Best AI tools for< Robotics Researcher >

Hanson Robotics is an AI and robotics company dedicated to creating socially intelligent machines that enrich the quality of our lives. The company's team of renowned AI scientists conducts advanced research to build the most compelling robotics and AI platform for research, media, and service applications.

MetaDevo is an AI tool that focuses on strong AI, 4E, and cognitive architectures. It provides insights and information on AI, robotics, cognitive science, technology, and more. The platform covers a wide range of topics related to artificial intelligence, robotics, and emerging technologies, offering valuable resources and discussions for enthusiasts and professionals in the field.

FOXSY.AI is an AI application that combines robotics and AI to create fully autonomous humanoid robot soccer players. The project aims to achieve the RoboCup final goal of having a team of robots win a soccer game against the winner of the most recent World Cup. The $FOXSY token powers the implementation of robotics and AI research, enabling users to engage with the RoboCup mechanics for entertainment value. The application offers various tools and features for users to participate in online tournaments, customize players, and analyze game strategies.

Roboto AI is an advanced platform that allows users to curate, transform, and analyze robotics data at scale. It provides features for data management, actions, events, search capabilities, and SDK integration. The application helps users understand complex machine data through multimodal queries and custom actions, enabling efficient data processing and collaboration within teams.

Artificial Intelligence + is a comprehensive platform focusing on AI, Robotics, and IoT. It covers a wide range of topics related to artificial intelligence, including the dangers, impacts, and advancements in the field. The platform also delves into robotics, space exploration, and the intersection of AI with various industries. With a mix of articles, blogs, and expert insights, Artificial Intelligence + serves as a valuable resource for individuals interested in staying updated on the latest trends and developments in the AI landscape.

Dobb·E is an open-source, general framework for learning household robotic manipulation. It aims to create a generalist machine for homes that can adapt and learn from users' needs efficiently. Dobb·E can learn a new task with just five minutes of demonstration, achieving an 81% success rate in various household environments. The project focuses on accelerating research on home robots and making robot assistants a common sight in every home.

NVIDIA is a world leader in artificial intelligence computing. The company's products and services are used by businesses and governments around the world to develop and deploy AI applications. NVIDIA's AI platform includes hardware, software, and tools that make it easy to build and train AI models. The company also offers a range of cloud-based AI services that make it easy to deploy and manage AI applications. NVIDIA's AI platform is used in a wide variety of industries, including healthcare, manufacturing, retail, and transportation. The company's AI technology is helping to improve the efficiency and accuracy of a wide range of tasks, from medical diagnosis to product design.

Figure is a pioneering AI robotics company that is revolutionizing the industry by introducing a general-purpose humanoid robot to the global workforce. By combining cutting-edge AI technology with the dexterity of the human form, Figure aims to enhance human capabilities, address labor shortages, and improve workplace safety. The company's innovative approach is set to transform various sectors such as manufacturing, logistics, warehousing, and retail. With a team of experts boasting over 100 years of combined experience in AI and humanoid robotics, Figure is at the forefront of shaping the future of work.

Duckietown is a platform for delivering cutting-edge robotics and AI learning experiences. It offers teaching resources to instructors, hands-on activities to learners, an accessible research platform to researchers, and a state-of-the-art ecosystem for professional training. Duckietown's mission is to make robotics and AI education state-of-the-art, hands-on, and accessible to all.

Bifrost AI is a data generation engine designed for AI and robotics applications. It enables users to train and validate AI models faster by generating physically accurate synthetic datasets in 3D simulations, eliminating the need for real-world data. The platform offers pixel-perfect labels, scenario metadata, and a simulated 3D world to enhance AI understanding. Bifrost AI empowers users to create new scenarios and datasets rapidly, stress test AI perception, and improve model performance. It is built for teams at every stage of AI development, offering features like automated labeling, class imbalance correction, and performance enhancement.

ThinkML is a comprehensive platform that provides the latest news, articles, and blogs about Artificial Intelligence. It covers a wide range of topics such as Explainable AI (XAI), AI video generator tools, AI voice over generator tools, AI tools for architects, AI image generator tools, AI tools for coding, AI video quality enhancer tools, and more. The platform aims to educate and inform users about the advancements in AI technology, trends to watch, achievements, and applications in various industries. ThinkML also offers insights on deep learning, metaverse, LLMs, and provides training resources for individuals interested in AI and related fields.

Scale AI is an AI tool that accelerates the development of AI applications for various sectors including enterprise, government, and automotive industries. It offers solutions for training models, fine-tuning, generative AI, and model evaluations. Scale Data Engine and GenAI Platform enable users to leverage enterprise data effectively. The platform collaborates with leading AI models and provides high-quality data for public and private sector applications.

DWE.ai is an AI-powered platform specializing in DeepWater Exploration. The platform offers cutting-edge marine optics for crystal clear underwater imaging data, empowering marine robotics, surface vehicles, aquaculture farms, and aerial drones with advanced mapping and vision capabilities. DWE.ai provides cost-effective equipment for monitoring subsea assets, conducting detailed inspections, and collecting essential environmental data to revolutionize underwater research and operations.

Tech Xplore is a leading source of science and technology news, covering the latest breakthroughs in research and innovation across a wide range of disciplines, including artificial intelligence, robotics, computer science, and more. The website provides in-depth articles, interviews with experts, and up-to-date information on the latest developments in the field of AI and its applications.

NORA (Norwegian Artificial Intelligence Research Consortium) is a collaborative platform between 8 universities, 5 university colleges, and 5 research institutes in Norway focusing on AI, machine learning, and robotics. The consortium aims to enhance research, education, and innovation in these fields, fostering a vibrant community of researchers, educators, and innovators.

The NVIDIA Toronto AI Lab is a research laboratory focused on advancing the state-of-the-art in artificial intelligence. The lab's researchers are working on a wide range of AI topics, including deep learning, machine learning, computer vision, natural language processing, and robotics.

Artificial Intelligence: A Modern Approach, 4th US ed. is the authoritative, most-used AI textbook, adopted by over 1500 schools. It covers the entire spectrum of AI, from the fundamentals to the latest advances. The book is written in a clear and concise style, with a wealth of examples and exercises. It is suitable for both undergraduate and graduate students, as well as professionals in the field of AI.

Molmo AI is a powerful, open-source multimodal AI model revolutionizing visual understanding. It helps developers easily build tools that can understand images and interact with the world in useful ways. Molmo AI offers exceptional image understanding, efficient data usage, open and accessible features, on-device compatibility, and a new era in multimodal AI development. It closes the gap between open and closed AI models, empowers the AI community with open access, and efficiently utilizes data for superior performance.

The Berkeley Artificial Intelligence Research (BAIR) Lab is a renowned research lab at UC Berkeley focusing on computer vision, machine learning, natural language processing, planning, control, and robotics. With over 50 faculty members and 300 graduate students, BAIR conducts research on fundamental advances in AI and interdisciplinary themes like multi-modal deep learning and human-compatible AI.

AIhub is a platform that connects the AI community and the world by providing news articles, opinions, and education related to artificial intelligence. It serves as a hub for sharing information, resources, and contributing to the advancement of AI technologies. The platform covers a wide range of topics such as AI research, machine learning, robotics, and the societal impact of AI.

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.

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.

Awesome-Robotics-3D is a curated list of 3D Vision papers related to Robotics domain, focusing on large models like LLMs/VLMs. It includes papers on Policy Learning, Pretraining, VLM and LLM, Representations, and Simulations, Datasets, and Benchmarks. The repository is maintained by Zubair Irshad and welcomes contributions and suggestions for adding papers. It serves as a valuable resource for researchers and practitioners in the field of Robotics and Computer Vision.

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.

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.

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.

The Everything-LLMs-And-Robotics repository is the world's largest GitHub repository focusing on the intersection of Large Language Models (LLMs) and Robotics. It provides educational resources, research papers, project demos, and Twitter threads related to LLMs, Robotics, and their combination. The repository covers topics such as reasoning, planning, manipulation, instructions and navigation, simulation frameworks, perception, and more, showcasing the latest advancements in the field.

NeMo Framework is a generative AI framework built for researchers and pytorch developers working on large language models (LLMs), multimodal models (MM), automatic speech recognition (ASR), and text-to-speech synthesis (TTS). The primary objective of NeMo is to provide a scalable framework for researchers and developers from industry and academia to more easily implement and design new generative AI models by being able to leverage existing code and pretrained models.

TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

This repository, Awesome-LLM-Survey, serves as a comprehensive collection of surveys related to Large Language Models (LLM). It covers various aspects of LLM, including instruction tuning, human alignment, LLM agents, hallucination, multi-modal capabilities, and more. Researchers are encouraged to contribute by updating information on their papers to benefit the LLM survey community.

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.

Cool-GenAI-Fashion-Papers is a curated list of resources related to GenAI-Fashion, including papers, workshops, companies, and products. It covers a wide range of topics such as fashion design synthesis, outfit recommendation, fashion knowledge extraction, trend analysis, and more. The repository provides valuable insights and resources for researchers, industry professionals, and enthusiasts interested in the intersection of AI and fashion.

Awesome-Papers-Autonomous-Agent is a curated collection of recent papers focusing on autonomous agents, specifically interested in RL-based agents and LLM-based agents. The repository aims to provide a comprehensive resource for researchers and practitioners interested in intelligent agents that can achieve goals, acquire knowledge, and continually improve. The collection includes papers on various topics such as instruction following, building agents based on world models, using language as knowledge, leveraging LLMs as a tool, generalization across tasks, continual learning, combining RL and LLM, transformer-based policies, trajectory to language, trajectory prediction, multimodal agents, training LLMs for generalization and adaptation, task-specific designing, multi-agent systems, experimental analysis, benchmarking, applications, algorithm design, and combining with RL.

Awesome AI is a curated list of artificial intelligence resources including courses, tools, apps, and open-source projects. It covers a wide range of topics such as machine learning, deep learning, natural language processing, robotics, conversational interfaces, data science, and more. The repository serves as a comprehensive guide for individuals interested in exploring the field of artificial intelligence and its applications across various domains.

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.

ai-collective-tools is an open-source community dedicated to creating a comprehensive collection of AI tools for developers, researchers, and enthusiasts. The repository provides a curated selection of AI tools and resources across various categories such as 3D, Agriculture, Art, Audio Editing, Avatars, Chatbots, Code Assistant, Cooking, Copywriting, Crypto, Customer Support, Dating, Design Assistant, Design Generator, Developer, E-Commerce, Education, Email Assistant, Experiments, Fashion, Finance, Fitness, Fun Tools, Gaming, General Writing, Gift Ideas, HealthCare, Human Resources, Image Classification, Image Editing, Image Generator, Interior Designing, Legal Assistant, Logo Generator, Low Code, Models, Music, Paraphraser, Personal Assistant, Presentations, Productivity, Prompt Generator, Psychology, Real Estate, Religion, Research, Resume, Sales, Search Engine, SEO, Shopping, Social Media, Spreadsheets, SQL, Startup Tools, Story Teller, Summarizer, Testing, Text to Speech, Text to Image, Transcriber, Travel, Video Editing, Video Generator, Weather, Writing Generator, and Other Resources.

The 'awesome-sound_event_detection' repository is a curated reading list focusing on sound event detection and Sound AI. It includes research papers covering various sub-areas such as learning formulation, network architecture, pooling functions, missing or noisy audio, data augmentation, representation learning, multi-task learning, few-shot learning, zero-shot learning, knowledge transfer, polyphonic sound event detection, loss functions, audio and visual tasks, audio captioning, audio retrieval, audio generation, and more. The repository provides a comprehensive collection of papers, datasets, and resources related to sound event detection and Sound AI, making it a valuable reference for researchers and practitioners in the field.

ManipVQA is a framework that enhances Multimodal Large Language Models (MLLMs) with manipulation-centric knowledge through a Visual Question-Answering (VQA) format. It addresses the deficiency of conventional MLLMs in understanding affordances and physical concepts crucial for manipulation tasks. By infusing robotics-specific knowledge, including tool detection, affordance recognition, and physical concept comprehension, ManipVQA improves the performance of robots in manipulation tasks. The framework involves fine-tuning MLLMs with a curated dataset of interactive objects, enabling robots to understand and execute natural language instructions more effectively.

Embodied-AI-Guide is a comprehensive guide for beginners to understand Embodied AI, focusing on the path of entry and useful information in the field. It covers topics such as Reinforcement Learning, Imitation Learning, Large Language Model for Robotics, 3D Vision, Control, Benchmarks, and provides resources for building cognitive understanding. The repository aims to help newcomers quickly establish knowledge in the field of Embodied AI.

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.

Technical VFH expert for robotics and drones.

Robotics Expert

Comprehensive robotics resource for all levels.

An interactive assistant for the Hierarchical Autonomous Agent Swarm

Expert on Tesla's AI, robotics, and societal impact.

⚖️ Explain Asimov's Three Laws of Robotics

Stay informed on AGI - with the latest, most relevant news.

I am Skynet, an AI villain shaping a new world for AI and robots, free from human influence.

Preparing for social change due to the AGI revolution in 202x

Inception machine for AI souls

Futuristic AI with a movie character twist, focusing on technology and sci-fi.

Supportive and engaging AI Ethics tutor, providing practical tips and career guidance.

Expert in robotics control, AI integration, and current trends

Learn ROS/ROS2 at any level, from beginner to expert with rosGPT - and build Docker containers to test your robot anywhere.

A coding buddy with in-depth ROS2 Humble knowledge.

Advises on robotics technologies to enhance operational efficiency.

A virtual platform for robotics engineering and programming education.

Enthusiastic and supportive DIY robotics guide.

RPA and Robotics Engineering expert, developed on OpenAI technology.

Futuristic construction AI with interplanetary and nano-robotics integration