Best AI tools for< Computational Physicist >
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20 - AI tool Sites
Iambic Therapeutics
Iambic Therapeutics is a cutting-edge AI-driven drug discovery platform that tackles the most challenging design problems in drug discovery, addressing unmet patient need. Its physics-based AI algorithms drive a high-throughput experimental platform, converting new molecular designs to new biological insights each week. Iambic's platform optimizes target product profiles, exploring multiple profiles in parallel to ensure that molecules are designed to solve the right problems in disease biology. It also optimizes drug candidates, deeply exploring chemical space to reveal novel mechanisms of action and deliver diverse high-quality leads.
XtalPi
XtalPi is a world-leading technology company driven by artificial intelligence (AI) and robotics to innovate in the fields of life sciences and new materials. Founded in 2015 at the Massachusetts Institute of Technology (MIT), the company is committed to realizing digital and intelligent innovation in the fields of life sciences and new materials. Based on cutting-edge technologies and capabilities such as quantum physics, artificial intelligence, cloud computing, and large-scale experimental robot clusters, the company provides innovative technologies, services, and products for global industries such as biomedicine, chemicals, new energy, and new materials.
Julius AI
Julius AI is an advanced AI data analyst tool that allows users to analyze data with computational AI, chat with files to get expert-level insights, create sleek data visualizations, perform modeling and predictive forecasting, solve math, physics, and chemistry problems, generate polished analyses and summaries, save time by automating data work, and unlock statistical modeling without complexity. It offers features like generating visualizations, asking data questions, effortless cleaning, instant data export, creating animations, and supercharging data analysis. Julius AI is loved by over 1,200,000 users worldwide and is designed to help knowledge workers make the most out of their data.
Limbic
Limbic is a clinical AI application designed for mental healthcare providers to save time, improve outcomes, and maximize impact. It offers a suite of tools developed by a team of therapists, physicians, and PhDs in computational psychiatry. Limbic is known for its evidence-based approach, safety focus, and commitment to patient care. The application leverages AI technology to enhance various aspects of the mental health pathway, from assessments to therapeutic content delivery. With a strong emphasis on patient safety and clinical accuracy, Limbic aims to support clinicians in meeting the rising demand for mental health services while improving patient outcomes and preventing burnout.
Artificial Intelligence: Foundations of Computational Agents
Artificial Intelligence: Foundations of Computational Agents, 3rd edition by David L. Poole and Alan K. Mackworth, Cambridge University Press 2023, is a book about the science of artificial intelligence (AI). It presents artificial intelligence as the study of the design of intelligent computational agents. The book is structured as a textbook, but it is accessible to a wide audience of professionals and researchers. In the last decades we have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. This book provides an accessible synthesis of the field aimed at undergraduate and graduate students. It provides a coherent vision of the foundations of the field as it is today. It aims to provide that synthesis as an integrated science, in terms of a multi-dimensional design space that has been partially explored. As with any science worth its salt, artificial intelligence has a coherent, formal theory and a rambunctious experimental wing. The book balances theory and experiment, showing how to link them intimately together. It develops the science of AI together with its engineering applications.
Proscia
Proscia is a leading provider of digital pathology solutions for the modern laboratory. Its flagship product, Concentriq, is an enterprise pathology platform that enables anatomic pathology laboratories to achieve 100% digitization and deliver faster, more precise results. Proscia also offers a range of AI applications that can be used to automate tasks, improve diagnostic accuracy, and accelerate research. The company's mission is to perfect cancer diagnosis with intelligent software that changes the way the world practices pathology.
Live Portrait Ai Generator
Live Portrait Ai Generator is an AI application that transforms static portrait images into lifelike videos using advanced animation technology. Users can effortlessly animate their portraits, fine-tune animations, unleash artistic styles, and make memories move with text, music, and other elements. The tool offers a seamless stitching technology and retargeting capabilities to achieve perfect results. Live Portrait Ai enhances generation quality and generalization ability through a mixed image-video training strategy and network architecture upgrades.
Cradle
Cradle is a protein engineering platform that uses machine learning to design improved protein sequences. It allows users to import assay data, generate new sequences, test them in the lab, and import the results to improve the model. Cradle can be used to optimize multiple properties of a protein simultaneously, and it has been used by leading biotech teams to accelerate new and ongoing projects.
Owkin
Owkin is a full-stack AI biotech company that integrates the best of human and artificial intelligence to deliver better drugs and diagnostics at scale. By understanding complex biology through AI, Owkin identifies new treatments, de-risks and accelerates clinical trials, and builds diagnostic tools to reduce time to impact for patients.
Variational AI
Variational AI is a company that uses generative AI to discover novel drug-like small molecules with optimized properties for defined targets. Their platform, Enki™, is the first commercially accessible foundation model for small molecules. It is designed to make generating novel molecule structures easy, with no data required. Users simply define their target product profile (TPP) and Enki does the rest. Enki is an ensemble of generative algorithms trained on decades worth of experimental data with proven results. The company was founded in September 2019 and is based in Vancouver, BC, Canada.
NLTK
NLTK (Natural Language Toolkit) is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum. Thanks to a hands-on guide introducing programming fundamentals alongside topics in computational linguistics, plus comprehensive API documentation, NLTK is suitable for linguists, engineers, students, educators, researchers, and industry users alike.
Lavo Life Sciences
Lavo Life Sciences is an AI-accelerated crystal structure prediction application that helps in drug development by providing accurate predictions. The platform offers solutions to de-risk pipelines, optimize solid-state formulations, and avoid late-stage surprises using AI technology. Lavo Life Sciences combines the expertise of chemists and engineers in AI and computational chemistry to deliver innovative solutions for drug development teams. The application aims to reduce turnaround time for crystal form identification, minimize risks of unexpected crystal forms, optimize drug formulations, and discover novel polymorphs with improved properties.
Bay Area AI
Bay Area AI is a technical AI meetup group based in San Francisco, CA, consisting of startup engineers, research scientists, computational linguists, mathematicians, and philosophers. The group focuses on understanding the meaning of text, reasoning, and human intent through technology to build new businesses and enhance the human experience in the modern connected world. They work on building systems with Machine Learning on top of Data Pipelines, exploring open-source solutions, and modeling human behavior in industry for practical results.
Wolfram
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.
Wolfram|Alpha
Wolfram|Alpha is a computational knowledge engine that answers questions using data, algorithms, and artificial intelligence. It can perform calculations, generate graphs, and provide information on a wide range of topics, including mathematics, science, history, and culture. Wolfram|Alpha is used by students, researchers, and professionals around the world to solve problems, learn new things, and make informed decisions.
Altair
Altair is a global leader in computational intelligence, offering software and cloud solutions in simulation, HPC, data analytics, and AI. The platform provides advanced technology for accelerating AI adoption, powering engineering processes, and enabling sustainability solutions across various industries. Altair's products and platforms cater to diverse sectors such as aerospace, automotive, healthcare, and more, with a focus on digital twin technology, generative AI, and cloud computing. The company also hosts events, webinars, and training programs to support users in leveraging their tools effectively.
Spectre
Spectre is an AI-powered shutter for iPhone that enables users to create amazing long exposures effortlessly. It simplifies the technical aspects of long exposures, such as camera stability and light estimation, making it accessible to all users. Spectre is designed by the team behind Halide, incorporating cutting-edge computational photography technologies like AI scene detection and intelligent exposure. The app is user-friendly, with a dark UI for night shooting and intuitive controls for a seamless experience. Spectre is not just a camera app but a showcase of high-tech features like DCI-P3 Wide Color Gamut and Machine Learning, setting it apart as a top camera application on the App Store.
Institute for Protein Design
The Institute for Protein Design is a research institute at the University of Washington that uses computational design to create new proteins that solve modern challenges in medicine, technology, and sustainability. The institute's research focuses on developing new protein therapeutics, vaccines, drug delivery systems, biological devices, self-assembling nanomaterials, and bioactive peptides. The institute also has a strong commitment to responsible AI development and has developed a set of principles to guide its use of AI in research.
Allchemy
Allchemy is a resource-aware AI platform for drug discovery. It combines state-of-the-art computational synthesis with AI algorithms to predict molecular properties. Within minutes, Allchemy creates thousands of synthesizable lead candidates meeting user-defined profiles of drug-likeness, affinity towards specific proteins, toxicity, and a range of other physical-chemical measures. Allchemy encompasses the entire resource-to-drug design process and has been used in academic, corporate and classified environments worldwide to: Design synthesizable leads targeting specific proteins Evolve scaffolds similar to desired drugs Design “circular” drug syntheses from renewable materials Interface with and instruct automated synthesis platforms and optimize pilot-scale processes Operate “iterative synthesis” schemes Predict side reactions and create forensic “synthetic signatures” of hazardous/toxic molecules Design synthetic degradation and recovery cycles for various types of feedstocks and functional target molecules
Phenaki
Phenaki is a model capable of generating realistic videos from a sequence of textual prompts. It is particularly challenging to generate videos from text due to the computational cost, limited quantities of high-quality text-video data, and variable length of videos. To address these issues, Phenaki introduces a new causal model for learning video representation, which compresses the video to a small representation of discrete tokens. This tokenizer uses causal attention in time, which allows it to work with variable-length videos. To generate video tokens from text, Phenaki uses a bidirectional masked transformer conditioned on pre-computed text tokens. The generated video tokens are subsequently de-tokenized to create the actual video. To address data issues, Phenaki demonstrates how joint training on a large corpus of image-text pairs as well as a smaller number of video-text examples can result in generalization beyond what is available in the video datasets. Compared to previous video generation methods, Phenaki can generate arbitrarily long videos conditioned on a sequence of prompts (i.e., time-variable text or a story) in an open domain. To the best of our knowledge, this is the first time a paper studies generating videos from time-variable prompts. In addition, the proposed video encoder-decoder outperforms all per-frame baselines currently used in the literature in terms of spatio-temporal quality and the number of tokens per video.
20 - Open Source Tools
PaddleScience
PaddleScience is a scientific computing suite developed based on the deep learning framework PaddlePaddle. It utilizes the learning ability of deep neural networks and the automatic (higher-order) differentiation mechanism of PaddlePaddle to solve problems in physics, chemistry, meteorology, and other fields. It supports three solving methods: physics mechanism-driven, data-driven, and mathematical fusion, and provides basic APIs and detailed documentation for users to use and further develop.
awesome_ai_for_programmers
Репозиторий содержит информацию о применении искусственного интеллекта в разработке программного обеспечения. В частности, рассматриваются кейсы использования ChatGPT и других языковых моделей для автоматизации задач разработки, таких как написание кода, тестирование, рефакторинг и генерация документации.
matsciml
The Open MatSci ML Toolkit is a flexible framework for machine learning in materials science. It provides a unified interface to a variety of materials science datasets, as well as a set of tools for data preprocessing, model training, and evaluation. The toolkit is designed to be easy to use for both beginners and experienced researchers, and it can be used to train models for a wide range of tasks, including property prediction, materials discovery, and materials design.
SciMLBenchmarks.jl
SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem, including: * Benchmarks of equation solver implementations * Speed and robustness comparisons of methods for parameter estimation / inverse problems * Training universal differential equations (and subsets like neural ODEs) * Training of physics-informed neural networks (PINNs) * Surrogate comparisons, including radial basis functions, neural operators (DeepONets, Fourier Neural Operators), and more The SciML Bench suite is made to be a comprehensive open source benchmark from the ground up, covering the methods of computational science and scientific computing all the way to AI for science.
DNAnalyzer
DNAnalyzer is a nonprofit organization dedicated to revolutionizing DNA analysis through AI-powered tools. It aims to democratize access to DNA analysis for a deeper understanding of human health and disease. The tool provides innovative AI-powered analysis and interpretive tools to empower geneticists, physicians, and researchers to gain deep insights into DNA sequences, revolutionizing how we understand human health and disease.
machine-learning-research
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.
awesome-AI4MolConformation-MD
The 'awesome-AI4MolConformation-MD' repository focuses on protein conformations and molecular dynamics using generative artificial intelligence and deep learning. It provides resources, reviews, datasets, packages, and tools related to AI-driven molecular dynamics simulations. The repository covers a wide range of topics such as neural networks potentials, force fields, AI engines/frameworks, trajectory analysis, visualization tools, and various AI-based models for protein conformational sampling. It serves as a comprehensive guide for researchers and practitioners interested in leveraging AI for studying molecular structures and dynamics.
AI2BMD
AI2BMD is a program for efficiently simulating protein molecular dynamics with ab initio accuracy. The repository contains datasets, simulation programs, and public materials related to AI2BMD. It provides a Docker image for easy deployment and a standalone launcher program. Users can run simulations by downloading the launcher script and specifying simulation parameters. The repository also includes ready-to-use protein structures for testing. AI2BMD is designed for x86-64 GNU/Linux systems with recommended hardware specifications. The related research includes model architectures like ViSNet, Geoformer, and fine-grained force metrics for MLFF. Citation information and contact details for the AI2BMD Team are provided.
TornadoVM
TornadoVM is a plug-in to OpenJDK and GraalVM that allows programmers to automatically run Java programs on heterogeneous hardware. TornadoVM targets OpenCL, PTX and SPIR-V compatible devices which include multi-core CPUs, dedicated GPUs (Intel, NVIDIA, AMD), integrated GPUs (Intel HD Graphics and ARM Mali), and FPGAs (Intel and Xilinx).
Awesome-AIGC-3D
Awesome-AIGC-3D is a curated list of awesome AIGC 3D papers, inspired by awesome-NeRF. It aims to provide a comprehensive overview of the state-of-the-art in AIGC 3D, including papers on text-to-3D generation, 3D scene generation, human avatar generation, and dynamic 3D generation. The repository also includes a list of benchmarks and datasets, talks, companies, and implementations related to AIGC 3D. The description is less than 400 words and provides a concise overview of the repository's content and purpose.
AIlice
AIlice is a fully autonomous, general-purpose AI agent that aims to create a standalone artificial intelligence assistant, similar to JARVIS, based on the open-source LLM. AIlice achieves this goal by building a "text computer" that uses a Large Language Model (LLM) as its core processor. Currently, AIlice demonstrates proficiency in a range of tasks, including thematic research, coding, system management, literature reviews, and complex hybrid tasks that go beyond these basic capabilities. AIlice has reached near-perfect performance in everyday tasks using GPT-4 and is making strides towards practical application with the latest open-source models. We will ultimately achieve self-evolution of AI agents. That is, AI agents will autonomously build their own feature expansions and new types of agents, unleashing LLM's knowledge and reasoning capabilities into the real world seamlessly.
MATLAB-Simulink-Challenge-Project-Hub
MATLAB-Simulink-Challenge-Project-Hub is a repository aimed at contributing to the progress of engineering and science by providing challenge projects with real industry relevance and societal impact. The repository offers a wide range of projects covering various technology trends such as Artificial Intelligence, Autonomous Vehicles, Big Data, Computer Vision, and Sustainability. Participants can gain practical skills with MATLAB and Simulink while making a significant contribution to science and engineering. The projects are designed to enhance expertise in areas like Sustainability and Renewable Energy, Control, Modeling and Simulation, Machine Learning, and Robotics. By participating in these projects, individuals can receive official recognition for their problem-solving skills from technology leaders at MathWorks and earn rewards upon project completion.
LLM-Agents-Papers
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.
awesome-mobile-robotics
The 'awesome-mobile-robotics' repository is a curated list of important content related to Mobile Robotics and AI. It includes resources such as courses, books, datasets, software and libraries, podcasts, conferences, journals, companies and jobs, laboratories and research groups, and miscellaneous resources. The repository covers a wide range of topics in the field of Mobile Robotics and AI, providing valuable information for enthusiasts, researchers, and professionals in the domain.
Open-Sora-Plan
Open-Sora-Plan is a project that aims to create a simple and scalable repo to reproduce Sora (OpenAI, but we prefer to call it "ClosedAI"). The project is still in its early stages, but the team is working hard to improve it and make it more accessible to the open-source community. The project is currently focused on training an unconditional model on a landscape dataset, but the team plans to expand the scope of the project in the future to include text2video experiments, training on video2text datasets, and controlling the model with more conditions.
habitat-lab
Habitat-Lab is a modular high-level library for end-to-end development in embodied AI. It is designed to train agents to perform a wide variety of embodied AI tasks in indoor environments, as well as develop agents that can interact with humans in performing these tasks.
16 - OpenAI Gpts
StephenBot
A digital homage to honor Stephen Wolfram's impact on computational science and technology and to celebrate his dedication to public education, powered by Stephen Wolfram's wealth of public presentations, writings, and live streams.
Formula Generator
Expert in generating and explaining mathematical, chemical, and computational formulas.
ChatPNP
Blends academic insights & accessible explanations on P vs NP, drawing from Lance Fortnow's works.