Best AI tools for< Research Evolutionary Algorithms >

Yabble is a leading AI solution for market research, offering a suite of AI tools for data creation, virtual audiences, surveys, and data analysis. Built with custom algorithms and world-class Large Language Models, Yabble provides secure and insightful answers for all stages of research. Trusted by global brands, Yabble enables users to generate deep insights quickly and efficiently, transforming the way market research is conducted.

Medeloop is a revolutionary platform in health research that leverages machine learning and big data analytics to accelerate breakthrough discoveries in disease research. The platform provides a comprehensive data-linking infrastructure to solve the problem of wasted health and medical data for both patients and researchers. Medeloop's multi-modal data linkage platform enables researchers to access and analyze diverse data types using analytical tools and programming languages. By utilizing machine learning and artificial intelligence algorithms, Medeloop drives the discovery and development of new therapies, making it a key player in changing the nature of healthcare for the better.

Wolfram is a comprehensive platform that unifies algorithms, data, notebooks, linguistics, and deployment to provide a powerful computation platform. It offers a range of products and services for various industries, including education, engineering, science, and technology. Wolfram is known for its revolutionary knowledge-based programming language, Wolfram Language, and its flagship product Wolfram|Alpha, a computational knowledge engine. The platform also includes Wolfram Cloud for cloud-based services, Wolfram Engine for software implementation, and Wolfram Data Framework for real-world data analysis.

DocuChat is a revolutionary app that transforms the way users interact with their documents. It allows users to engage with PDF files and photos in a conversational manner, extracting information effortlessly and navigating through complex files with ease. Powered by ChatGPT, DocuChat enables users to have interactive and engaging conversations with their documents, obtain concise summaries, ask questions, and receive detailed explanations through an intuitive chat interface. By leveraging advanced AI algorithms, DocuChat provides users with smart navigation features, saving time and effort in document analysis and understanding.

CogPrints is an electronic archive for self-archived papers in any area of Psychology, Neuroscience, and Linguistics, and many areas of Computer Science (e.g., artificial intelligence, robotics, vision, learning, speech, neural networks), Philosophy (e.g., mind, language, knowledge, science, logic), Biology (e.g., ethology, behavioral ecology, sociobiology, behavior genetics, evolutionary theory), Medicine (e.g., Psychiatry, Neurology, human genetics, Imaging), Anthropology (e.g., primatology, cognitive ethnology, archeology, paleontology), as well as any other portions of the physical, social and mathematical sciences that are pertinent to the study of cognition.

PromptReply is a revolutionary AI assistant integrated with WhatsApp, designed to enhance productivity by providing instant assistance, generating images, and creating content effortlessly. It offers features such as content creation for social posts, quick definitions and explanations, resume and topic summarization, and image generation/redesign using AI technology. With PromptReply, users can streamline their research, learning, decision-making processes, and add creativity to their projects. The AI assistant is developed by Tipodean Technologies.

LitStudy is an AI study assistant designed to enhance learning efficiency for students. It offers features such as real-time audio note generation, converting various content types into structured notes, personalized quiz and flashcard generation, report writing, media upload support, web link processing, language translation, and more. LitStudy aims to help busy individuals learn effectively by providing AI-structured notes in minutes, saving time and optimizing learning between commitments.

Parroview is a revolutionary AI-powered user research platform that automates the process of conducting user interviews. It uses natural language processing (NLP) to engage with users in real-time conversations, asking follow-up questions and uncovering insights that would be difficult to obtain through traditional methods. Parroview is designed to be fully autonomous, allowing researchers to set up interviews and gather insights without the need for manual intervention. It supports multiple languages, making it accessible to a global audience. Parroview offers a range of features, including the ability to conduct interviews via text or voice, analyze insights in real-time, and generate detailed transcripts. It is suitable for a wide range of research needs, including product validation, consumer behavior analysis, post-purchase evaluations, brand perception studies, and customer persona development.

NovaResp cMAP™ is an AI-powered platform software designed to improve adherence to Continuous Positive Airway Pressure (CPAP) therapy for sleep apnea patients. It utilizes artificial intelligence and machine learning to predict and prevent apnea episodes during therapy, delivering personalized treatment at more comfortable air pressure levels. The application aims to enhance patient quality of life, increase sales for device manufacturers, and reduce labor costs for DMEs. NovaResp cMAP™ is compatible with all major PAP machines and is a revolutionary solution in the treatment of Obstructive Sleep Apnea (OSA).

Zamora Labs is an AI-driven platform that focuses on innovation in education and immigration. The platform offers cutting-edge solutions powered by ResidentIA and CortexAI technologies. It leverages artificial intelligence to enhance learning experiences, streamline immigration processes, and provide personalized services to users. Zamora Labs aims to revolutionize the education and immigration sectors by harnessing the power of AI to deliver efficient and effective solutions.

ACHIV is an AI tool for ideas validation and market research. It helps businesses make informed decisions based on real market needs by providing data-driven insights. The tool streamlines the market validation process, allowing quick adaptation and refinement of product development strategies. ACHIV offers a revolutionary approach to data collection and preprocessing, along with proprietary AI models for smart analysis and predictive forecasting. It is designed to assist entrepreneurs in understanding market gaps, exploring competitors, and enhancing investment decisions with real-time data.

RejuveAI is a decentralized token-based system that aims to democratize longevity globally. The Longevity App allows users to monitor essential health metrics, enhance lifespan, and earn RJV tokens. The application leverages revolutionary AI technology to analyze human body functions in-depth, providing insights for aging combat. RejuveAI collaborates with researchers, clinics, and data enthusiasts to ensure innovative outcomes are affordable and accessible. The platform also offers exclusive discounts on travel, supplements, medical tests, and longevity therapies.

Digital First AI is an AI-powered visual workflows tool that helps users build and execute personalized marketing strategies. The platform offers features such as data safe room for managing marketing data, AI-powered NLP for extracting insights, collaborative workspace for team collaboration, customizable marketing workflows, scalable content production, and automated data collection from social media and websites. Digital First AI aims to maximize marketing impact, streamline campaign creation, and enhance decision-making with AI-driven insights.

LearnMate is a revolutionary AI-integrated productivity app designed for students. It offers collaborative tools for study goal setting, assignment and task management, note-taking, and more. The app utilizes cutting-edge AI technology to enhance the learning experience and productivity of students. LearnMate is accessible on various devices, allowing seamless progress tracking and data synchronization across PCs, tablets, and mobile devices. With features like AI tutor assistance, assignment management, task lists, study notes creation, and more, LearnMate aims to revolutionize the way students study and excel in their academic endeavors.

Prompt Storm is a powerful and easy-to-use Artificial Intelligence Chrome extension designed for ChatGPT, Google's Gemini, and Anthropic's Claude. It unlocks the potential of revolutionary AI technology by providing skillfully crafted prompts for various purposes such as acquiring new knowledge, enhancing productivity, developing marketing strategies, speeding up project development, and receiving expert advice. With Prompt Storm, users can unleash the power of AI to improve productivity and expand their knowledge base.

Mool Capital is an AI-powered platform that offers elevated investing and high fidelity research capabilities. The platform provides revolutionary AI tools for analyzing vast datasets in seconds, trustworthy analysis for informed investing, and performant portfolios curated for optimal performance. Users can access the latest market analysis, investment ideas, and premium articles to enhance their investment decisions. Mool Capital aims to empower investors with AI superpowers to make better investment choices and navigate the complex world of finance with confidence.

Sharly AI is a revolutionary tool that utilizes advanced AI technology to transform complex documents and PDFs into easily digestible summaries and facilitate interactive chat-based interactions. It empowers users to engage in natural language conversations with their documents, ask questions, and retrieve specific information effortlessly. Sharly AI's capabilities extend to various domains, including research, legal analysis, project management, and content summarization, offering tailored solutions for professionals in each field. By leveraging the power of AI, Sharly AI streamlines workflows, enhances productivity, and unlocks deeper insights from vast amounts of information.

Laxis is a revolutionary AI Meeting Assistant designed to capture and distill key insights from every customer interaction effortlessly. It seamlessly integrates across platforms, from online meetings to CRM updates, all with a user-friendly interface. Laxis empowers revenue teams to maximize every customer conversation, ensuring no valuable detail is missed. With Laxis, sales teams can close more deals with AI note-taking and insights from client conversations, business development teams can engage prospects more effectively and grow their business faster, marketing teams can repurpose podcasts, webinars, and meetings into engaging content with a single click, product and market researchers can conduct better research interviews that get to the "aha!" moment faster, project managers can remember key takeaways and status updates, and capture them for progress reports, and product and UX designers can capture and organize insights from their interviews and user research.

NOA by biped.ai is a revolutionary mobility vest designed to enhance the independence and safety of individuals with blindness and low vision. It combines cutting-edge AI technology with wearable devices to provide real-time navigation instructions, obstacle detection, and object finding capabilities. NOA is a hands-free solution that complements traditional mobility aids like white canes and guide dogs, offering a compact and lightweight design for seamless integration into daily life. Developed through extensive research and collaboration with experts in the field, NOA aims to empower users to navigate their surroundings with confidence and ease.

Google Research is a leading research organization focusing on advancing science and artificial intelligence. They conduct research in various domains such as AI/ML foundations, responsible human-centric technology, science & societal impact, computing paradigms, and algorithms & optimization. Google Research aims to create an environment for diverse research across different time scales and levels of risk, driving advancements in computer science through fundamental and applied research. They publish hundreds of research papers annually, collaborate with the academic community, and work on projects that impact technology used by billions of people worldwide.

SharpNEAT is a complete implementation of NEAT written in C# and targeting .NET 9. It provides an implementation of an Evolutionary Algorithm (EA) with the specific goal of evolving a population of neural networks towards solving some goal problem task. The framework facilitates research into evolutionary computation and specifically evolution of neural networks, allowing for modular experimentation with genetic coding and evolutionary algorithms.

LLM4EC is an interdisciplinary research repository focusing on the intersection of Large Language Models (LLM) and Evolutionary Computation (EC). It provides a comprehensive collection of papers and resources exploring various applications, enhancements, and synergies between LLM and EC. The repository covers topics such as LLM-assisted optimization, EA-based LLM architecture search, and applications in code generation, software engineering, neural architecture search, and other generative tasks. The goal is to facilitate research and development in leveraging LLM and EC for innovative solutions in diverse domains.

EvoMaster is an open-source AI-driven tool that automatically generates system-level test cases for web/enterprise applications. It uses an Evolutionary Algorithm and Dynamic Program Analysis to evolve test cases, maximizing code coverage and fault detection. The tool supports REST, GraphQL, and RPC APIs, with whitebox testing for JVM-compiled languages. It generates JUnit tests, detects faults, handles SQL databases, and supports authentication. EvoMaster has been funded by the European Research Council and the Research Council of Norway.

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 is a collection of papers and resources related to Lifelong Learning of Large Language Model (LLM) based Agents. It focuses on continual learning and incremental learning of LLM agents, identifying key modules such as Perception, Memory, and Action. The repository serves as a roadmap for understanding lifelong learning in LLM agents and provides a comprehensive overview of related research and surveys.

EvoMaster is an open-source AI-driven tool that automatically generates system-level test cases for web/enterprise applications. It uses Evolutionary Algorithm and Dynamic Program Analysis to evolve test cases, maximizing code coverage and fault detection. It supports REST, GraphQL, and RPC APIs, with whitebox testing for JVM-compiled APIs. The tool generates JUnit tests in Java or Kotlin, focusing on fault detection, self-contained tests, SQL handling, and authentication. Known limitations include manual driver creation for whitebox testing and longer execution times for better results. EvoMaster has been funded by ERC and RCN grants.

Awesome-llm-role-playing-with-persona is a curated list of resources for large language models for role-playing with assigned personas. It includes papers and resources related to persona-based dialogue systems, personalized response generation, psychology of LLMs, biases in LLMs, and more. The repository aims to provide a comprehensive collection of research papers and tools for exploring role-playing abilities of large language models in various contexts.

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, named Awesome-Embodied-Agent-with-LLMs, is a curated list of research related to Embodied AI or agents with Large Language Models. It includes various papers, surveys, and projects focusing on topics such as self-evolving agents, advanced agent applications, LLMs with RL or world models, planning and manipulation, multi-agent learning and coordination, vision and language navigation, detection, 3D grounding, interactive embodied learning, rearrangement, benchmarks, simulators, and more. The repository provides a comprehensive collection of resources for individuals interested in exploring the intersection of embodied agents and large language models.

LLM-as-HH is a codebase that accompanies the paper ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution. It introduces Language Hyper-Heuristics (LHHs) that leverage LLMs for heuristic generation with minimal manual intervention and open-ended heuristic spaces. Reflective Evolution (ReEvo) is presented as a searching framework that emulates the reflective design approach of human experts while surpassing human capabilities with scalable LLM inference, Internet-scale domain knowledge, and powerful evolutionary search. The tool can improve various algorithms on problems like Traveling Salesman Problem, Capacitated Vehicle Routing Problem, Orienteering Problem, Multiple Knapsack Problems, Bin Packing Problem, and Decap Placement Problem in both black-box and white-box settings.

GOLEM is an open-source AI framework focused on optimization and learning of structured graph-based models using meta-heuristic methods. It emphasizes the potential of meta-heuristics in complex problem spaces where gradient-based methods are not suitable, and the importance of structured models in various problem domains. The framework offers features like structured model optimization, metaheuristic methods, multi-objective optimization, constrained optimization, extensibility, interpretability, and reproducibility. It can be applied to optimization problems represented as directed graphs with defined fitness functions. GOLEM has applications in areas like AutoML, Bayesian network structure search, differential equation discovery, geometric design, and neural architecture search. The project structure includes packages for core functionalities, adapters, graph representation, optimizers, genetic algorithms, utilities, serialization, visualization, examples, and testing. Contributions are welcome, and the project is supported by ITMO University's Research Center Strong Artificial Intelligence in Industry.

A curated list of open-ended learning AI resources focusing on algorithms that invent new and complex tasks endlessly, inspired by human advancements. The repository includes papers, safety considerations, surveys, perspectives, and blog posts related to open-ended AI research.

Awesome LLM compression research papers and tools to accelerate LLM training and inference.

The 'llms-tools' repository is a comprehensive collection of AI tools, open-source projects, and research related to Large Language Models (LLMs) and Chatbots. It covers a wide range of topics such as AI in various domains, open-source models, chats & assistants, visual language models, evaluation tools, libraries, devices, income models, text-to-image, computer vision, audio & speech, code & math, games, robotics, typography, bio & med, military, climate, finance, and presentation. The repository provides valuable resources for researchers, developers, and enthusiasts interested in exploring the capabilities of LLMs and related technologies.

AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

Mergekit is a toolkit for merging pre-trained language models. It uses an out-of-core approach to perform unreasonably elaborate merges in resource-constrained situations. Merges can be run entirely on CPU or accelerated with as little as 8 GB of VRAM. Many merging algorithms are supported, with more coming as they catch my attention.

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.

This repository includes papers and blogs about Efficient Transformers, Length Extrapolation, Long Term Memory, Retrieval Augmented Generation(RAG), and Evaluation for Long Context Modeling.

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