Best AI tools for< Accelerate Discovery >

Kuano is an AI tool that focuses on redefining drug discovery using Quantum and AI technologies. The platform offers world-class scientific expertise in quantum physics, AI, and medicinal chemistry to revolutionize the drug design process. Kuano aims to leverage cutting-edge technologies to accelerate the discovery of new drugs and improve healthcare outcomes.

Genesis Therapeutics is a cutting-edge platform that leverages advanced molecular AI technology to unlock challenging protein targets and develop highly potent and selective medicines. The platform, known as GEMS, combines AI and physics research to accelerate drug discovery processes. Genesis Therapeutics is dedicated to designing breakthrough medicines for complex targets, driven by a team of collaborative experts in AI and biotech.

JADBio is an automated machine learning (AutoML) platform designed to accelerate biomarker discovery and drug development processes. It offers a no-code solution that automates the discovery of biomarkers and interprets their role based on research needs. JADBio can parse multi-omics data, including genomics, transcriptome, metagenome, proteome, metabolome, phenotype/clinical data, and images, enabling users to efficiently discover insights for various conditions such as cancer, immune system disorders, chronic diseases, infectious diseases, and mental health.

Synthace is a software and expertise platform designed for Discovery Biology Teams to streamline and optimize their experiments in assay development, media optimization, and purification process development. The platform offers software solutions, training, and on-site support from specialists to help scientists conduct experiments more efficiently and effectively. By leveraging multifactorial methods and automation, Synthace aims to accelerate drug discovery processes and deliver faster, definitive results.

Insitro is a drug discovery and development company that uses machine learning and data to identify and develop new medicines. The company's platform integrates in vitro cellular data produced in its labs with human clinical data to help redefine disease. Insitro's pipeline includes wholly-owned and partnered therapeutic programs in metabolism, oncology, and neuroscience.

Recursion is a techbio company that uses artificial intelligence to accelerate drug discovery. The company's platform combines hardware, software, and data to create a more efficient and effective drug discovery process. Recursion has a broad pipeline of drug candidates in development, and it has partnered with several leading pharmaceutical companies. The company is headquartered in Salt Lake City, Utah.

BenevolentAI is a leader in applying advanced AI to accelerate biopharma drug discovery blending science and technology with a focus on finding solutions for complex diseases. We empower both biopharmaceutical companies and our internal scientists to harness the full potential of data and AI to accelerate the next generation of scientific advances. We have built our AI-enabled drug discovery engine to drive a revolution in drug discovery. The Benevolent Platform™ unlocks the power of a vast biomedical data landscape to provide a multidimensional representation of human biology across all diseases. We believe this approach will improve the probability of clinical success, and help us deliver life-changing treatments to patients – because it matters.

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.

Ignota Labs is a technology company focused on rescuing failing drugs and bringing new life to abandoned projects, ultimately providing hope to patients. The company utilizes a proprietary AI model, SAFEPATH, which applies deep learning to bioinformatics and cheminformatics datasets to solve drug safety issues. Ignota Labs aims to identify promising drug targets, address safety problems in clinical trials, and accelerate the delivery of therapeutically effective drugs to patients.

Scopilot AI is an AI-powered tool designed to accelerate software project scoping by generating project scope, features, user stories, and clarification questions based on the initial project description. It helps software agencies and individuals in defining a clear scope and facilitating the product discovery and specification phase. The tool automates the process of generating UI screens, user actions, components, and database schema, making project scoping 10x faster and more efficient.

SOMA is a Research Automation Platform designed to accelerate medical innovation by automating the process of analyzing medical research articles. It extracts important concepts, identifies causal and associative relationships, and organizes information into a specialized database forming a knowledge graph. Researchers can retrieve causal chains, access specific research articles, and perform tasks like drug repurposing, target discovery, and literature review efficiently. The platform offers API access, community support, and freemium sign-up options.

Valo is a company that uses AI-driven technology to transform the discovery and development of life-changing medicines. They combine machine learning, tissue biology, and patient data to create a suite of powerful capabilities that bring the future of drug discovery and development to bear. Valo's team of software engineers, data scientists, biologists, medicinal chemists, and big-picture thinkers are dedicated to advancing the combined power of technology and patient data.

Automation Anywhere is a leading provider of intelligent automation and process intelligence solutions. The company's platform combines robotic process automation (RPA), artificial intelligence (AI), and analytics to help organizations automate complex business processes, improve efficiency, and reduce costs. Automation Anywhere's platform is used by a wide range of organizations, including Fortune 500 companies and government agencies. The company has a global presence with offices in over 40 countries.

The AI Summit London is a premier event that celebrates commercial AI applications, bringing together technologists and business professionals to explore real-world AI implementations. The event offers unparalleled learning opportunities, deep-dive discovery, and extensive networking with heavyweight speakers. Attendees can expect to engage with cutting-edge AI demos, immersive fringe features, and VIP experiences, all aimed at accelerating their AI journey and transforming theoretical discussions into practical and profitable applications.

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.

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.

Rhino.ai is a SaaS application company that offers an all-in-one AI platform for transforming legacy systems or building new applications. The platform helps organizations execute large transformations, accelerate legacy migrations, re-engineer applications, and develop applications faster with AI-driven modeling and automation. Rhino.ai empowers businesses to modernize their systems, reduce technical debt, avoid vendor lock-in, and gain leverage in product licensing negotiations. The platform provides a unified solution for discovery, design, coding, and deployment, enabling faster decision-making and streamlined modernization processes.

Crunchbase Solutions is an AI-powered company intelligence platform that helps users find prospects, investors, conduct market research, enrich databases, and build products. The platform offers products like Crunchbase Pro and Crunchbase Enterprise, providing personalized recommendations, AI-powered insights, and tools for company discovery and research. With a focus on leveraging AI technology, Crunchbase Solutions aims to assist users in making better decisions about investments, pipeline management, fundraising, partnerships, and product development. The platform's data is sourced from various contributors, partners, in-house experts, and AI algorithms, ensuring quality and compliance with SOC 2 Type II standards.

neurons.bio is an AI application that offers a unique collection of over 100 AI agents designed for drug development, medicine, and life science research. These agents perform specific tasks efficiently, retrieve data from various sources, and provide insights to accelerate research processes. The platform aims to revolutionize drug discovery and development by integrating cutting-edge LLM technology with domain-specific agents, reducing research costs and time to clinic.

Nucleai is an AI-driven spatial biomarker analysis tool that leverages military intelligence-grade geospatial AI methods to analyze complex cellular interactions in a patient's biopsy. The platform offers a first-of-its-kind multimodal solution by ingesting images from various modalities and delivering actionable insights to optimize biomarker scoring, predict response to therapy, and revolutionize disease diagnosis and treatment.

Generative-AI-Drug-Discovery is a public repository on GitHub focused on using tensor network machine learning approaches to accelerate GenAI for drug discovery. The repository aims to implement effective architectures and methodologies into Large Language Models (LLMs) to enhance Drug Discovery Generative AI performance.

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.

NVIDIA BioNeMo Framework is a collection of programming tools, libraries, and models for computational drug discovery. It accelerates building and adapting biomolecular AI models by providing domain-specific, optimized models and tooling for GPU-based computational resources. The framework offers comprehensive documentation and support for both community and enterprise users.

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.

AI-Drug-Discovery-Design is a repository focused on Artificial Intelligence-assisted Drug Discovery and Design. It explores the use of AI technology to accelerate and optimize the drug development process. The advantages of AI in drug design include speeding up research cycles, improving accuracy through data-driven models, reducing costs by minimizing experimental redundancies, and enabling personalized drug design for specific patients or disease characteristics.

FuseMedML is a Python framework designed to accelerate machine learning-based discovery in the medical field by promoting code reuse. It provides a flexible design concept where data is stored in a nested dictionary, allowing easy handling of multi-modality information. The framework includes components for creating custom models, loss functions, metrics, and data processing operators. Additionally, FuseMedML offers 'batteries included' key components such as fuse.data for data processing, fuse.eval for model evaluation, and fuse.dl for reusable deep learning components. It supports PyTorch and PyTorch Lightning libraries and encourages the creation of domain extensions for specific medical domains.

NoLabs is an open-source biolab that provides easy access to state-of-the-art models for bio research. It supports various tasks, including drug discovery, protein analysis, and small molecule design. NoLabs aims to accelerate bio research by making inference models accessible to everyone.

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.

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.

Taiyi (太一) is a bilingual large language model fine-tuned for diverse biomedical tasks. It aims to facilitate communication between healthcare professionals and patients, provide medical information, and assist in diagnosis, biomedical knowledge discovery, drug development, and personalized healthcare solutions. The model is based on the Qwen-7B-base model and has been fine-tuned using rich bilingual instruction data. It covers tasks such as question answering, biomedical dialogue, medical report generation, biomedical information extraction, machine translation, title generation, text classification, and text semantic similarity. The project also provides standardized data formats, model training details, model inference guidelines, and overall performance metrics across various BioNLP tasks.

LLM4DB is a repository focused on the intersection of Large Language Models (LLMs) and Database technologies. It covers various aspects such as data processing, data analysis, database optimization, and data management for LLMs. The repository includes research papers, tools, and techniques related to leveraging LLMs for tasks like data cleaning, entity matching, schema matching, data discovery, NL2SQL, data exploration, data visualization, knob tuning, query optimization, and database diagnosis.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

The LLM RAG Workshop repository provides a workshop on using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to generate and understand text in a human-like manner. It includes instructions on setting up the environment, indexing Zoomcamp FAQ documents, creating a Q&A system, and using OpenAI for generation based on retrieved information. The repository focuses on enhancing language model responses with retrieved information from external sources, such as document databases or search engines, to improve factual accuracy and relevance of generated text.

SuperKnowa is a fast framework to build Enterprise RAG (Retriever Augmented Generation) Pipelines at Scale, powered by watsonx. It accelerates Enterprise Generative AI applications to get prod-ready solutions quickly on private data. The framework provides pluggable components for tackling various Generative AI use cases using Large Language Models (LLMs), allowing users to assemble building blocks to address challenges in AI-driven text generation. SuperKnowa is battle-tested from 1M to 200M private knowledge base & scaled to billions of retriever tokens.

LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.

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