Best AI tools for< Support Scientific Discovery >

PumasAI is an AI tool designed to accelerate access to life-saving treatments for patients by providing data analytics tools and personalized treatments for drug development and healthcare delivery needs. The company has been recognized for its innovative contributions to the pharmaceutical industry, helping in making data-driven decisions more efficiently. PumasAI aims to save time and money for its clients through its fine-tuned offerings and successful regulatory submissions.

Researcher.Life is a comprehensive research support platform that provides AI-powered tools and expert publication services to empower researchers at every stage of their journey. With a suite of advanced AI tools, including Paperpal, R Discovery, and Mind the Graph, Researcher.Life helps researchers write better, discover relevant literature, create stunning scientific illustrations, and find the right journals for their work. Additionally, Researcher.Life offers expert publication services from Editage, ensuring that manuscripts are polished and ready for publication. By combining AI technology with human expertise, Researcher.Life simplifies complex research tasks, saves time, and accelerates the path to success for researchers worldwide.

The website focuses on showcasing groundbreaking research and studies across various scientific disciplines, including physics, biology, computer science, and mental health. It provides detailed insights into innovative projects, technological advancements, and transformative discoveries in the academic and research communities. Users can explore articles on topics such as quantum communication, artificial intelligence applications in healthcare, semiconductor dynamics, mental health support initiatives, and dietary interventions for mental disorders.

DMLR (Data-centric Machine Learning Research) is an AI tool that focuses on advancing research in data-centric machine learning. It organizes workshops, research retreats, maintains a journal, and runs a working group to support infrastructure projects. The platform covers topics such as data collection, governance, bias, and drifts, as well as data-centric explainable AI and AI alignment. DMLR encourages submissions around the theme of AI for Science, using AI to tackle scientific challenges and accelerate discoveries.

Editage is a professional editing, translation, and publication support services company that enables academicians, researchers, scientists, and authors worldwide to publish their work in the best light. Over the past two decades, Editage has helped 500,000+ researchers across 192+ countries to pursue successful publications. The goal is to help researchers improve the quality of their research and increase their chances of publication in international indexed journals.

NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and high-level mathematical functions to perform operations on these arrays. It is the fundamental package for scientific computing with Python and is used in a wide range of applications, including data science, machine learning, and image processing. NumPy is open source and distributed under a liberal BSD license, and is developed and maintained publicly on GitHub by a vibrant, responsive, and diverse community.

PokaMind is an AI tool that leverages Artificial Intelligence and scientific principles to provide accessible mental care solutions. By utilizing advanced technology, PokaMind aims to support individuals in enhancing their mental well-being. The platform offers a range of innovative features designed to cater to the diverse needs of users seeking mental health support.

Ascenscia is a specialized AI voice assistant designed to streamline lab digitization processes. It integrates with laboratory software and machines to enable hands-free interactions, automating data collection, optimizing workflows, and accelerating R&D cycles. Ascenscia offers features such as data accessibility, data capturing, inventory access, and additional task management. The application is designed for scientific labs, addressing concerns with precision, safety, and adaptability. It boasts high accuracy in understanding scientific terminologies, end-to-end data encryption, multi-lingual support, and customization options for different lab workflows.

Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Harver is a talent assessment platform that helps businesses make better hiring decisions faster. It offers a suite of solutions, including assessments, video interviews, scheduling, and reference checking, that can be used to optimize the hiring process and reduce time to hire. Harver's assessments are based on data and scientific insights, and they help businesses identify the right people for the right roles. Harver also offers support for the full talent lifecycle, including talent management, mobility, and development.

Tidalflow is an AI-powered weight loss coach application that helps users achieve lasting weight loss through personalized workout and diet plans. The app, backed by Google's AI fund, offers features such as daily check-ins, meal logging through photos, progress tracking summaries, and real-time support from an AI coach named Marcus. Tidalflow aims to provide a hyper-personalized experience to users, guiding them towards their weight loss goals with the latest scientific research and data-backed insights.

包阅AI is an intelligent AI reading assistant that covers various scenarios such as paper reading, legal analysis, scientific research, marketing, education, brand analysis, and business understanding. It supports multiple document formats like PDF, Word, PPT, EPUB, Mobi, TXT, and Markdown. The tool offers features like document interpretation, web page summarization, contract review, resume analysis, and financial document analysis. With the ability to analyze over 50,000 documents and assist more than 100,000 knowledge workers efficiently, it aims to enhance work and study productivity through AI-powered assistance.

Support AI is a custom AI chatbot application powered by ChatGPT that allows website owners to create personalized chatbots to provide instant answers to customers, capture leads, and enhance customer support. With Support AI, users can easily integrate AI chatbots on their websites, train them with specific content, and customize their behavior and responses. The application offers features such as capturing leads, providing accurate answers, handling bookings, collecting feedback, and offering product recommendations. Users can choose from different pricing plans based on their message volume and training content needs.

AI Chatbot Support is an autonomous AI and live chat customer service application that provides magic customer experiences by connecting websites, social media, and business messaging platforms. It offers multi-platform support, auto language translation, rich messaging features, smart-reply suggestions, and platform-agnostic AI assistance. The application is designed to enhance customer engagement, satisfaction, and retention across digital platforms through personalized experiences and swift query resolutions.

This AI-powered customer support chatbot is a cutting-edge tool that transforms customer engagement and drives revenue growth. It leverages advanced natural language processing (NLP) and machine learning algorithms to provide personalized, real-time support to customers across multiple channels. By automating routine inquiries, resolving complex issues, and offering proactive assistance, this chatbot empowers businesses to enhance customer satisfaction, increase conversion rates, and optimize their support operations.

Anthropic is a research and deployment company founded in 2021 by former OpenAI researchers Dario Amodei, Daniela Amodei, and Geoffrey Irving. The company is developing large language models, including Claude, a multimodal AI model that can perform a variety of language-related tasks, such as answering questions, generating text, and translating languages.

Wondershare Help Center provides comprehensive support for Wondershare products, including video editing, video creation, diagramming, PDF solutions, and data management. It offers a wide range of resources such as tutorials, FAQs, troubleshooting guides, and access to customer support.

Rank Math is an AI-powered SEO tool that helps you optimize your website for search engines. It offers a variety of features to help you improve your website's ranking, including keyword research, on-page optimization, and link building. Rank Math also provides detailed analytics to help you track your progress and identify areas for improvement.

Meetgeek.ai is an AI-powered platform designed to enhance virtual meetings and conferences. It offers a range of features to streamline the meeting experience, such as integrations with popular conferencing tools, detailed guides on settings and features, and regular updates to improve functionality. With a focus on user-friendly interfaces and seamless communication, Meetgeek.ai aims to revolutionize the way teams collaborate remotely.

Pulse is a world-class expert support tool for BigData stacks, specifically focusing on ensuring the stability and performance of Elasticsearch and OpenSearch clusters. It offers early issue detection, AI-generated insights, and expert support to optimize performance, reduce costs, and align with user needs. Pulse leverages AI for issue detection and root-cause analysis, complemented by real human expertise, making it a strategic ally in search cluster management.

The 'LLMs-in-science' repository is a collaborative environment for organizing papers related to large language models (LLMs) and autonomous agents in the field of chemistry. The goal is to discuss trend topics, challenges, and the potential for supporting scientific discovery in the context of artificial intelligence. The repository aims to maintain a systematic structure of the field and welcomes contributions from the community to keep the content up-to-date and relevant.

The AI Scientist is a comprehensive system for fully automatic scientific discovery, enabling Foundation Models to perform research independently. It aims to tackle the grand challenge of developing agents capable of conducting scientific research and discovering new knowledge. The tool generates papers on various topics using Large Language Models (LLMs) and provides a platform for exploring new research ideas. Users can create their own templates for specific areas of study and run experiments to generate papers. However, caution is advised as the codebase executes LLM-written code, which may pose risks such as the use of potentially dangerous packages and web access.

The 'machine-learning-research' repository is a comprehensive collection of resources related to mathematics, machine learning, deep learning, artificial intelligence, data science, and various scientific fields. It includes materials such as courses, tutorials, books, podcasts, communities, online courses, papers, and dissertations. The repository covers topics ranging from fundamental math skills to advanced machine learning concepts, with a focus on applications in healthcare, genetics, computational biology, precision health, and AI in science. It serves as a valuable resource for individuals interested in learning and researching in the fields of machine learning and related disciplines.

LLM4AD is an open-source Python-based platform leveraging Large Language Models (LLMs) for Automatic Algorithm Design (AD). It provides unified interfaces for methods, tasks, and LLMs, along with features like evaluation acceleration, secure evaluation, logs, GUI support, and more. The platform was originally developed for optimization tasks but is versatile enough to be used in other areas such as machine learning, science discovery, game theory, and engineering design. It offers various search methods and algorithm design tasks across different domains. LLM4AD supports remote LLM API, local HuggingFace LLM deployment, and custom LLM interfaces. The project is licensed under the MIT License and welcomes contributions, collaborations, and issue reports.

Lobe Chat is an open-source, modern-design ChatGPT/LLMs UI/Framework. Supports speech-synthesis, multi-modal, and extensible ([function call][docs-functionc-call]) plugin system. One-click **FREE** deployment of your private OpenAI ChatGPT/Claude/Gemini/Groq/Ollama chat application.

SurveyX is an advanced academic survey automation system that leverages Large Language Models (LLMs) to generate high-quality, domain-specific academic papers and surveys. Users can request comprehensive academic papers or surveys tailored to specific topics by providing a paper title and keywords for literature retrieval. The system streamlines academic research by automating paper creation, saving users time and effort in compiling research content.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

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.

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.

The 'Awesome LLMs Planning Reasoning' repository is a curated collection focusing on exploring the capabilities of Large Language Models (LLMs) in planning and reasoning tasks. It includes research papers, code repositories, and benchmarks that delve into innovative techniques, reasoning limitations, and standardized evaluations related to LLMs' performance in complex cognitive tasks. The repository serves as a comprehensive resource for researchers, developers, and enthusiasts interested in understanding the advancements and challenges in leveraging LLMs for planning and reasoning in real-world scenarios.

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.

This repository contains a comprehensive list of various summer schools and winter schools in the field of artificial intelligence, machine learning, medical imaging, and healthcare. It provides detailed information about upcoming events, including the name, venue, date, deadline, organizers, fees, and scholarship details. The repository aims to share opportunities with the community and aspiring AI researchers/engineers, data scientists.

The 'awesome-ai-llm4education' repository is a curated list of papers related to artificial intelligence (AI) and large language models (LLM) for education. It collects papers from top conferences, journals, and specialized domain-specific conferences, categorizing them based on specific tasks for better organization. The repository covers a wide range of topics including tutoring, personalized learning, assessment, material preparation, specific scenarios like computer science, language, math, and medicine, aided teaching, as well as datasets and benchmarks for educational research.

SciML.ai is an open source software organization dedicated to unifying packages for scientific machine learning. It focuses on developing modular scientific simulation support software, including differential equation solvers, inverse problems methodologies, and automated model discovery. The organization aims to provide a diverse set of tools with a common interface, creating a modular, easily-extendable, and highly performant ecosystem for scientific simulations. The website serves as a platform to showcase SciML organization's packages and share news within the ecosystem. Pull requests are encouraged for contributions.

Scientific Large Language Models (Sci-LLMs) is a repository that collects papers on scientific large language models, focusing on biology and chemistry domains. It includes textual, molecular, protein, and genomic languages, as well as multimodal language. The repository covers various large language models for tasks such as molecule property prediction, interaction prediction, protein sequence representation, protein sequence generation/design, DNA-protein interaction prediction, and RNA prediction. It also provides datasets and benchmarks for evaluating these models. The repository aims to facilitate research and development in the field of scientific language modeling.

With the scientific support of Prof. Kiskinov, SJD

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