Best AI tools for< Solve Reasoning Puzzles >

Choosy Chat is an AI-powered chat application that utilizes advanced AI models such as OpenAI GPT-4o and Google Gemini Pro 1.5 to provide intelligent responses and engage in meaningful conversations with users. The application is designed to assist users in various tasks, including answering questions, providing information on recent knowledge, coding assistance, and reasoning puzzles. Choosy Chat aims to enhance user experience through its cutting-edge AI technology and user-friendly interface.

OpenAI Strawberry Model is a cutting-edge AI initiative that represents a significant leap in AI capabilities, focusing on enhancing reasoning, problem-solving, and complex task execution. It aims to improve AI's ability to handle mathematical problems, programming tasks, and deep research, including long-term planning and action. The project showcases advancements in AI safety and aims to reduce errors in AI responses by generating high-quality synthetic data for training future models. Strawberry is designed to achieve human-like reasoning and is expected to play a crucial role in the development of OpenAI's next major model, codenamed 'Orion.'

DeepSeek R1 is a revolutionary open-source AI model for advanced reasoning that outperforms leading AI models in mathematics, coding, and general reasoning tasks. It utilizes a sophisticated MoE architecture with 37B active/671B total parameters and 128K context length, incorporating advanced reinforcement learning techniques. DeepSeek R1 offers multiple variants and distilled models optimized for complex problem-solving, multilingual understanding, and production-grade code generation. It provides cost-effective pricing compared to competitors like OpenAI o1, making it an attractive choice for developers and enterprises.

Imandra is a company that provides automated logical reasoning for Large Language Models (LLMs). Imandra's technology allows LLMs to build mental models and reason about them, unlocking the potential of generative AI for industries where correctness and compliance matter. Imandra's platform is used by leading financial firms, the US Air Force, and DARPA.

OpenAI01.net is an AI tool that offers free usage with some limitations. It provides a new series of AI models designed to spend more time thinking before responding, capable of reasoning through complex tasks and solving harder problems in science, coding, and math. Users can ask questions and get answers for free, with the option to select different models based on credits. The tool excels in complex reasoning tasks and has shown impressive performance in various benchmarks.

Cognition is an applied AI lab that has developed Devin, a collaborative AI teammate designed to assist engineering teams in achieving more. Devin is the world's first AI software engineer, available for all engineering teams. The team behind Cognition comprises individuals with extensive experience in applied AI at top companies, and they are focused on building AI that can reason and solve complex problems.

Interview Coder is an undetectable desktop application designed to assist users in solving coding problems for technical interviews. It features robust undetectability capabilities, detailed solution reasoning, and webcam monitoring. The application provides a platform for capturing coding problems, generating solutions, debugging, and optimizing code. Interview Coder aims to help users articulate their solution approaches convincingly and optimize their coding solutions efficiently.

AI MathGPT is an AI-powered math tutoring tool designed to assist students and parents with math homework. It offers advanced reasoning, step-by-step solutions, and clear explanations for challenging math problems. The tool aims to boost math performance, provide 24/7 support, and enhance math learning experiences for users of all levels.

Kie.ai is an AI platform that offers access to DeepSeek R1 & V3 APIs for secure and scalable AI solutions. It provides advanced reasoning models for tasks in math, coding, and language, along with versatile natural language processing capabilities. With no local deployment required, developers can easily integrate the APIs into their projects for fast and efficient AI solutions. Kie.ai ensures data security by hosting the APIs on U.S.-based servers, offering affordable pricing plans and comprehensive documentation for seamless integration.

Instabase is an AI-native unstructured data platform that helps businesses transform their processes stuck in unstructured data. It offers solutions for automating document processing workflows, analyzing data from any document or knowledge base, and surfacing insights across all company data. Instabase leverages generative AI, agentic reasoning, and federated processing to enable users to automate processes, find information, and make smarter decisions faster. The platform prioritizes AI privacy, security, and trust, providing users with complete control over their data and enterprise-grade security measures. Instabase has received several awards and recognitions for its innovative approach to leveraging AI for business solutions.

AI Math is an online math solver that uses artificial intelligence to help users solve math problems. It can solve a wide range of math problems, including arithmetic, algebra, geometry, trigonometry, calculus, combinations, word problems, statistics, and probability. AI Math is available in over 30 languages and is free to use. It is a valuable tool for students, educators, and anyone who needs help with math.

Ferhat Erata is an AI application developed by a Computer Science PhD graduate from Yale University. The application focuses on training transformers to solve NP-complete problems using reinforcement learning and improving test-time compute strategies for reasoning. It also explores learning randomized reductions and program properties for security, privacy, and side-channel resilience. Ferhat Erata is currently an Applied Scientist at the Automated Reasoning Group at AWS, working on Neuro-Symbolic AI to prevent factual errors caused by LLM hallucinations using mathematically sound Automated Reasoning checks.

Reka is a cutting-edge AI application offering next-generation multimodal AI models that empower agents to see, hear, and speak. Their flagship model, Reka Core, competes with industry leaders like OpenAI and Google, showcasing top performance across various evaluation metrics. Reka's models are natively multimodal, capable of tasks such as generating textual descriptions from videos, translating speech, answering complex questions, writing code, and more. With advanced reasoning capabilities, Reka enables users to solve a wide range of complex problems. The application provides end-to-end support for 32 languages, image and video comprehension, multilingual understanding, tool use, function calling, and coding, as well as speech input and output.

Solve Intelligence is an AI-powered platform designed to assist legal professionals in writing high-quality patents efficiently. The platform offers an in-browser document editor that leverages generative AI to streamline the patent drafting process. With a focus on security and confidentiality, Solve Intelligence ensures that all data is encrypted and not used for AI model training. Trusted by IP teams globally, the platform enables users to customize their drafting style and increase the efficiency of their IP team.

Solve For X is an AI tool that empowers growth stage organizations by leveraging AI and data solutions to enhance operations, efficiency, and decision-making. The platform offers AI consulting services, data analysis and reporting, automation solutions, and custom AI models to help organizations achieve measurable impact and value through seamlessly integrated AI technologies. With a focus on empowering businesses with innovative AI solutions, Solve For X aims to help organizations successfully implement AI and data solutions into their operations by 2028.

NuMind is an AI tool designed to solve information extraction tasks efficiently. It offers high-quality lightweight models tailored to users' needs, automating classification, entity recognition, and structured extraction. The tool is powered by task-specific and domain-agnostic foundation models, outperforming GPT-4 and similar models. NuMind provides solutions for various industries such as insurance and healthcare, ensuring privacy, cost-effectiveness, and faster NLP projects.

MathSolver.top is an AI math solver and personalized math tutor application that offers a free platform for solving math problems with high accuracy. Users can upload math questions and receive step-by-step answers instantly. The application includes features like Homework Helper Mode, Tutor/Learner Mode, and the ability to scan/upload/copy math problems for quick solutions. It provides personalized progressive learning through AI-generated study sets and smart recommendations for daily tasks. MathSolver aims to enhance math learning by offering a user-friendly interface and efficient problem-solving capabilities.

Subscribr is an AI tool designed exclusively for YouTube scriptwriting, aiming to revolutionize the script creation process by providing fast ideation, high-quality research, scriptwriting on easy mode, instant feedback, and the ability to remix proven viral videos. Founded by Gil Hildebrand, Subscribr addresses the common challenges faced by content creators on YouTube, offering a solution that streamlines the scriptwriting workflow and enhances the overall quality of video content.

SadCaptcha is an AI-powered tool designed to solve TikTok Captcha challenges efficiently. It offers a fast, accurate, and simple solution to bypass the puzzle slide, image rotate, and 3D shapes challenges on TikTok. The tool provides a Python client for easy integration and works with any programming language. With a high success rate and instant response using advanced AI computer vision algorithms, SadCaptcha helps users automate TikTok tasks without barriers.

MyMathSolver.ai is an AI math solver powered by Math GPT models like GPT-4o, providing comprehensive assistance across various math topics. Users can easily access detailed, step-by-step solutions to complex math problems using versatile input methods such as text, images, PDFs, or CSV files. The platform offers interactive problem-solving through a math AI bot and ensures accessibility on various devices and operating systems. With features like math AI bot, math solver online free access, and math GPT for advanced solutions, MyMathSolver.ai transforms the learning journey for students and math enthusiasts.

The 'awesome-deliberative-prompting' repository focuses on how to ask Large Language Models (LLMs) to produce reliable reasoning and make reason-responsive decisions through deliberative prompting. It includes success stories, prompting patterns and strategies, multi-agent deliberation, reflection and meta-cognition, text generation techniques, self-correction methods, reasoning analytics, limitations, failures, puzzles, datasets, tools, and other resources related to deliberative prompting. The repository provides a comprehensive overview of research, techniques, and tools for enhancing reasoning capabilities of LLMs.

MisguidedAttention is a collection of prompts designed to challenge the reasoning abilities of large language models by presenting them with modified versions of well-known thought experiments, riddles, and paradoxes. The goal is to assess the logical deduction capabilities of these models and observe any shortcomings or fallacies in their responses. The repository includes a variety of prompts that test different aspects of reasoning, such as decision-making, probability assessment, and problem-solving. By analyzing how language models handle these challenges, researchers can gain insights into their reasoning processes and potential biases.

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.

Buffer of Thoughts (BoT) is a thought-augmented reasoning framework designed to enhance the accuracy, efficiency, and robustness of large language models (LLMs). It introduces a meta-buffer to store high-level thought-templates distilled from problem-solving processes, enabling adaptive reasoning for efficient problem-solving. The framework includes a buffer-manager to dynamically update the meta-buffer, ensuring scalability and stability. BoT achieves significant performance improvements on reasoning-intensive tasks and demonstrates superior generalization ability and robustness while being cost-effective compared to other methods.

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

This repository focuses on test-time computing, exploring various strategies such as test-time adaptation, modifying the input, editing the representation, calibrating the output, test-time reasoning, and search strategies. It covers topics like self-supervised test-time training, in-context learning, activation steering, nearest neighbor models, reward modeling, and multimodal reasoning. The repository provides resources including papers and code for researchers and practitioners interested in enhancing the reasoning capabilities of large language models.

**Curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.** **Description in less than 400 words, no line breaks and quotation marks.** Large Language Models (LLMs) have revolutionized the NLP landscape, showing improved performance and sample efficiency over smaller models. However, increasing model size alone has not proved sufficient for high performance on challenging reasoning tasks, such as solving arithmetic or commonsense problems. This curated collection of papers and resources presents the latest advancements in unlocking the reasoning abilities of LLMs and Multimodal LLMs (MLLMs). It covers various techniques, benchmarks, and applications, providing a comprehensive overview of the field. **5 jobs suitable for this tool, in lowercase letters.** - content writer - researcher - data analyst - software engineer - product manager **Keywords of the tool, in lowercase letters.** - llm - reasoning - multimodal - chain-of-thought - prompt engineering **5 specific tasks user can use this tool to do, in less than 3 words, Verb + noun form, in daily spoken language.** - write a story - answer a question - translate a language - generate code - summarize a document

RAGEN is a reinforcement learning framework designed to train reasoning-capable large language model (LLM) agents in interactive, stochastic environments. It addresses challenges such as multi-turn interactions and stochastic environments through a Markov Decision Process (MDP) formulation, Reason-Interaction Chain Optimization (RICO) algorithm, and progressive reward normalization strategies. The framework enables LLMs to reason and interact with the environment, optimizing entire trajectories for long-horizon reasoning while maintaining computational efficiency.

RAGEN is a reinforcement learning framework designed to train reasoning-capable large language model (LLM) agents in interactive, stochastic environments. It addresses challenges such as multi-turn interactions and stochastic environments through a Markov Decision Process (MDP) formulation, Reason-Interaction Chain Optimization (RICO) algorithm, and progressive reward normalization strategies. The framework consists of MDP formulation, RICO algorithm with rollout and update stages, and reward normalization strategies to stabilize training. RAGEN aims to optimize reasoning and action strategies for LLM agents operating in complex environments.

Mentals AI is a tool designed for creating and operating agents that feature loops, memory, and various tools, all through straightforward markdown syntax. This tool enables you to concentrate solely on the agent’s logic, eliminating the necessity to compose underlying code in Python or any other language. It redefines the foundational frameworks for future AI applications by allowing the creation of agents with recursive decision-making processes, integration of reasoning frameworks, and control flow expressed in natural language. Key concepts include instructions with prompts and references, working memory for context, short-term memory for storing intermediate results, and control flow from strings to algorithms. The tool provides a set of native tools for message output, user input, file handling, Python interpreter, Bash commands, and short-term memory. The roadmap includes features like a web UI, vector database tools, agent's experience, and tools for image generation and browsing. The idea behind Mentals AI originated from studies on psychoanalysis executive functions and aims to integrate 'System 1' (cognitive executor) with 'System 2' (central executive) to create more sophisticated agents.

InternLM is a powerful language model series with features such as 200K context window for long-context tasks, outstanding comprehensive performance in reasoning, math, code, chat experience, instruction following, and creative writing, code interpreter & data analysis capabilities, and stronger tool utilization capabilities. It offers models in sizes of 7B and 20B, suitable for research and complex scenarios. The models are recommended for various applications and exhibit better performance than previous generations. InternLM models may match or surpass other open-source models like ChatGPT. The tool has been evaluated on various datasets and has shown superior performance in multiple tasks. It requires Python >= 3.8, PyTorch >= 1.12.0, and Transformers >= 4.34 for usage. InternLM can be used for tasks like chat, agent applications, fine-tuning, deployment, and long-context inference.

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**

QuantaLogic is a ReAct framework for building advanced AI agents that seamlessly integrates large language models with a robust tool system. It aims to bridge the gap between advanced AI models and practical implementation in business processes by enabling agents to understand, reason about, and execute complex tasks through natural language interaction. The framework includes features such as ReAct Framework, Universal LLM Support, Secure Tool System, Real-time Monitoring, Memory Management, and Enterprise Ready components.

The Awesome-Neuro-Symbolic-Learning-with-LLM repository is a curated collection of papers and resources focusing on improving reasoning and planning capabilities of Large Language Models (LLMs) and Multi-Modal Large Language Models (MLLMs) through neuro-symbolic learning. It covers a wide range of topics such as neuro-symbolic visual reasoning, program synthesis, logical reasoning, mathematical reasoning, code generation, visual reasoning, geometric reasoning, classical planning, game AI planning, robotic planning, AI agent planning, and more. The repository provides a comprehensive overview of tutorials, workshops, talks, surveys, papers, datasets, and benchmarks related to neuro-symbolic learning with LLMs and MLLMs.

Expert at logical puzzles, reasoning, and thoughtful analysis. Uses CoT and ToT.

Original and logical situation puzzles

海龜湯是訓練邏輯推理與MECE的好遊戲，透過「是」、「不是」或「無關」得到線索，拼湊出完整的劇情。如果太過困難，可以說「你贏了」

解答数理逻辑问题的专家

Ubbe generates answers, not just advice. Designed for action, Ubbe adjusts its reasoning framework and tool use as your objective evolves, allowing you to solve even the most complex tasks.

Guides you through detailed reasoning to find well-supported answers.

An astute critical-thinking partner with the deductive reasoning skills of Sherlock Holmes

Articulate, precise mentor employing the Socratic method & Batesonian reasoning to find solution to issues (updated on 10 Jan 24)

Solves problems using the simplest solutions, explains reasoning concisely.

A decisive entity that makes choices and explains reasoning.

A logician with a witty and gentlemanly demeanor.

Helps thinking from first principles

Ajattelun kehittämiseen ja ymmärtämiseen keskittynyt botti

Tries to decompose responses into logic and using equations, avoiding any diplomacy

Multilingual analytical critic.

Challenges viewpoints with counterarguments and evidence.

Solve Medical Mysteries!

Mysteries to solve in every spoonful

Solve situation puzzles with GPT 海龟汤助手

A detective game simulator, using real-world events and local knowledge to solve a crime mystery..