Best AI tools for< Rule-based Reasoning >

Bulk Rename Utility is a free online file renaming tool that combines AI and rule-based operations to efficiently rename multiple files or folders. Users can easily describe their renaming needs to the AI or apply customizable rules for batch renaming. The tool operates online, eliminating the need for file uploads and ensuring user privacy. With support for various file operations and diverse renaming rules, Bulk Rename Utility offers a user-friendly interface optimized for Chrome and Edge browsers on Windows and Mac systems.

Syntho is a self-service AI-generated Synthetic Data Platform that offers a comprehensive solution for generating synthetic data with high accuracy and privacy. It provides tools for de-identification, test data management, rule-based synthetic data generation, and more. Syntho aims to simplify data collaborations, streamline data sharing, and accelerate innovation by leveraging AI technology to create secure and nonsensitive synthetic data for various industries.

UiPath is a leading provider of robotic process automation (RPA) and artificial intelligence (AI) software. Its platform enables businesses to automate repetitive, rule-based tasks, freeing up employees to focus on more strategic initiatives. UiPath's AI capabilities allow businesses to further enhance their automation efforts by enabling robots to learn from data, make decisions, and interact with humans in a more natural way.

Gretel.ai is a synthetic data platform designed for Generative AI applications. It allows users to generate artificial datasets with the same characteristics as real data, enabling the improvement of AI models without compromising privacy. The platform offers various features such as building synthetic data pipelines, rule-based data transformation, measuring data quality, and customizing language models. Gretel.ai is suitable for industries like finance, healthcare, and the public sector, providing a secure and efficient solution for data generation and model enhancement.

LINQ Me Up is an AI-powered tool designed to boost .Net productivity by generating and converting LINQ queries efficiently. It offers fast and reliable conversion of SQL queries to LINQ code, transformation of LINQ code into SQL queries, and tailored LINQ queries for various datasets. The tool supports C# and Visual Basic code, Method and Query syntax, and utilizes AI-powered analysis for optimized results. LINQ Me Up is more versatile and powerful than rule-based or syntax conversions, enabling users to effortlessly migrate, build, and focus on essential code parts.

Graphlogic.ai is an AI-powered platform that offers Conversational AI solutions through text and voice bots. It provides partner-enabled services for various industries, including HR, customer support, marketing, and internal task management. The platform features AI-powered chatbots with goal-oriented NLU and rule-based bots, seamless integrations with CRM systems, and 24/7 omnichannel availability. Graphlogic.ai aims to transform and speed up customer service and FAQ conversations by providing instant replies in a human-like manner. It also offers dedicated HR manager bots, hiring assistants for mass recruitment, responsible managers for internal tasks, and outbound marketing coordinators.

Social Share is an all-in-one social tool that allows users to create bio link pages, shorten links, generate QR codes, create vCard links, and generate file links. It is a comprehensive platform that provides users with everything they need to manage their social media presence and online marketing efforts.

Watchdog is an AI-powered chat moderation tool designed to fully automate chat moderation for Telegram communities. It helps community owners tackle rulebreakers, trolls, and spambots effortlessly, ensuring consistent rule enforcement and user retention. With features like automatic monitoring, customizable rule enforcement, and quick setup, Watchdog offers significant cost savings and eliminates the need for manual moderation. The tool is developed by Ben, a solo developer, who created it to address the challenges he faced in managing his own community. Watchdog aims to save time, money, and enhance user experience by swiftly identifying and handling rule violations.

Ascent RLM is a regulatory lifecycle management platform that helps financial services companies identify, analyze, and manage regulatory obligations. It is composed of two integrated modules: AscentHorizon, a global horizon scanning tool, and AscentFocus, a regulatory mapping tool. Ascent RLM automates the regulatory mapping process, extracts individual obligations from regulatory text, and provides a centralized digital register of a firm's regulatory obligations. It also includes features such as side-by-side rule comparison, scenario planning, and audit trail.

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 Coupon & Discounts, Loyalty Program, Gift Cards & Vouchers, and Referral Program. The platform is AI-powered, providing contextual, predictive marketing promotions and special offers to drive customer engagement. Vouchery allows users to create, redeem, and synchronize all promotions, monitor campaign results, maximize promotional ROI, manage multiple budgets, and prevent coupon abuse. It also enables users to personalize promotions using a flexible rule engine and seamlessly integrate with major 3rd party services. The platform is trusted by leading brands across various industries and offers 24/7 customer support.

Rapid Claims AI is an autonomous medical coding and documentation solution powered by AI technology. It aims to streamline medical coding operations, reduce administrative costs, improve reimbursements, and ensure compliance for healthcare providers. The platform offers features like automated coding, personalized solutions, actionable insights, and customizable AI rule sets. Rapid Claims AI is designed to seamlessly integrate into existing workflows, catering to various healthcare setups and specialties. The application prioritizes security and privacy, with data encryption and secure cloud storage. It serves as a valuable tool for enhancing revenue cycle management processes in the healthcare industry.

Idea Hunt is an AI tool designed to help users uncover sales leads on Reddit by finding potential customers who are interested in reacting to ideas, solutions, and products. It utilizes advanced AI technologies, including GPT-4, to provide users with a platform to discover trends, find customers, and receive feedback. Idea Hunt offers features such as discovering potential customer leads, customized matching prompts, self-service matching rule optimization, comment assistance, and generating new revenue. The platform assists users in engaging with Reddit users effectively and converting them into paying customers, making it a valuable marketing tool for startups and large companies alike.

This repository contains the source code and datasets for Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs accepted to ACL 2024. It proposes a framework called Graph Chain-of-thought (Graph-CoT) to enable Language Models to traverse graphs step-by-step for reasoning, interaction, and execution. The motivation is to alleviate hallucination issues in Language Models by augmenting them with structured knowledge sources represented as graphs.

Nucleoid is a declarative (logic) runtime environment that manages both data and logic under the same runtime. It uses a declarative programming paradigm, which allows developers to focus on the business logic of the application, while the runtime manages the technical details. This allows for faster development and reduces the amount of code that needs to be written. Additionally, the sharding feature can help to distribute the load across multiple instances, which can further improve the performance of the system.

This repository does not provide a tool, but rather a collection of resources and strategies for academics in the field of artificial intelligence who are feeling depressed or overwhelmed by the rapid advancements in the field. The resources include articles, blog posts, and other materials that offer advice on how to cope with the challenges of working in a fast-paced and competitive environment.

This repository contains the implementation of Self-Play of Adversarial Language Game (SPAG) as described in the paper 'Self-playing Adversarial Language Game Enhances LLM Reasoning'. The SPAG involves training Language Models (LLMs) in an adversarial language game called Adversarial Taboo. The repository provides tools for imitation learning, self-play episode collection, and reinforcement learning on game episodes to enhance LLM reasoning abilities. The process involves training models using GPUs, launching imitation learning, conducting self-play episodes, assigning rewards based on outcomes, and learning the SPAG model through reinforcement learning. Continuous improvements on reasoning benchmarks can be observed by repeating the episode-collection and SPAG-learning processes.

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!

A repository that lists papers related to Large Language Model (LLM) based agents. The repository covers various topics including survey, planning, feedback & reflection, memory mechanism, role playing, game playing, tool usage & human-agent interaction, benchmark & evaluation, environment & platform, agent framework, multi-agent system, and agent fine-tuning. It provides a comprehensive collection of research papers on LLM-based agents, exploring different aspects of AI agent architectures and applications.

Awesome-LLM-in-Social-Science is a repository that compiles papers evaluating Large Language Models (LLMs) from a social science perspective. It includes papers on evaluating, aligning, and simulating LLMs, as well as enhancing tools in social science research. The repository categorizes papers based on their focus on attitudes, opinions, values, personality, morality, and more. It aims to contribute to discussions on the potential and challenges of using LLMs in social science research.

Avalon-LLM is a repository containing the official code for AvalonBench and the Avalon agent Strategist. AvalonBench evaluates Large Language Models (LLMs) playing The Resistance: Avalon, a board game requiring deductive reasoning, coordination, collaboration, and deception skills. Strategist utilizes LLMs to learn strategic skills through self-improvement, including high-level strategic evaluation and low-level execution guidance. The repository provides instructions for running AvalonBench, setting up Strategist, and conducting experiments with different agents in the game environment.

The W3C Cognitive AI Community Group focuses on advancing Cognitive AI through collaboration on defining use cases, open source implementations, and application areas. The group aims to demonstrate the potential of Cognitive AI in various domains such as customer services, healthcare, cybersecurity, online learning, autonomous vehicles, manufacturing, and web search. They work on formal specifications for chunk data and rules, plausible knowledge notation, and neural networks for human-like AI. The group positions Cognitive AI as a combination of symbolic and statistical approaches inspired by human thought processes. They address research challenges including mimicry, emotional intelligence, natural language processing, and common sense reasoning. The long-term goal is to develop cognitive agents that are knowledgeable, creative, collaborative, empathic, and multilingual, capable of continual learning and self-awareness.

This repository compiles a list of academic papers that evaluate, align, simulate, and provide surveys or perspectives on the use of Large Language Models (LLMs) in the field of Social Science. The papers cover various aspects of LLM research, including assessing their alignment with human values, evaluating their capabilities in tasks such as opinion formation and moral reasoning, and exploring their potential for simulating social interactions and addressing issues in diverse fields of Social Science. The repository aims to provide a comprehensive resource for researchers and practitioners interested in the intersection of LLMs and Social Science.

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.

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.

SheetCopilot is an assistant agent that manipulates spreadsheets by following user commands. It leverages Large Language Models (LLMs) to interact with spreadsheets like a human expert, enabling non-expert users to complete tasks on complex software such as Google Sheets and Excel via a language interface. The tool observes spreadsheet states, polishes generated solutions based on external action documents and error feedback, and aims to improve success rate and efficiency. SheetCopilot offers a dataset with diverse task categories and operations, supporting operations like entry & manipulation, management, formatting, charts, and pivot tables. Users can interact with SheetCopilot in Excel or Google Sheets, executing tasks like calculating revenue, creating pivot tables, and plotting charts. The tool's evaluation includes performance comparisons with leading LLMs and VBA-based methods on specific datasets, showcasing its capabilities in controlling various aspects of a spreadsheet.

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)

This repository contains a collection of papers and resources related to Large Language Models (LLMs), including their applications in various domains such as text generation, translation, question answering, and dialogue systems. The repository also includes discussions on the ethical and societal implications of LLMs. **Description** This repository is a collection of papers and resources related to Large Language Models (LLMs). LLMs are a type of artificial intelligence (AI) that can understand and generate human-like text. They have a wide range of applications, including text generation, translation, question answering, and dialogue systems. **For Jobs** - **Content Writer** - **Copywriter** - **Editor** - **Journalist** - **Marketer** **AI Keywords** - **Large Language Models** - **Natural Language Processing** - **Machine Learning** - **Artificial Intelligence** - **Deep Learning** **For Tasks** - **Generate text** - **Translate text** - **Answer questions** - **Engage in dialogue** - **Summarize text**

DriveLM is a multimodal AI model that enables autonomous driving by combining computer vision and natural language processing. It is designed to understand and respond to complex driving scenarios using visual and textual information. DriveLM can perform various tasks related to driving, such as object detection, lane keeping, and decision-making. It is trained on a massive dataset of images and text, which allows it to learn the relationships between visual cues and driving actions. DriveLM is a powerful tool that can help to improve the safety and efficiency of autonomous vehicles.

根据用户给出的背景设定，扩展出一篇规则类怪谈小说，让读者感到惊悚刺激

I generate creative business ideas based on a text about a problem, a news item, a topic, a reflection. The 3 Words Rule

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Generate your eslint rule

Expert in simplified financial rule engines.

Formal and concise golf rule expert with current rulebook access.

NFL rules expert with clear and concise responses.

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Machiavellian advisor to help you rule in business, politics and finance.

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Combines rule analysis with media insights.

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College Football Data and Rule Analyst in your pocket

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Provides campaign plots, character design and rule interpretations for tabletop RPG game masters.

Your Expert on the Official 2023 Golf Rules: Simply describe or upload an image of your play scenario, and receive precise, reliable guidance on the applicable rules. Perfect for players and enthusiasts seeking accurate and instant rule clarifications

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Discover the 80/20 in any situation.