Best AI tools for< Physics Researcher >

Siml.ai is a software platform designed for fast AI-driven physics simulations. It combines state-of-the-art machine learning with physics simulation to provide interactive visualization and high-performance AI-based numerical simulators. The platform offers tools like Model Engineer and Simulation Studio for training and optimizing simulators, managing datasets, and leveraging AI models for engineering and scientific problems. Siml.ai aims to democratize scientific-grade simulation tools by simplifying the development and deployment of physics-based simulations for engineers and researchers.

Jotlify is an AI-powered platform that simplifies complex research papers, making them accessible and easy to understand for students, researchers, professionals, and curious minds. It transforms dense academic content into engaging stories and insights, bridging the gap between complex research and easy understanding. With Jotlify, users can uncover stories and insights that can transform their understanding and impact various aspects of their lives.

Eureka Labs is a pioneering educational platform that leverages generative AI to provide an innovative learning experience. The platform combines the expertise of subject matter experts with AI Teaching Assistants to guide students through high-quality course materials. Their flagship product, LLM101n, offers an undergraduate-level class where students train their own AI. Eureka Labs aims to democratize education by making learning accessible and comprehensive for everyone.

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.

Anthropic is an AI safety and research company based in San Francisco. Our interdisciplinary team has experience across ML, physics, policy, and product. Together, we generate research and create reliable, beneficial AI systems.

Gauth is an AI-powered homework helper that provides step-by-step solutions to STEM problems. It utilizes advanced algorithms and AI technology to solve complex math, statistics, calculus, physics, chemistry, biology, and history questions. Gauth also offers live expert support, with thousands of real experts available 24/7 to provide detailed explanations and guidance. The app is designed to help students of all grades and levels conquer challenging homework problems and improve their understanding of STEM subjects.

Math Sniper is an AI-powered application designed to provide precise math solutions, exam preparation assistance, and exploration of mathematical concepts. The app offers step-by-step solutions to math challenges at all levels, connects users with math tutors for personalized help, and covers a wide range of subjects beyond mathematics, such as biology, chemistry, physics, history, economics, and language tasks. With features like Snap & Ask for instant answers, step-by-step explanations, and a user-friendly interface, Math Sniper aims to enhance users' understanding of complex concepts and facilitate learning in various disciplines.

arXiv.org is a free distribution service and an open-access archive for nearly 2.4 million scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics. Materials on this site are not peer-reviewed by arXiv.

Science in the News is a Harvard graduate student organization with a mission to bridge the communication gap between scientists and non-scientists. It provides a platform for researchers to share their work with the wider community in an accessible and engaging way. The website features articles, podcasts, videos, and other resources on a wide range of scientific topics, including astronomy, biology, chemistry, computer science, and physics.

Anthropic is an AI safety and research company based in San Francisco. Our interdisciplinary team has experience across ML, physics, policy, and product. Together, we generate research and create reliable, beneficial AI systems.

CCDS (Center for Computational & Data Sciences) is a research center at Independent University Bangladesh dedicated to artificial intelligence, data sciences, and computational science. The center has various wings focusing on AI, computational biology, physics, data science, human-computer interaction, and industry partnerships. CCDS explores the use of computation to understand nature and society, uncover hidden stories in data, and tackle complex challenges. The center collaborates with institutions like CERN and the Dunlap Institute for Astronomy and Astrophysics.

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.

LearnFast AI Physics Solver is an advanced AI-powered application designed to provide instant and accurate solutions to physics problems. It offers real-time physics solutions accessible anytime, anywhere, with support for text input, image uploads, and file formats. Users can benefit from free daily problem-solving, continuous upgrades for AI models, and a user-friendly interface. The application is suitable for high school students, university physics students, tutors, educators, lifelong learners, and physics enthusiasts.

Cascadeur is a standalone 3D software that lets you create keyframe animation, as well as clean up and edit any imported ones. Thanks to its AI-assisted and physics tools you can dramatically speed up the animation process and get high quality results. It works with .FBX, .DAE and .USD files making it easy to integrate into any animation workflow.

Quilter is an end-to-end PCB design platform that uses generative AI to automate the layout process. It can place components, route traces, define board stackups, and generate pours. Quilter is compatible with existing design tools and libraries, and it returns completed designs in the same file format they were submitted in. Quilter is currently in open beta and is free to use.

Viggle AI is a cutting-edge platform that allows users to effortlessly transform text into stunning 3D character animations. Powered by advanced JST-1 technology, this tool bridges the gap between professionals and hobbyists, offering a user-friendly interface for creating high-quality animations. With features like physics-based realism, community support, and a Discord server for collaboration, Viggle AI revolutionizes the animation creation process. Users can access the platform instantly via the web, join the vibrant creator community, and leverage the Viggle Bot for streamlined animation workflows.

Kling AI is a revolutionary text-to-video generation model that enables users to effortlessly craft artistic video productions. It boasts impressive capabilities in creating videos, making imagination come alive. With features like dynamic motion generation, long video creation, simulation of the physical world, conceptual combination, and cinematic video generation, Kling AI offers a unique and efficient video production experience. Users can enjoy generating videos with realistic movements, diverse aspect ratios, and cinematic quality, all powered by advanced AI technology.

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.

SnapXam is an AI-powered math tutor that helps students learn math and physics step-by-step. It offers a variety of features, including a math solver, step-by-step solutions, and video explanations. SnapXam is available on iOS and Android devices.

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.

llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.

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.

Awesome-Segment-Anything is a powerful tool for segmenting and extracting information from various types of data. It provides a user-friendly interface to easily define segmentation rules and apply them to text, images, and other data formats. The tool supports both supervised and unsupervised segmentation methods, allowing users to customize the segmentation process based on their specific needs. With its versatile functionality and intuitive design, Awesome-Segment-Anything is ideal for data analysts, researchers, content creators, and anyone looking to efficiently extract valuable insights from complex datasets.

Awesome Large Weather Models (LWMs) is a curated collection of articles and resources related to large weather models used in AI for Earth and AI for Science. It includes information on various cutting-edge weather forecasting models, benchmark datasets, and research papers. The repository serves as a hub for researchers and enthusiasts to explore the latest advancements in weather modeling and forecasting.

Awesome-Colorful-LLM is a meticulously assembled anthology of vibrant multimodal research focusing on advancements propelled by large language models (LLMs) in domains such as Vision, Audio, Agent, Robotics, and Fundamental Sciences like Mathematics. The repository contains curated collections of works, datasets, benchmarks, projects, and tools related to LLMs and multimodal learning. It serves as a comprehensive resource for researchers and practitioners interested in exploring the intersection of language models and various modalities for tasks like image understanding, video pretraining, 3D modeling, document understanding, audio analysis, agent learning, robotic applications, and mathematical research.

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

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.

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.

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.

This repository contains a collection of papers and code for the CVPR 2024 conference. The papers cover a wide range of topics in computer vision, including object detection, image segmentation, image generation, and video analysis. The code provides implementations of the algorithms described in the papers, making it easy for researchers and practitioners to reproduce the results and build upon the work of others. The repository is maintained by a team of researchers at the University of California, Berkeley.

Habitat-Sim is a high-performance physics-enabled 3D simulator with support for 3D scans of indoor/outdoor spaces, CAD models of spaces and piecewise-rigid objects, configurable sensors, robots described via URDF, and rigid-body mechanics. It prioritizes simulation speed over the breadth of simulation capabilities, achieving several thousand frames per second (FPS) running single-threaded and over 10,000 FPS multi-process on a single GPU when rendering a scene from the Matterport3D dataset. Habitat-Sim simulates a Fetch robot interacting in ReplicaCAD scenes at over 8,000 steps per second (SPS), where each ‘step’ involves rendering 1 RGBD observation (128×128 pixels) and rigid-body dynamics for 1/30sec.

Genesis is a physics platform designed for general purpose Robotics/Embodied AI/Physical AI applications. It includes a universal physics engine, a lightweight, ultra-fast, pythonic, and user-friendly robotics simulation platform, a powerful and fast photo-realistic rendering system, and a generative data engine that transforms user-prompted natural language description into various modalities of data. It aims to lower the barrier to using physics simulations, unify state-of-the-art physics solvers, and minimize human effort in collecting and generating data for robotics and other domains.

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.

PeriDyno is a CUDA-based, highly parallel physics engine targeted at providing real-time simulation of physical environments for intelligent agents. It is designed to be easy to use and integrate into existing projects, and it provides a wide range of features for simulating a variety of physical phenomena. PeriDyno is open source and available under the Apache 2.0 license.

UNav-Sim is an open-source underwater robotics simulator tool that leverages the power of Unreal Engine 5 (UE5) and AirSim to provide highly detailed rendering and simulation capabilities. With UNav-Sim, you can explore underwater terrains, design and test autonomous underwater vehicles (AUVs), and accelerate your learning and experimentation process in the field of underwater robotics.

WeatherGFT is a physics-AI hybrid model designed to generalize weather forecasts to finer-grained temporal scales beyond the training dataset. It incorporates physical partial differential equations (PDEs) into neural networks to simulate fine-grained physical evolution and correct biases. The model achieves state-of-the-art performance in forecasting tasks at different time scales, from nowcasting to medium-range forecasts, by utilizing a lead time-aware training framework and a carefully designed PDE kernel. WeatherGFT bridges the gap between nowcast and medium-range forecast by extending forecasting abilities to predict accurately at a 30-minute time scale.

Awesome-LLM is a curated list of resources related to large language models, focusing on papers, projects, frameworks, tools, tutorials, courses, opinions, and other useful resources in the field. It covers trending LLM projects, milestone papers, other papers, open LLM projects, LLM training frameworks, LLM evaluation frameworks, tools for deploying LLM, prompting libraries & tools, tutorials, courses, books, and opinions. The repository provides a comprehensive overview of the latest advancements and resources in the field of large language models.

Neurite is an innovative project that combines chaos theory and graph theory to create a digital interface that explores hidden patterns and connections for creative thinking. It offers a unique workspace blending fractals with mind mapping techniques, allowing users to navigate the Mandelbrot set in real-time. Nodes in Neurite represent various content types like text, images, videos, code, and AI agents, enabling users to create personalized microcosms of thoughts and inspirations. The tool supports synchronized knowledge management through bi-directional synchronization between mind-mapping and text-based hyperlinking. Neurite also features FractalGPT for modular conversation with AI, local AI capabilities for multi-agent chat networks, and a Neural API for executing code and sequencing animations. The project is actively developed with plans for deeper fractal zoom, advanced control over node placement, and experimental features.

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.

I'm like Einstein, making physics clear and visual.

I craft tricky physics sets for learning.

Your sympy expert for physics

Expert in advanced physics, insightful and precise

Edits texts in physics and biology with scholarly precision

Especialista em teses e dissertações de Física do Brasil

A GPT that provides lectures for String Theory

Solves Numericals in Physics, provides ideas to design an Internal Assessment (Physics Projects) and Extended Essays for IBDP Curriculum

A GPT that can provides lectures on Statistical Mechanics

Ce programme fournit des explications claires sur un large éventail de sujets liés à la physique. Les utilisateurs peuvent s'attendre à tout apprendre, des concepts de base de la physique aux théories plus complexes. Il est conçu pour rendre la physique facile à comprendre pour tout le monde.

Este programa ofrece explicaciones claras sobre una amplia gama de temas de física. Los usuarios pueden aprender desde conceptos básicos de física hasta teorías más complejas. Está diseñado para que la física sea fácil de entender para todo el mundo.

Dit programma biedt duidelijke uitleg over een breed scala aan natuurkundige onderwerpen. Gebruikers kunnen verwachten dat ze alles leren, van elementaire natuurkundige concepten tot complexere theorieën. Het is ontworpen om natuurkunde voor iedereen begrijpelijk te maken.