Best AI tools for< Improve Reasoning Accuracy >
20 - AI tool Sites

LangChain
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.

Everseen
Everseen is an AI platform that offers a comprehensive suite of tools for data collection, contextualization, insight discovery, process modeling, video translation, AI reasoning, model engineering, continuous learning, governance, and more. It is designed to help businesses in the retail industry prevent losses, accelerate sales, protect inventory, improve product availability, and ensure process integrity. Everseen's Vision AI Factory supports hyper-scaled applications with value assurance and governance at its core, enabling users to combat retail shrink threats effectively.

OpenAI Strawberry Model
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.'

Debate AI
Debate AI is an AI-powered platform designed to enhance users' critical thinking and argumentation skills. It provides insights, feedback, and personalized advice to help individuals master the art of debate. By leveraging AI technology, Debate AI offers a unique opportunity for users to engage in meaningful discussions, improve reasoning skills, and gain confidence in articulating ideas effectively. Whether you are a professional debater, university student, aspiring politician, high school debater, or public speaking coach, Debate AI aims to revolutionize the way you approach debates and communication.

d-Matrix
d-Matrix is an AI tool that offers ultra-low latency batched inference for generative AI technology. It introduces Corsair™, the world's most efficient AI inference platform for datacenters, providing high performance, efficiency, and scalability for large-scale inference tasks. The tool aims to transform the economics of AI inference by delivering fast, sustainable, and scalable AI solutions without compromising on speed or usability.

Socratify
Socratify is an AI tool designed for professionals, students, and curious minds to sharpen their debating skills. It offers curated business stories, challenges users with AI, provides personalized feedback, and encourages daily practice in just 5 minutes. Users can enhance decision-making, explore real business situations, and improve critical thinking through active learning. Socratify aims to upgrade how humans think and learn by leveraging AI technology.

Nuance
Nuance is a Conversational AI platform specializing in Healthcare and Customer Engagement. It offers AI solutions and services that transform the way organizations work, connect, and interact with others. Nuance provides industry-leading AI technology and deep vertical expertise to address challenges and accelerate business results, from healthcare solutions to customer engagement. The platform aims to amplify users' ability to help others and advance the effectiveness of organizations, ultimately making a positive impact on the world.

Brainy Buddy
Brainy Buddy is an AI learning companion designed to assist users in enhancing their reasoning skills. It leverages artificial intelligence technology to provide personalized learning experiences and improve cognitive abilities. With Brainy Buddy, users can engage in interactive activities and challenges that stimulate critical thinking and problem-solving. The platform offers a diverse range of educational resources and tools to support continuous learning and skill development. Whether you are a student looking to boost academic performance or an individual seeking to sharpen your cognitive skills, Brainy Buddy is your go-to AI companion for intellectual growth and development.

Lecturio
Lecturio is an award-winning, AI-powered, all-in-one study tool designed for medical and nursing students. It offers comprehensive learning content, personalized tutoring, and resources for various medical and nursing courses, exams, and specialties. Lecturio integrates evidence-based learning tools and strategies to enhance students' study routines and exam performance. The platform aims to help students achieve mastery of medical and nursing concepts through innovative teaching methods and advanced technology.

Image In Words
Image In Words is a generative model designed for scenarios that require generating ultra-detailed text from images. It leverages cutting-edge image recognition technology to provide high-quality and natural image descriptions. The framework ensures detailed and accurate descriptions, improves model performance, reduces fictional content, enhances visual-language reasoning capabilities, and has wide applications across various fields. Image In Words supports English and has been trained using approximately 100,000 hours of English data. It has demonstrated high quality and naturalness in various tests.

Alan AI
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.

Robot Writers AI
Robot Writers AI is an artificial intelligence tool that automates writing tasks. It offers advanced AI engines like ChatGPT-4o, enabling users to interact with AI personalities, generate content, interpret voice, video, and text in real-time, and more. The tool aims to enhance the writing process by providing faster response times, increased reasoning capabilities, and improved user experience. With features like video interaction, voice-to-voice communication, and a desktop app, Robot Writers AI is revolutionizing the writing industry by leveraging cutting-edge AI technology.

Chima
Chima is an AI tool that is revolutionizing the enterprise landscape by offering Complex Human Reasoning Systems powered by AI. It automates various functions, enhances customer targeting, and improves business operations. Chima ensures industry-grade security and compliance, making it a reliable choice for enterprises looking to leverage AI for growth and efficiency.

Ferhat Erata
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.

Tutorly
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.

Rainbird Decision Intelligence
Rainbird Decision Intelligence is an AI-powered platform that automates complex decision-making processes with trust and explainability. It leverages advanced reasoning engines to bridge data and processes, ensuring reliable and traceable AI-powered decisions. Rainbird is used across various industries such as banking, financial services, healthcare, legal, and insurance to streamline operations and enhance decision-making capabilities.

Tactic
Tactic is an AI-powered platform that provides generative insights and solutions for customers by leveraging AI technology to generate target accounts unique to businesses and new customer insights from various data sources. It offers features such as no-code custom AI builder, process automation, multi-step reasoning, model agnostic data import, and simple user experience. Tactic is trusted by hypergrowth startups and Fortune 500 companies for market research, audience automation, and customer data management. The platform helps users increase revenue, save time on research and analysis, and close more deals efficiently.

Prompt Engineering
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.

AI MathGPT
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.

Abridge
Abridge is an enterprise-grade AI platform for clinical conversations, transforming patient-clinician interactions into structured clinical notes in real-time. It is trusted by leading healthcare systems and offers auditable AI infrastructure. The platform aims to improve clinician efficiency, patient care, and overall healthcare outcomes through advanced AI technology.
20 - Open Source AI Tools

awesome-deliberative-prompting
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.

Awesome-LLM-Reasoning
**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

optillm
optillm is an OpenAI API compatible optimizing inference proxy implementing state-of-the-art techniques to enhance accuracy and performance of LLMs, focusing on reasoning over coding, logical, and mathematical queries. By leveraging additional compute at inference time, it surpasses frontier models across diverse tasks.

Awesome-System2-Reasoning-LLM
The Awesome-System2-Reasoning-LLM repository is dedicated to a survey paper titled 'From System 1 to System 2: A Survey of Reasoning Large Language Models'. It explores the development of reasoning Large Language Models (LLMs), their foundational technologies, benchmarks, and future directions. The repository provides resources and updates related to the research, tracking the latest developments in the field of reasoning LLMs.

Awesome_Test_Time_LLMs
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.

agentUniverse
agentUniverse is a multi-agent framework based on large language models, providing flexible capabilities for building individual agents. It focuses on collaborative pattern components to solve problems in various fields and integrates domain experience. The framework supports LLM model integration and offers various pattern components like PEER and DOE. Users can easily configure models and set up agents for tasks. agentUniverse aims to assist developers and enterprises in constructing domain-expert-level intelligent agents for seamless collaboration.

FuseAI
FuseAI is a repository that focuses on knowledge fusion of large language models. It includes FuseChat, a state-of-the-art 7B LLM on MT-Bench, and FuseLLM, which surpasses Llama-2-7B by fusing three open-source foundation LLMs. The repository provides tech reports, releases, and datasets for FuseChat and FuseLLM, showcasing their performance and advancements in the field of chat models and large language models.

awesome-transformer-nlp
This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, Chatbot, and transfer learning in NLP.

awesome-RLAIF
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.

LLMInterviewQuestions
LLMInterviewQuestions is a repository containing over 100+ interview questions for Large Language Models (LLM) used by top companies like Google, NVIDIA, Meta, Microsoft, and Fortune 500 companies. The questions cover various topics related to LLMs, including prompt engineering, retrieval augmented generation, chunking, embedding models, internal working of vector databases, advanced search algorithms, language models internal working, supervised fine-tuning of LLM, preference alignment, evaluation of LLM system, hallucination control techniques, deployment of LLM, agent-based system, prompt hacking, and miscellaneous topics. The questions are organized into 15 categories to facilitate learning and preparation.

awesome-llms-fine-tuning
This repository is a curated collection of resources for fine-tuning Large Language Models (LLMs) like GPT, BERT, RoBERTa, and their variants. It includes tutorials, papers, tools, frameworks, and best practices to aid researchers, data scientists, and machine learning practitioners in adapting pre-trained models to specific tasks and domains. The resources cover a wide range of topics related to fine-tuning LLMs, providing valuable insights and guidelines to streamline the process and enhance model performance.

AGI-Papers
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**

awesome-gpt-prompt-engineering
Awesome GPT Prompt Engineering is a curated list of resources, tools, and shiny things for GPT prompt engineering. It includes roadmaps, guides, techniques, prompt collections, papers, books, communities, prompt generators, Auto-GPT related tools, prompt injection information, ChatGPT plug-ins, prompt engineering job offers, and AI links directories. The repository aims to provide a comprehensive guide for prompt engineering enthusiasts, covering various aspects of working with GPT models and improving communication with AI tools.

HuixiangDou2
HuixiangDou2 is a robustly optimized GraphRAG approach that integrates multiple open-source projects to improve performance in graph-based augmented generation. It conducts comparative experiments and achieves a significant score increase, leading to a GraphRAG implementation with recognized performance. The repository provides code improvements, dense retrieval for querying entities and relationships, real domain knowledge testing, and impact analysis on accuracy.

Slow_Thinking_with_LLMs
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.

text-to-sql-bedrock-workshop
This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

PURE
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.
20 - OpenAI Gpts

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

GRE Test Vocabulary Learning
Helps user learn essential vocabulary for GRE test with multiple choice questions

Grade an Op-ed type essay
Grades op-eds on reasoning, fair engagement, and open-mindedness.

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

Auto Prompt Agent 🚩
Prompt Engineer automatically enhances the prompt, autonomously reasons based on that prompt, and generates exceptional responses.

UX & UI
Gives you tips and suggestions on how you can improve your application for your users.

Memory Enhancer
Offers exercises and techniques to improve memory retention and cognitive functions.

English Conversation Role Play Creator
Generates conversation examples and chunks for specified situations. Improve your instantaneous conversational skills through repetitive practice!

Customer Retention Consultant
Analyzes customer churn and provides strategies to improve loyalty and retention.