs) for recommendation. It converts recommendation data into language prompts, encodes them with both textual and collaborative information, and uses a two-step tuning method to train the model. The method incorporates user/item ID fields in prompts and employs a conventional collaborative model to generate user/item representations. CoLLM is built upon MiniGPT-4 and utilizes pretrained Vicuna weights for training.

Expert in dark romance style, offers makeup and attire recommendations with image generation.

Caters to the Health and Nutrition Needs of the Baby Boomer Generation.This includes Support for Managing Age-Related Dietary Needs, Promoting Heart and Joint Health, and Enhancing Cognitive Function.

Your expert in limitless, detailed scientific data analysis and reporting

I cannot share free OpenAI API keys. https://gptsapp123.com

原创选题市场趋势与建议

A counselor aiding in writing recommendation letters for PhD applications, with a formal and informative tone.

Expert in drafting recommendation letters for U.S. green card application under EB-1A and EB2-NIW applications. Please start from the conversation starters but with the info of yourself.

为您找到想要的酒店，请说您的要求Finds hotels in China with preferd demand

Given a set of Parameters, Provides a set of Order Recommendations

Ask me to recommend a plugin or script from the official Hex-Rays plugin repository

Finds the best Shopify app for your requirements and budget

A movie and TV show , Songs & Books recommendation assistant for various streaming platforms.

The best non-fiction book recommendation assistant.

Expert on Twitter's recommendation algorithm with code insights.

Expert in personalized content discovery and recommendation.

Detailed facial analysis advisor with Mogwarts recommendation.

Crafts detailed, formal letters of recommendation.

AI for GPU, CPU, memory, and storage recommendation

帮我找到一部有意思的想要看的电影推荐