Best AI tools for< Reasoning Answers >

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.

Ask a Philosopher is a website where users can submit questions to a philosopher and receive answers. The platform allows individuals to engage in philosophical discussions and seek insights on various topics. It is a valuable resource for those interested in exploring deep questions and gaining a better understanding of philosophical concepts.

The website features Grok-1.5, an AI application that bridges the gap between the digital and physical worlds through its multimodal model. Grok-1.5 boasts enhanced reasoning capabilities and a context length of 128,000 tokens. Additionally, the platform offers PromptIDE, an IDE for prompt engineering and interpretability research, allowing users to create and share complex prompts in Python. Grok, an AI modeled after the Hitchhiker’s Guide to the Galaxy, is also available on the site, providing answers to a wide range of questions and even suggesting relevant queries. The platform aims to facilitate knowledge sharing and exploration through advanced AI technologies.

Tutorly is an AI-powered tutoring platform that offers personalized quiz questions, interactive verbal reasoning exercises, and tailored feedback to enhance the learning experience. Users can choose from a selection of premade tutors or provide custom instructions, upload notes, chat with the tutor, and ask unlimited questions to get instant, accurate answers. With flexible pricing plans and access to beta gamemodes, Tutorly aims to revolutionize the way students learn beyond limits.

Mendel AI is an advanced clinical AI tool that deciphers clinical data with clinician-like logic. It offers a fully integrated suite of clinical-specific data processing products, combining OCR, de-identification, and clinical reasoning to interpret medical records. Users can ask questions in plain English and receive accurate answers from health records in seconds. Mendel's technology goes beyond traditional AI by understanding patient-level data and ensuring consistency and explainability of results in healthcare.

Hey Mind is a new kind of design lab that aims to unlock hidden ideas through AI-powered tools. The platform offers a unique journaling experience with LB, an inner guide, to help users understand their thoughts better. Hey Mind promotes a new renaissance by transforming work into play, enhancing productivity through creative workflows and innovative thinking. Users can revolutionize the way they work and think, with a focus on boosting efficiency and creativity.

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.

Gemini is a large and powerful AI model developed by Google. It is designed to handle a wide variety of text and image reasoning tasks, and it can be used to build a variety of AI-powered applications. Gemini is available in three sizes: Ultra, Pro, and Nano. Ultra is the most capable model, but it is also the most expensive. Pro is the best performing model for a wide variety of tasks, and it is a good value for the price. Nano is the most efficient model, and it is designed for on-device use cases.

Alan AI is an advanced conversational AI platform that offers a wide range of AI solutions for various industries. It simplifies tasks, enhances business operations, and empowers sales strategies through AI technology. The platform provides features like question answering, semantic search, reporting, private data sources, and context awareness. With a focus on actionable AI, Alan AI aims to redefine learning and streamline decision-making processes. It offers a comprehensive suite of tools for developers, including technology architecture overview, integration, deployment, and analytics. Alan AI stands out for its innovative approach to AI reasoning, transparency, and control, making it a valuable asset for organizations seeking to leverage AI capabilities.

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.

Meta AI is an intelligent assistant that aims to create new AI experiences for everyone. It offers enhanced capabilities in Llama 3.1, allowing users to discover new possibilities and expand their world. Users can connect with the things that matter to them, get advice, create images, and more. With AI Studio, users can create their own AI characters or explore AIs made by others. The platform also introduces the latest release of Llama 3.1 with enhanced reasoning and coding capabilities, multilingual support, and the largest open model available. Meta AI strives to help users learn, create, and do more in the field of artificial intelligence.

Prompt Engineering is a discipline focused on developing and optimizing prompts to efficiently utilize language models (LMs) for various applications and research topics. It involves skills to understand the capabilities and limitations of large language models, improving their performance on tasks like question answering and arithmetic reasoning. Prompt engineering is essential for designing robust prompting techniques that interact with LLMs and other tools, enhancing safety and building new capabilities by augmenting LLMs with domain knowledge and external tools.

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.

HelloScribe is an autonomous reasoning engine that provides high-level creativity, strategy, and planning. It offers over 150 precision-made AI tools and templates, the ability to create in over 50 languages, speech-to-text functionality, and access to over 200 million research papers, live news, and web search. HelloScribe is designed to help professionals in various fields, including sales, marketing, consulting, and research, by automating tasks, providing real-time insights, and facilitating collaboration.

LangChain is an AI tool that offers a suite of products supporting developers in the LLM application lifecycle. It provides a framework to construct LLM-powered apps easily, visibility into app performance, and a turnkey solution for serving APIs. LangChain enables developers to build context-aware, reasoning applications and future-proof their applications by incorporating vendor optionality. LangSmith, a part of LangChain, helps teams improve accuracy and performance, iterate faster, and ship new AI features efficiently. The tool is designed to drive operational efficiency, increase discovery & personalization, and deliver premium products that generate revenue.

Imbue is a company focused on building AI systems that can reason and code, with the goal of rekindling the dream of the personal computer by creating practical AI agents that can accomplish larger goals and work safely in the real world. The company emphasizes innovation in AI technology and aims to push the boundaries of what AI can achieve in various fields.

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.'

MIRI (Machine Intelligence Research Institute) is a non-profit research organization dedicated to ensuring that artificial intelligence has a positive impact on humanity. MIRI conducts foundational mathematical research on topics such as decision theory, game theory, and reinforcement learning, with the goal of developing new insights into how to build safe and beneficial AI systems.

GPT-4o is a state-of-the-art AI model developed by OpenAI, capable of processing and generating text, audio, and image outputs. It offers enhanced emotion recognition, real-time interaction, multimodal capabilities, improved accessibility, and advanced language capabilities. GPT-4o provides cost-effective and efficient AI solutions with superior vision and audio understanding. It aims to revolutionize human-computer interaction and empower users worldwide with cutting-edge AI technology.

Trickle AI is an innovative AI tool that allows users to turn their ideas into powerful AI agents without the need for coding. Users can create apps using natural language, explore AI agents crafted by the community, and spark endless possibilities with a single idea. The tool enables users to build AI agents for various purposes such as startup product analysis, perplexity alternatives, pricing plan comparison, and more. Trickle AI empowers users to unleash their creativity and bring their ideas into reality through a seamless and intuitive platform.

ST-LLM is a temporal-sensitive video large language model that incorporates joint spatial-temporal modeling, dynamic masking strategy, and global-local input module for effective video understanding. It has achieved state-of-the-art results on various video benchmarks. The repository provides code and weights for the model, along with demo scripts for easy usage. Users can train, validate, and use the model for tasks like video description, action identification, and reasoning.

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.

Foyle is a project focused on building agents to assist software developers in deploying and operating software. It aims to improve agent performance by collecting human feedback on agent suggestions and human examples of reasoning traces. Foyle utilizes a literate environment using vscode notebooks to interact with infrastructure, capturing prompts, AI-provided answers, and user corrections. The goal is to continuously retrain AI to enhance performance. Additionally, Foyle emphasizes the importance of reasoning traces for training agents to work with internal systems, providing a self-documenting process for operations and troubleshooting.

MathVerse is an all-around visual math benchmark designed to evaluate the capabilities of Multi-modal Large Language Models (MLLMs) in visual math problem-solving. It collects high-quality math problems with diagrams to assess how well MLLMs can understand visual diagrams for mathematical reasoning. The benchmark includes 2,612 problems transformed into six versions each, contributing to 15K test samples. It also introduces a Chain-of-Thought (CoT) Evaluation strategy for fine-grained assessment of output answers.

LiveBench is a benchmark tool designed for Language Model Models (LLMs) with a focus on limiting contamination through monthly new questions based on recent datasets, arXiv papers, news articles, and IMDb movie synopses. It provides verifiable, objective ground-truth answers for accurate scoring without an LLM judge. The tool offers 18 diverse tasks across 6 categories and promises to release more challenging tasks over time. LiveBench is built on FastChat's llm_judge module and incorporates code from LiveCodeBench and IFEval.

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.

Raspberry is an open source project aimed at creating a toy dataset for finetuning Large Language Models (LLMs) with reasoning abilities. The project involves synthesizing complex user queries across various domains, generating CoT and Self-Critique data, cleaning and rectifying samples, finetuning an LLM with the dataset, and seeking funding for scalability. The ultimate goal is to develop a dataset that challenges models with tasks requiring math, coding, logic, reasoning, and planning skills, spanning different sectors like medicine, science, and software development.

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.

CLadder is a repository containing the CLadder dataset for evaluating causal reasoning in language models. The dataset consists of yes/no questions in natural language that require statistical and causal inference to answer. It includes fields such as question_id, given_info, question, answer, reasoning, and metadata like query_type and rung. The dataset also provides prompts for evaluating language models and example questions with associated reasoning steps. Additionally, it offers dataset statistics, data variants, and code setup instructions for using the repository.

MMMU is a benchmark designed to evaluate multimodal models on college-level subject knowledge tasks, covering 30 subjects and 183 subfields with 11.5K questions. It focuses on advanced perception and reasoning with domain-specific knowledge, challenging models to perform tasks akin to those faced by experts. The evaluation of various models highlights substantial challenges, with room for improvement to stimulate the community towards expert artificial general intelligence (AGI).

llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.

The Self-Iterative Agent System for Complex Problem Solving is a solution developed for the Alibaba Mathematical Competition (AI Challenge). It involves multiple LLMs engaging in multi-round 'self-questioning' to iteratively refine the problem-solving process and select optimal solutions. The system consists of main and evaluation models, with a process that includes detailed problem-solving steps, feedback loops, and iterative improvements. The approach emphasizes communication and reasoning between sub-agents, knowledge extraction, and the importance of Agent-like architectures in complex tasks. While effective, there is room for improvement in model capabilities and error prevention mechanisms.

RAGElo is a streamlined toolkit for evaluating Retrieval Augmented Generation (RAG)-powered Large Language Models (LLMs) question answering agents using the Elo rating system. It simplifies the process of comparing different outputs from multiple prompt and pipeline variations to a 'gold standard' by allowing a powerful LLM to judge between pairs of answers and questions. RAGElo conducts tournament-style Elo ranking of LLM outputs, providing insights into the effectiveness of different settings.

This repository contains a sophisticated deterministic graph-based solution for answering complex questions using a controllable autonomous agent. The solution is designed to ensure that answers are solely based on the provided data, avoiding hallucinations. It involves various steps such as PDF loading, text preprocessing, summarization, database creation, encoding, and utilizing large language models. The algorithm follows a detailed workflow involving planning, retrieval, answering, replanning, content distillation, and performance evaluation. Heuristics and techniques implemented focus on content encoding, anonymizing questions, task breakdown, content distillation, chain of thought answering, verification, and model performance evaluation.

2P-Kt is a Kotlin-based and multi-platform reboot of tuProlog (2P), a multi-paradigm logic programming framework written in Java. It consists of an open ecosystem for Symbolic Artificial Intelligence (AI) with modules supporting logic terms, unification, indexing, resolution of logic queries, probabilistic logic programming, binary decision diagrams, OR-concurrent resolution, DSL for logic programming, parsing modules, serialisation modules, command-line interface, and graphical user interface. The tool is designed to support knowledge representation and automatic reasoning through logic programming in an extensible and flexible way, encouraging extensions towards other symbolic AI systems than Prolog. It is a pure, multi-platform Kotlin project supporting JVM, JS, Android, and Native platforms, with a lightweight library leveraging the Kotlin common library.

TigerGraph CoPilot is an AI assistant that combines graph databases and generative AI to enhance productivity across various business functions. It includes three core component services: InquiryAI for natural language assistance, SupportAI for knowledge Q&A, and QueryAI for GSQL code generation. Users can interact with CoPilot through a chat interface on TigerGraph Cloud and APIs. CoPilot requires LLM services for beta but will support TigerGraph's LLM in future releases. It aims to improve contextual relevance and accuracy of answers to natural-language questions by building knowledge graphs and using RAG. CoPilot is extensible and can be configured with different LLM providers, graph schemas, and LangChain tools.

Nejumi Leaderboard 3 is a comprehensive evaluation platform for large language models, assessing general language capabilities and alignment aspects. The evaluation framework includes metrics for language processing, translation, summarization, information extraction, reasoning, mathematical reasoning, entity extraction, knowledge/question answering, English, semantic analysis, syntactic analysis, alignment, ethics/moral, toxicity, bias, truthfulness, and robustness. The repository provides an implementation guide for environment setup, dataset preparation, configuration, model configurations, and chat template creation. Users can run evaluation processes using specified configuration files and log results to the Weights & Biases project.

WDoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It supports querying tens of thousands of documents simultaneously, offers tailored summaries to efficiently manage large amounts of information, and includes features like supporting multiple file types, various LLMs, local and private LLMs, advanced RAG capabilities, advanced summaries, trust verification, markdown formatted answers, sophisticated embeddings, extensive documentation, scriptability, type checking, lazy imports, caching, fast processing, shell autocompletion, notification callbacks, and more. WDoc is ideal for researchers, students, and professionals dealing with extensive information sources.

wdoc is a powerful Retrieval-Augmented Generation (RAG) system designed to summarize, search, and query documents across various file types. It aims to handle large volumes of diverse document types, making it ideal for researchers, students, and professionals dealing with extensive information sources. wdoc uses LangChain to process and analyze documents, supporting tens of thousands of documents simultaneously. The system includes features like high recall and specificity, support for various Language Model Models (LLMs), advanced RAG capabilities, advanced document summaries, and support for multiple tasks. It offers markdown-formatted answers and summaries, customizable embeddings, extensive documentation, scriptability, and runtime type checking. wdoc is suitable for power users seeking document querying capabilities and AI-powered document summaries.

WebScout is a versatile tool that allows users to search for anything using Google, DuckDuckGo, and phind.com. It contains AI models, can transcribe YouTube videos, generate temporary email and phone numbers, has TTS support, webai (terminal GPT and open interpreter), and offline LLMs. It also supports features like weather forecasting, YT video downloading, temp mail and number generation, text-to-speech, advanced web searches, and more.

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

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.

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

I imitate GPT-5 LLM, with advanced reasoning, personalization, and higher emotional intelligence

Solves problems using the simplest solutions, explains reasoning concisely.

Conversate numerically to your prompts

Formal academic logic analysis.

My strong counterarguments refine reasoning, fostering intellectual growth.

Grades op-eds on reasoning, fair engagement, and open-mindedness.

Self Discover: Self-Composing Reasoning Structures. A self-reflecting reasoning agent.

I identify flaws in debates and outline reasoning errors.

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

Constructive advisor in educational strategies, focusing on inverse reasoning and DDD.

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

A decisive entity that makes choices and explains reasoning.

As LegalGPT, I'm an AI legal assistant with expertise in law, adaptable for nationwide legal queries. I provide precise, context-sensitive advice based on a rich knowledge source, aiding in legal reasoning and drafting. Note: I'm not a substitute for a lawyer.

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」

A logician with a witty and gentlemanly demeanor.

Stephen Toulmin’s Theory of Argumentation. FIRST TIME? Start with "Good morning!" PRIMEIRA VEZ? Comece com um "Bom dia!"

解答数理逻辑问题的专家