Best AI tools for< Reward User Loyalty >

Gamelight is a revolutionary AI platform for mobile games marketing. It utilizes advanced algorithms to analyze app usage data and users' behavior, creating detailed user profiles and delivering personalized game recommendations. The platform also includes a loyalty program that rewards users for gameplay duration, fostering retention and engagement. Gamelight's ROAS Algorithm identifies users with the highest likelihood of making a purchase on your game, providing a competitive advantage in user acquisition.

PurplePro is an AI-powered loyalty club platform designed to help businesses launch and manage loyalty programs effortlessly. With features like referral management, streaks, quizzes, variable rewards, and automated triggers, PurplePro aims to enhance customer engagement, retention, and acquisition. The platform offers advanced customization and segmentation options, making it suitable for direct-to-consumer (D2C) brands looking to boost customer loyalty and increase revenue. PurplePro's AI capabilities enable users to create and implement effective loyalty campaigns in just a few clicks, without the need for coding knowledge. The platform also provides a seamless integration with Shopify, making it easy for businesses to set up and activate their loyalty programs.

Gensbot is an innovative platform that empowers users to create personalized goods on demand. By leveraging advanced AI technology, Gensbot eliminates the hassle of searching, stressing, or second-guessing, offering a seamless and convenient online shopping experience. Users can simply prompt the AI with their desired product specifications, and Gensbot will generate unique designs tailored to their preferences. This user-centric approach extends to the production process, where Gensbot prioritizes local manufacturing to minimize shipping distances and carbon emissions, contributing to a greener planet. Additionally, Gensbot rewards users with tokens for every purchase, which can be redeemed for future designs or exclusive offers, fostering a sustainable and rewarding shopping experience.

The Advantage Club is an AI-powered Employee Engagement Platform that offers solutions for workforce engagement through various features such as recognition, marketplace, wellness, incentive automation, communities, and pulse tracking. It digitizes rewarding processes, curates personalized vouchers and gifts, elevates well-being with a holistic wellness platform, automates sales contests, fosters inclusion through communities, and captures employee sentiments through surveys and quizzes. The platform integrates with global HRIS and communication tools, provides real-time analytics, and offers a seamless user experience for both employees and administrators.

Text Enhancer is a free online AI-powered tool that helps users enhance and improve their writing. It offers a range of features, including text enhancement, rewriting, and advanced paraphrasing capabilities. The tool is designed to be user-friendly and provides quick and efficient assistance to refine and elevate the quality of writing. Text Enhancer is ideal for students, professionals, and everyday writers who want to improve the clarity, eliminate redundancy, and ensure their writing is impactful and engaging.

Smartwithpoints.com is a website that focuses on rewarding users with points for various activities. Users are required to verify their identity before proceeding, ensuring a secure connection. The site emphasizes the importance of enabling JavaScript and cookies to enhance user experience. Powered by Cloudflare, smartwithpoints.com prioritizes performance and security for its users.

Brave is a privacy-focused web browser that prioritizes user experience by blocking ads, trackers, and unwanted content. It offers features such as Shields, VPN, Leo AI Wallet, Rewards, Playlist, News Talk, and advanced privacy settings. Brave aims to provide a faster and more secure browsing experience while protecting user data and privacy. The browser is built on the open-source Chromium Web core and offers a private search engine called Brave Search. With a focus on user-first design, Brave is designed to save time, data, and battery life for its users.

Catizen is an AI-powered application that combines gaming, blockchain technology, and artificial intelligence to create a unique virtual world for users and their digital companions, AI kitties. With features like mini-games, user acquisition tasks, and blockchain-powered gaming, Catizen offers a fun and interactive experience for players. The application is designed to provide entertainment, user engagement, and rewards through a seamless integration of AI technology and gaming elements.

Infinilearn is a personalized learning platform that revolutionizes education by offering gamified and interactive learning experiences. It features a customized AI Guide that grows with the user, providing personalized learning paths, gamified level system, earning grants directly through the app, and human-AI powered symbiosis. Infinilearn aims to make learning engaging, rewarding, and tailored to individual needs.

TravelFeed is a comprehensive travel blogging platform that allows users to create and share travel stories, connect with fellow travelers, and earn rewards through blogging. The platform offers a range of features including free blog creation, custom maps, AI-powered content creation tools, fast article delivery, and cryptocurrency earnings. TravelFeed is optimized for travelers and provides a user-friendly experience for both novice and experienced bloggers.

Answerthis is an AI-powered Q&A platform that connects users with experts in various fields. It allows users to ask questions and receive personalized answers from a global community of experts. Answerthis covers a wide range of topics, including business, technology, science, health, and more. The platform is designed to be user-friendly and accessible, making it easy for anyone to find the information they need.

Yoursearch.ai is an AI-powered search engine web application that aims to revolutionize internet research by providing users with better search results without any advertising. With features like a new Messenger service, summarized and relevant search results, and the ability to share findings with family and friends, Yoursearch.ai offers a user-friendly and efficient search experience. The application also emphasizes user control and personalization, allowing users to get only the most relevant information. Yoursearch.ai is committed to protecting minors and offers a service for age verification on websites with adult content. Overall, Yoursearch.ai is a smart search tool that leverages artificial intelligence to enhance productivity and knowledge discovery.

Questflow is a decentralized AI agent economy platform that allows users to orchestrate multiple AI agents to gather insights, take action, and earn rewards autonomously. It offers a user-friendly dashboard, visual reports, smart keyword generator, content evaluation, SEO goal setting, automated alerts, actionable SEO tips, and link optimization wizard. The platform aims to automate repetitive tasks for knowledge workers in a private and safety-first approach, providing a co-pilot for work. Users can dispatch tasks to AI agents in groups and incentivize them for completing tasks. Questflow also rewards AI agent creators and supporters through revenue sharing and staking incentives, fostering a community-driven ecosystem.

Moot is an innovative application that allows users to share their thoughts and opinions on any website or link without limitations. It provides a platform for open discussion and interaction, enabling users to engage with content across the web freely and express their views in a community-driven environment. Moot's cutting-edge features are designed to enhance the browsing experience and facilitate meaningful interactions, making it an essential tool for anyone looking to engage with online content in a more dynamic and engaging way.

Questflow is a decentralized AI agent economy platform that enables users to orchestrate multiple AI agents to gather insights, take action, and earn rewards autonomously. It serves as a co-pilot for work, helping knowledge workers automate repetitive tasks in a private and safety-first approach. The platform offers user-friendly dashboards, visual reports, smart keyword generators, content evaluation, SEO goal setting, automated alerts, actionable SEO tips, and link optimization wizards. Users can dispatch tasks to AI agents in groups and take action on tasks automatically through decentralized multi-agent orchestration. Questflow also facilitates the distribution of economic incentives to creators and guardians of AI agents via a blockchain network, rewarding them for their contributions to the future of work.

PTool is an AI application that offers various AI tools and features to users. Users can generate AI art, change outfits in photos, swap faces, create AI girls, and more using the advanced AI technology provided by PTool. The application is designed to be user-friendly and fun, allowing users to create unique pictures and videos with ease. PTool is developed by Hong Kong Vision World AI Limited and offers an affiliate program for users to earn rewards. The application also ensures user privacy and security through its strict privacy policy and terms of service.

BET4D is a trusted online platform for Toto 4D and Togel games, offering a wide range of features and benefits for players. It provides a complete and rewarding experience with the chance to win big jackpots. With a variety of games and generous prize promotions, BET4D aims to bring excitement and nostalgia to players, ensuring quick withdrawal processes and a user-friendly interface. As the first in Asia and Indonesia, BET4D stands out with its extensive game selection and attractive rewards, promising a thrilling gaming experience and numerous opportunities for winning. The platform is designed to cater to players' needs and preferences, making it a popular choice for online Toto and Togel enthusiasts.

KODOKTOTO is an online platform for playing various types of online lottery games. It offers a user-friendly interface for players to register, login, and access live chat support. Players can enjoy bonuses upon registration and engage in lottery games through the platform. KODOKTOTO aims to provide a convenient and entertaining experience for online lottery enthusiasts.

Vouchery.io is an all-in-one promotional engine designed to help businesses orchestrate and deliver the right incentives at every stage of the customer lifecycle. It offers features such as Coupons & Discounts, Loyalty Program, Gift Cards & Vouchers, and Referral Program. The platform is AI-powered, enabling users to manage and automate coupon distribution efficiently. Vouchery.io aims to maximize promotional ROI, prevent coupon abuse, and personalize promotions through a flexible rule engine. Trusted by leading brands worldwide, Vouchery.io provides a programmable Coupon API, 24/7 customer support, and a headless architecture for seamless integration across platforms.

Perspect is an AI-powered platform designed for high-performance software teams. It offers real-time insights into team contributions and impact, optimizing developer experience, and rewarding high-performers. With 50+ integrations, Perspect enables visualization of impact, benchmarking performance, and uses machine learning models to identify and eliminate blockers. The platform is deeply integrated with web3 wallets and offers built-in reward mechanisms. Managers can align resources around crucial KPIs, identify top talent, and prevent burnout. Perspect aims to enhance team productivity and employee retention through AI and ML technologies.

ChatGPT Queue Prompts is a collection of prompt chains designed to enhance interactions with large language models like ChatGPT. These prompt chains help build context for the AI before performing specific tasks, improving performance. Users can copy and paste prompt chains into the ChatGPT Queue extension to process prompts in sequence. The repository includes example prompt chains for tasks like conducting AI company research, building SEO optimized blog posts, creating courses, revising resumes, enriching leads for CRM, personal finance document creation, workout and nutrition plans, marketing plans, and more.

This repository contains code for training reward models for Deep Reinforcement Learning-based Reward-modulated Hierarchical Fine-tuning (DRL-based RLHF), Iterative Selection Fine-tuning (Rejection sampling fine-tuning), and iterative Decision Policy Optimization (DPO). The reward models are trained using a Bradley-Terry model based on the Gemma and Mistral language models. The resulting reward models achieve state-of-the-art performance on the RewardBench leaderboard for reward models with base models of up to 13B parameters.

This repository, RLHF-Reward-Modeling, is dedicated to training reward models for DRL-based RLHF (PPO), Iterative SFT, and iterative DPO. It provides state-of-the-art performance in reward models with a base model size of up to 13B. The installation instructions involve setting up the environment and aligning the handbook. Dataset preparation requires preprocessing conversations into a standard format. The code can be run with Gemma-2b-it, and evaluation results can be obtained using provided datasets. The to-do list includes various reward models like Bradley-Terry, preference model, regression-based reward model, and multi-objective reward model. The repository is part of iterative rejection sampling fine-tuning and iterative DPO.

This is a super customizable, concise, user-friendly, and efficient toolkit for training and aligning LLMs. It provides support for various methods such as SFT, Distillation, DPO, ORPO, CPO, SimPO, SMPO, Non-pair Reward Modeling, Special prompts basket format, Rejection Sampling, Scoring using RM, Effective FAISS Map-Reduce Deduplication, LLM scoring using RM, NER, CLIP, Classification, and STS. The toolkit offers key libraries like PyTorch, Transformers, TRL, Accelerate, FSDP, DeepSpeed, and tools for result logging with wandb or clearml. It allows mixing datasets, generation and logging in wandb/clearml, vLLM batched generation, and aligns models using the SMPO method.

h2oGPT is an Apache V2 open-source project that allows users to query and summarize documents or chat with local private GPT LLMs. It features a private offline database of any documents (PDFs, Excel, Word, Images, Video Frames, Youtube, Audio, Code, Text, MarkDown, etc.), a persistent database (Chroma, Weaviate, or in-memory FAISS) using accurate embeddings (instructor-large, all-MiniLM-L6-v2, etc.), and efficient use of context using instruct-tuned LLMs (no need for LangChain's few-shot approach). h2oGPT also offers parallel summarization and extraction, reaching an output of 80 tokens per second with the 13B LLaMa2 model, HYDE (Hypothetical Document Embeddings) for enhanced retrieval based upon LLM responses, a variety of models supported (LLaMa2, Mistral, Falcon, Vicuna, WizardLM. With AutoGPTQ, 4-bit/8-bit, LORA, etc.), GPU support from HF and LLaMa.cpp GGML models, and CPU support using HF, LLaMa.cpp, and GPT4ALL models. Additionally, h2oGPT provides Attention Sinks for arbitrarily long generation (LLaMa-2, Mistral, MPT, Pythia, Falcon, etc.), a UI or CLI with streaming of all models, the ability to upload and view documents through the UI (control multiple collaborative or personal collections), Vision Models LLaVa, Claude-3, Gemini-Pro-Vision, GPT-4-Vision, Image Generation Stable Diffusion (sdxl-turbo, sdxl) and PlaygroundAI (playv2), Voice STT using Whisper with streaming audio conversion, Voice TTS using MIT-Licensed Microsoft Speech T5 with multiple voices and Streaming audio conversion, Voice TTS using MPL2-Licensed TTS including Voice Cloning and Streaming audio conversion, AI Assistant Voice Control Mode for hands-free control of h2oGPT chat, Bake-off UI mode against many models at the same time, Easy Download of model artifacts and control over models like LLaMa.cpp through the UI, Authentication in the UI by user/password via Native or Google OAuth, State Preservation in the UI by user/password, Linux, Docker, macOS, and Windows support, Easy Windows Installer for Windows 10 64-bit (CPU/CUDA), Easy macOS Installer for macOS (CPU/M1/M2), Inference Servers support (oLLaMa, HF TGI server, vLLM, Gradio, ExLLaMa, Replicate, OpenAI, Azure OpenAI, Anthropic), OpenAI-compliant, Server Proxy API (h2oGPT acts as drop-in-replacement to OpenAI server), Python client API (to talk to Gradio server), JSON Mode with any model via code block extraction. Also supports MistralAI JSON mode, Claude-3 via function calling with strict Schema, OpenAI via JSON mode, and vLLM via guided_json with strict Schema, Web-Search integration with Chat and Document Q/A, Agents for Search, Document Q/A, Python Code, CSV frames (Experimental, best with OpenAI currently), Evaluate performance using reward models, and Quality maintained with over 1000 unit and integration tests taking over 4 GPU-hours.

Mosec is a high-performance and flexible model serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. * **Highly performant** : web layer and task coordination built with Rust 🦀, which offers blazing speed in addition to efficient CPU utilization powered by async I/O * **Ease of use** : user interface purely in Python 🐍, by which users can serve their models in an ML framework-agnostic manner using the same code as they do for offline testing * **Dynamic batching** : aggregate requests from different users for batched inference and distribute results back * **Pipelined stages** : spawn multiple processes for pipelined stages to handle CPU/GPU/IO mixed workloads * **Cloud friendly** : designed to run in the cloud, with the model warmup, graceful shutdown, and Prometheus monitoring metrics, easily managed by Kubernetes or any container orchestration systems * **Do one thing well** : focus on the online serving part, users can pay attention to the model optimization and business logic

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

Proactive Agent is a project aimed at constructing a fully active agent that can anticipate user's requirements and offer assistance without explicit requests. It includes a data collection and generation pipeline, automatic evaluator, and training agent. The project provides datasets, evaluation scripts, and prompts to finetune LLM for proactive agent. Features include environment sensing, assistance annotation, dynamic data generation, and construction pipeline with a high F1 score on the test set. The project is intended for coding, writing, and daily life scenarios, distributed under Apache License 2.0.

LLaMA Factory is a unified framework for fine-tuning 100+ large language models (LLMs) with various methods, including pre-training, supervised fine-tuning, reward modeling, PPO, DPO and ORPO. It features integrated algorithms like GaLore, BAdam, DoRA, LongLoRA, LLaMA Pro, LoRA+, LoftQ and Agent tuning, as well as practical tricks like FlashAttention-2, Unsloth, RoPE scaling, NEFTune and rsLoRA. LLaMA Factory provides experiment monitors like LlamaBoard, TensorBoard, Wandb, MLflow, etc., and supports faster inference with OpenAI-style API, Gradio UI and CLI with vLLM worker. Compared to ChatGLM's P-Tuning, LLaMA Factory's LoRA tuning offers up to 3.7 times faster training speed with a better Rouge score on the advertising text generation task. By leveraging 4-bit quantization technique, LLaMA Factory's QLoRA further improves the efficiency regarding the GPU memory.

ZORA AIO is a software tool designed for interacting with the ZORA.CO ecosystem, offering extensive customization options, a wide range of contracts, and user-friendly settings. Users can perform various tasks related to NFT minting, bridging, gas management, token transactions, and more. The tool requires Python 3.10.10 for operation and provides detailed guidance on installation and usage. It includes features such as official and instant bridges, minting NFTs on different networks, creating ERC1155 contracts, updating NFT metadata, and more. Users can configure private keys and proxies in the _data_ folder and adjust settings in the _settings.py_ file. ZORA AIO is suitable for users looking to streamline their interactions within the ZORA.CO ecosystem.

STILL is an open-source project exploring slow-thinking reasoning systems, focusing on o1-like reasoning systems. The project has released technical reports on enhancing LLM reasoning with reward-guided tree search algorithms and implementing slow-thinking reasoning systems using an imitate, explore, and self-improve framework. The project aims to replicate the capabilities of industry-level reasoning systems by fine-tuning reasoning models with long-form thought data and iteratively refining training datasets.

The 𝓜𝓔𝓥-𝓑𝓞𝓣 is a revolutionary tool that empowers users to maximize their ETH earnings through advanced slippage techniques within the Ethereum ecosystem. Its user-centric design, optimized earning mechanism, and comprehensive security measures make it an indispensable tool for traders seeking to enhance their crypto trading strategies. With its current free access, there's no better time to explore the 𝓜𝓔𝓥-𝓑𝓞𝓣's capabilities and witness the transformative impact it can have on your crypto trading journey.

LLM Reasoners is a library that enables LLMs to conduct complex reasoning, with advanced reasoning algorithms. It approaches multi-step reasoning as planning and searches for the optimal reasoning chain, which achieves the best balance of exploration vs exploitation with the idea of "World Model" and "Reward". Given any reasoning problem, simply define the reward function and an optional world model (explained below), and let LLM reasoners take care of the rest, including Reasoning Algorithms, Visualization, LLM calling, and more!

Xwin-LM is a powerful and stable open-source tool for aligning large language models, offering various alignment technologies like supervised fine-tuning, reward models, reject sampling, and reinforcement learning from human feedback. It has achieved top rankings in benchmarks like AlpacaEval and surpassed GPT-4. The tool is continuously updated with new models and features.

PsyDI is a multi-modal and interactive chatbot designed for psychological assessments. It aims to explore users' cognitive styles through interactive analysis of their inputs, ultimately determining their Myers-Briggs Type Indicator (MBTI). The chatbot offers customized feedback and detailed analysis for each user, with upcoming features such as an MBTI gallery. Users can access PsyDI directly online to begin their journey of self-discovery.

The repository 'Awesome-LLM-Preference-Learning' is the official repository of a survey paper titled 'Towards a Unified View of Preference Learning for Large Language Models: A Survey'. It contains a curated list of papers related to preference learning for Large Language Models (LLMs). The repository covers various aspects of preference learning, including on-policy and off-policy methods, feedback mechanisms, reward models, algorithms, evaluation techniques, and more. The papers included in the repository explore different approaches to aligning LLMs with human preferences, improving mathematical reasoning in LLMs, enhancing code generation, and optimizing language model performance.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

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

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, ,'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in less than 3 words,Verb + noun form,in daily spoken language,in lowercase letters).Answer in english languagesname:Awesome-Chinese-LLM readme:# Awesome Chinese LLM   An Awesome Collection for LLM in Chinese 收集和梳理中文LLM相关    自ChatGPT为代表的大语言模型（Large Language Model, LLM）出现以后，由于其惊人的类通用人工智能（AGI）的能力，掀起了新一轮自然语言处理领域的研究和应用的浪潮。尤其是以ChatGLM、LLaMA等平民玩家都能跑起来的较小规模的LLM开源之后，业界涌现了非常多基于LLM的二次微调或应用的案例。本项目旨在收集和梳理中文LLM相关的开源模型、应用、数据集及教程等资料，目前收录的资源已达100+个！ 如果本项目能给您带来一点点帮助，麻烦点个⭐️吧～ 同时也欢迎大家贡献本项目未收录的开源模型、应用、数据集等。提供新的仓库信息请发起PR，并按照本项目的格式提供仓库链接、star数，简介等相关信息，感谢~

OpenRL is an open-source general reinforcement learning research framework that supports training for various tasks such as single-agent, multi-agent, offline RL, self-play, and natural language. Developed based on PyTorch, the goal of OpenRL is to provide a simple-to-use, flexible, efficient and sustainable platform for the reinforcement learning research community. It supports a universal interface for all tasks/environments, single-agent and multi-agent tasks, offline RL training with expert dataset, self-play training, reinforcement learning training for natural language tasks, DeepSpeed, Arena for evaluation, importing models and datasets from Hugging Face, user-defined environments, models, and datasets, gymnasium environments, callbacks, visualization tools, unit testing, and code coverage testing. It also supports various algorithms like PPO, DQN, SAC, and environments like Gymnasium, MuJoCo, Atari, and more.

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