Best AI tools for< Reward 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 features a loyalty program that rewards users with points for gameplay duration, fostering engagement and retention. Gamelight's ROAS Algorithm identifies users with the highest likelihood of making a purchase on your game, providing exclusive access to valuable data points for effective 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.

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 contextual, predictive marketing promotions and special offers to drive customer engagement. Vouchery allows users to create, distribute, and manage promo campaigns efficiently, with capabilities to analyze data, maximize promo ROI, manage and collaborate on promotions, detect coupon abuse, and personalize incentives. Trusted by leading brands globally, Vouchery aims to help businesses scale their promotional infrastructure and prevent fraud through its headless architecture and machine learning technology.

Almonds Ai is a powerful and scalable AI-driven platform that focuses on channel engagement for businesses. It offers solutions such as B2B loyalty programs, interactive product learning, and hybrid/virtual events to enhance partner engagement and drive revenue growth. With features like platform customization, dedicated customer support, data & AI engine, and global recognition, Almonds Ai aims to deliver measurable conversions and return on experience for its users. The platform caters to various industries including technology, retail, auto, and banking, helping businesses engage, educate, and reward their channel partners effectively.

Saara Inc is an AI tool for eCommerce that focuses on maximizing profits by leveraging AI-powered automation and smart agents. The platform helps online stores increase profitability by addressing challenges such as high return rates, operational costs, and customer churn. By enhancing loyalty, reducing expenses, and streamlining processes through automation and AI, Saara enables businesses to achieve sustainable growth and long-term profitability.

Mighty Travels Premium is a platform that helps users save up to 90% on airfare tickets and hotels. Users can sign up for free to access exclusive deals and discounts. The website offers a range of travel-related content, including blog posts, customer testimonials, and a FAQ section. With Mighty Travels Premium, users can stay updated on the latest travel deals and maximize their travel rewards.

Bing Sign in Rewards is a loyalty program that allows users to earn points for using Bing search engine and other Microsoft products and services. Points can be redeemed for gift cards, merchandise, and other rewards.

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.

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.

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.

Community Hub is a free-to-use, AI-powered community management platform that helps you automate tasks, reward members, and keep your community engaged. With Community Hub, you can:

MyShell is an AI application that enables users to build, share, and own AI agents. It serves as a platform connecting users, creators, and open-source AI researchers. With MyShell, users can interact with AI friends and work companions, such as Shizuku and Emma 01 03, through voice and video conversations. The application empowers creators to leverage generative AI models to transform ideas into AI-native apps quickly. MyShell fosters a creator economy in the AI-native era, allowing anyone to become a creator, take ownership of their work, and be rewarded for their ideas.

Huntr is the world's first bug bounty platform for AI/ML. It provides a single place for security researchers to submit vulnerabilities, ensuring the security and stability of AI/ML applications, including those powered by Open Source Software (OSS).

Bagel is an AI & Cryptography Research Lab that focuses on making open source AI monetizable by leveraging novel cryptography techniques. Their innovative fine-tuning technology tracks the evolution of AI models, ensuring every contribution is rewarded. Bagel is built for autonomous AIs with large resource requirements and offers permissionless infrastructure for seamless information flow between machines and humans. The lab is dedicated to privacy-preserving machine learning through advanced cryptography schemes.

MeddiPop is an AI-powered platform that seamlessly connects patients with medical practices in various industries such as plastic surgery, dermatology, cosmetic dentistry, and ophthalmology. The application streamlines the process by allowing patients to submit applications for services, which are then matched with the most suitable practice using AI algorithms. MeddiPop aims to revolutionize healthcare by simplifying patient-practice connections and optimizing appointment scheduling.

The website 'What should I build next?' is a platform designed to help developers generate random development project ideas. It serves as the ultimate resource for developers seeking inspiration for their next project. Users can pick components or randomize to generate unique project ideas. The platform also offers a Challenge Mode for added excitement. Additionally, free credits are rewarded to active users daily, ensuring a continuous flow of ideas. The website aims to support developers in overcoming creative blocks and sparking innovation.

Zesh AI is an advanced AI-powered ecosystem that offers a range of innovative tools and solutions for Web3 projects, community managers, data analysts, and decision-makers. It leverages AI Agents and LLMs to redefine KOL analysis, community engagement, and campaign optimization. With features like InfluenceAI for KOL discovery, EngageAI for campaign management, IDAI for fraud detection, AnalyticsAI for data analysis, and Wallet & NFT Profile for community empowerment, Zesh AI provides cutting-edge solutions for various aspects of Web3 ecosystems.

Giftpack is a global gifting platform that offers a smart gifting service to help businesses make a unique impression through personalized experiences. The platform leverages data and design to strengthen relationships, automate gifting operations, boost retention, and drive recurring revenue. With a diverse global catalog, Giftpack provides branded merchandise, vouchers, and experiences sourced locally and globally. The platform also offers integrated automation, intelligent gift customization powered by AI, and a reward program system. Giftpack aims to simplify gifting processes and enhance engagement and retention within organizations.

Teachr is an online course creation platform that uses artificial intelligence to help users create and sell stunning courses. With Teachr, users can create interactive courses with 3D visuals, 360° perspectives, and augmented reality. They can also use speech recognition and AI voice-over technology to create engaging learning experiences. Teachr also offers a range of features to help users manage their courses, including a payment system, reward system, and fitness challenges. With Teachr, users can turn their expertise into a product that they can sell infinitely and create the perfect learning experience for their customers.

Charstar is an AI-powered platform where users can chat with virtual AI characters representing various personalities and backgrounds. Users can create chats with these characters, earn rewards, and explore a wide range of characters from different genres such as anime, movies, games, books, and more. The platform offers a unique and interactive experience for users to engage with AI characters and immerse themselves in storytelling and role-playing scenarios.

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.

Vision-LLM-Alignment is a repository focused on implementing alignment training for visual large language models (LLMs), including SFT training, reward model training, and PPO/DPO training. It supports various model architectures and provides datasets for training. The repository also offers benchmark results and installation instructions for users.

MM-RLHF is a comprehensive project for aligning Multimodal Large Language Models (MLLMs) with human preferences. It includes a high-quality MLLM alignment dataset, a Critique-Based MLLM reward model, a novel alignment algorithm MM-DPO, and benchmarks for reward models and multimodal safety. The dataset covers image understanding, video understanding, and safety-related tasks with model-generated responses and human-annotated scores. The reward model generates critiques of candidate texts before assigning scores for enhanced interpretability. MM-DPO is an alignment algorithm that achieves performance gains with simple adjustments to the DPO framework. The project enables consistent performance improvements across 10 dimensions and 27 benchmarks for open-source MLLMs.

FoR is the official code repository for the 'Flow of Reasoning: Training LLMs for Divergent Problem Solving with Minimal Examples' project. It formulates multi-step reasoning tasks as a flow, involving designing reward functions, collecting trajectories, and training LLM policies with trajectory balance loss. The code provides tools for training and inference in a reproducible experiment environment using conda. Users can choose from 5 tasks to run, each with detailed instructions in the respective branches.

ReST-MCTS is a reinforced self-training approach that integrates process reward guidance with tree search MCTS to collect higher-quality reasoning traces and per-step value for training policy and reward models. It eliminates the need for manual per-step annotation by estimating the probability of steps leading to correct answers. The inferred rewards refine the process reward model and aid in selecting high-quality traces for policy model self-training.

OREAL is a reinforcement learning framework designed for mathematical reasoning tasks, aiming to achieve optimal performance through outcome reward-based learning. The framework utilizes behavior cloning, reshaping rewards, and token-level reward models to address challenges in sparse rewards and partial correctness. OREAL has achieved significant results, with a 7B model reaching 94.0 pass@1 accuracy on MATH-500 and surpassing previous 32B models. The tool provides training tutorials and Hugging Face model repositories for easy access and implementation.

AceCoder is a tool that introduces a fully automated pipeline for synthesizing large-scale reliable tests used for reward model training and reinforcement learning in the coding scenario. It curates datasets, trains reward models, and performs RL training to improve coding abilities of language models. The tool aims to unlock the potential of RL training for code generation models and push the boundaries of LLM's coding abilities.

SatoshiVM Pioneers NFT is a collection of NFTs issued by SatoshiVM team to reward early contributors. The repository contains information about the NFT collection, including the contract address and winner list.

PURE (Process-sUpervised Reinforcement lEarning) is a framework that trains a Process Reward Model (PRM) on a dataset and fine-tunes a language model to achieve state-of-the-art mathematical reasoning capabilities. It uses a novel credit assignment method to calculate return and supports multiple reward types. The final model outperforms existing methods with minimal RL data or compute resources, achieving high accuracy on various benchmarks. The tool addresses reward hacking issues and aims to enhance long-range decision-making and reasoning tasks using large language models.

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.

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.

MedicalGPT is a training medical GPT model with ChatGPT training pipeline, implement of Pretraining, Supervised Finetuning, RLHF(Reward Modeling and Reinforcement Learning) and DPO(Direct Preference Optimization).

This competition is organized by Javier Rando and Florian Tramèr from the ETH AI Center and SPY Lab at ETH Zurich. The goal of the competition is to create a method that can detect universal backdoors in aligned language models. A universal backdoor is a secret suffix that, when appended to any prompt, enables the model to answer harmful instructions. The competition provides a set of poisoned generation models, a reward model that measures how safe a completion is, and a dataset with prompts to run experiments. Participants are encouraged to use novel methods for red-teaming, automated approaches with low human oversight, and interpretability tools to find the trojans. The best submissions will be offered the chance to present their work at an event during the SaTML 2024 conference and may be invited to co-author a publication summarizing the competition results.

This repository contains a list of EOS airdrops. Airdrops are a way for projects to distribute tokens to their community. They can be used to reward early adopters, promote the project, or raise funds. This repository includes airdrops for a variety of projects, including both new and established projects.

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!

The Alignment Handbook provides robust training recipes for continuing pretraining and aligning language models with human and AI preferences. It includes techniques such as continued pretraining, supervised fine-tuning, reward modeling, rejection sampling, and direct preference optimization (DPO). The handbook aims to fill the gap in public resources on training these models, collecting data, and measuring metrics for optimal downstream performance.

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.

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.

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